The document summarizes a research paper that proposes a Particle Swarm Optimization–Long Short-Term Memory based channel estimation method (PSO-LSTMEstNet) for wireless sensor networks and Internet of Things applications. The key points are:
1. PSO-LSTMEstNet uses a PSO algorithm to optimize the input weights of an LSTM network for channel estimation. This allows the model to dynamically adapt to changing channel conditions.
2. A hybrid beamforming approach is used to group users based on their channel conditions. PSO then estimates the network characteristics after an initial channel parameter approximation from received data.
3. An evaluation shows PSO-LSTMEstNet enhances bit error rate performance over
The document discusses various literature on OFDM and MC-CDMA techniques. It summarizes 17 research papers on topics like using wavelet packets instead of Fourier transform in MC-CDMA to improve bandwidth efficiency and reduce interference. It also discusses using techniques like DWT, Radon transform, and antenna diversity with MC-CDMA and comparing the BER performance of different approaches in various channel conditions like AWGN, Rayleigh fading and frequency selective fading channels. The rationale given is that replacing Fourier transform with wavelet packets in MC-CDMA can eliminate the need for cyclic prefix and improve spectral efficiency.
The document surveys 17 literature sources on multi-carrier modulation techniques like OFDM and MC-CDMA. Several sources propose using wavelet transforms instead of Fourier transforms to improve bandwidth efficiency and reduce interference for MC-CDMA systems. Simulation results from the literature show that wavelet packet based MC-CDMA can outperform FFT based MC-CDMA in terms of lower bit error rates, especially in frequency selective fading channels. The rationale given is that wavelet transforms eliminate the need for cyclic prefixes, thereby improving spectral efficiency over traditional MC-CDMA schemes.
IJCER (www.ijceronline.com) International Journal of computational Engineerin...ijceronline
This document summarizes a research paper that proposes a new algorithm for congestion control in Wavelength Division Multiplexing (WDM) optical networks. The algorithm aims to improve network survivability and reduce congestion. It analyzes existing congestion issues in WDM networks and formulates the problem the new algorithm seeks to address. The proposed algorithm will be tested through simulations to evaluate its performance at reducing congestion compared to existing strategies. The research has the potential to provide cost-effective solutions for congestion control in developing countries.
Optical network is an emerging technology for data communication
inworldwide. The information is transmitted from the source to destination
through the fiber optics. All optical network (AON) provides good
transmission transparency, good expandability, large bandwidth, lower bit
error rate (BER), and high processing speed. Link failure and node failure
haveconsistently occurred in the traditional methods. In order to overcome
the above mentioned issues, this paper proposes a robust software defined
switching enabled fault localization framework (SDSFLF) to monitor the
node and link failure in an AON. In this work, a novel faulty node
localization (FNL) algorithm is exploited to locate the faulty node. Then, the
software defined faulty link detection (SDFLD) algorithm that addresses the
problem of link failure. The failures are localized in multi traffic stream
(MTS) and multi agent system (MAS). Thus, the throughput is improved in
SDSFLF compared than other existing methods like traditional routing and
wavelength assignment (RWA), simulated annealing (SA) algorithm, attackaware RWA (A-RWA) convex, longest path first (LPF) ordering, and
biggest source-destination node degree (BND) ordering. The performance of
the proposed algorithm is evaluated in terms of network load, wavelength
utilization, packet loss rate, and burst loss rate. Hence, proposed SDSFLF
assures that high performance is achieved than other traditional techniques.
Investigation of the performance of multi-input multi-output detectors based...IJECEIAES
The next generation of wireless cellular communication networks must be energy efficient, extremely reliable, and have low latency, leading to the necessity of using algorithms based on deep neural networks (DNN) which have better bit error rate (BER) or symbol error rate (SER) performance than traditional complex multi-antenna or multi-input multi-output (MIMO) detectors. This paper examines deep neural networks and deep iterative detectors such as OAMP-Net based on information theory criteria such as maximum correntropy criterion (MCC) for the implementation of MIMO detectors in non-Gaussian environments, and the results illustrate that the proposed method has better BER or SER performance.
This document summarizes a paper presented at the 2023 International Conference on Computer Communication and Informatics. The paper proposes a novel interference mitigation technique and signal prediction method for future wireless communication. It discusses using IDMA (interleaved division multiple access) which improves error rate performance by suppressing interference. It also evaluates using Elliot wave theory to predict mobile signal strength without requiring extra hardware. Simulation results show IDMA with space-time transmit diversity and 256 quantization levels achieves a 10^-4 bit error rate at -0.5 dB. The paper concludes IDMA is a promising technology but further research is needed to explore its potential.
Optimize the Network Coding Paths to Enhance the Coding Protection in Wireles...IJCNCJournal
Efficient protection techniques for multimedia data transfer over Wireless Sensor Network (WSN) are very essential issues. In noisy Wireless Multimedia Sensor Networks (WMSN) Quality of Service (QoS) is a challenging task due to bandwidth and limited energy, and unpredictable channel conditions. Therefore, Forward Error Correction (FEC), a class of channel coding has been widely used in WSN. Nevertheless, the bulky size of multimedia data makes it more difficult to be transported over the noisy multi-hop wireless network. Moreover, the efficiency of FEC drops as the number of hops increases. In this paper, an optimized protection technique based on network coding and rateless code has been proposed to enhance the throughput and reduce overhead during data transfer in WMSN. The performance of NCP-OPR is enhanced via Optimal Network Path Model (ONPM) where the best available paths are optimally selected using Particle Swarm Optimization (PSO). In conjunction with the proposed protection scheme, the proposed ONPM is intended for limited power WSN by optimally distributing the power usage among the network paths so that the throughput can be improved.
Optimize the Network Coding Paths to Enhance the Coding Protection in Wireles...IJCNCJournal
- The document proposes an optimized protection technique using network coding and rateless codes to enhance throughput and reduce overhead during data transfer in wireless multimedia sensor networks.
- It presents an Optimal Network Path Model (ONPM) that uses Particle Swarm Optimization to select the best available paths in a way that optimally distributes power usage among network paths to improve throughput.
- The performance of the proposed ONPM is evaluated through simulations and compared to existing algorithms, showing it can enhance coding protection and effectively optimize network paths to improve data transfer in wireless multimedia sensor networks.
The document discusses various literature on OFDM and MC-CDMA techniques. It summarizes 17 research papers on topics like using wavelet packets instead of Fourier transform in MC-CDMA to improve bandwidth efficiency and reduce interference. It also discusses using techniques like DWT, Radon transform, and antenna diversity with MC-CDMA and comparing the BER performance of different approaches in various channel conditions like AWGN, Rayleigh fading and frequency selective fading channels. The rationale given is that replacing Fourier transform with wavelet packets in MC-CDMA can eliminate the need for cyclic prefix and improve spectral efficiency.
The document surveys 17 literature sources on multi-carrier modulation techniques like OFDM and MC-CDMA. Several sources propose using wavelet transforms instead of Fourier transforms to improve bandwidth efficiency and reduce interference for MC-CDMA systems. Simulation results from the literature show that wavelet packet based MC-CDMA can outperform FFT based MC-CDMA in terms of lower bit error rates, especially in frequency selective fading channels. The rationale given is that wavelet transforms eliminate the need for cyclic prefixes, thereby improving spectral efficiency over traditional MC-CDMA schemes.
IJCER (www.ijceronline.com) International Journal of computational Engineerin...ijceronline
This document summarizes a research paper that proposes a new algorithm for congestion control in Wavelength Division Multiplexing (WDM) optical networks. The algorithm aims to improve network survivability and reduce congestion. It analyzes existing congestion issues in WDM networks and formulates the problem the new algorithm seeks to address. The proposed algorithm will be tested through simulations to evaluate its performance at reducing congestion compared to existing strategies. The research has the potential to provide cost-effective solutions for congestion control in developing countries.
Optical network is an emerging technology for data communication
inworldwide. The information is transmitted from the source to destination
through the fiber optics. All optical network (AON) provides good
transmission transparency, good expandability, large bandwidth, lower bit
error rate (BER), and high processing speed. Link failure and node failure
haveconsistently occurred in the traditional methods. In order to overcome
the above mentioned issues, this paper proposes a robust software defined
switching enabled fault localization framework (SDSFLF) to monitor the
node and link failure in an AON. In this work, a novel faulty node
localization (FNL) algorithm is exploited to locate the faulty node. Then, the
software defined faulty link detection (SDFLD) algorithm that addresses the
problem of link failure. The failures are localized in multi traffic stream
(MTS) and multi agent system (MAS). Thus, the throughput is improved in
SDSFLF compared than other existing methods like traditional routing and
wavelength assignment (RWA), simulated annealing (SA) algorithm, attackaware RWA (A-RWA) convex, longest path first (LPF) ordering, and
biggest source-destination node degree (BND) ordering. The performance of
the proposed algorithm is evaluated in terms of network load, wavelength
utilization, packet loss rate, and burst loss rate. Hence, proposed SDSFLF
assures that high performance is achieved than other traditional techniques.
Investigation of the performance of multi-input multi-output detectors based...IJECEIAES
The next generation of wireless cellular communication networks must be energy efficient, extremely reliable, and have low latency, leading to the necessity of using algorithms based on deep neural networks (DNN) which have better bit error rate (BER) or symbol error rate (SER) performance than traditional complex multi-antenna or multi-input multi-output (MIMO) detectors. This paper examines deep neural networks and deep iterative detectors such as OAMP-Net based on information theory criteria such as maximum correntropy criterion (MCC) for the implementation of MIMO detectors in non-Gaussian environments, and the results illustrate that the proposed method has better BER or SER performance.
This document summarizes a paper presented at the 2023 International Conference on Computer Communication and Informatics. The paper proposes a novel interference mitigation technique and signal prediction method for future wireless communication. It discusses using IDMA (interleaved division multiple access) which improves error rate performance by suppressing interference. It also evaluates using Elliot wave theory to predict mobile signal strength without requiring extra hardware. Simulation results show IDMA with space-time transmit diversity and 256 quantization levels achieves a 10^-4 bit error rate at -0.5 dB. The paper concludes IDMA is a promising technology but further research is needed to explore its potential.
Optimize the Network Coding Paths to Enhance the Coding Protection in Wireles...IJCNCJournal
Efficient protection techniques for multimedia data transfer over Wireless Sensor Network (WSN) are very essential issues. In noisy Wireless Multimedia Sensor Networks (WMSN) Quality of Service (QoS) is a challenging task due to bandwidth and limited energy, and unpredictable channel conditions. Therefore, Forward Error Correction (FEC), a class of channel coding has been widely used in WSN. Nevertheless, the bulky size of multimedia data makes it more difficult to be transported over the noisy multi-hop wireless network. Moreover, the efficiency of FEC drops as the number of hops increases. In this paper, an optimized protection technique based on network coding and rateless code has been proposed to enhance the throughput and reduce overhead during data transfer in WMSN. The performance of NCP-OPR is enhanced via Optimal Network Path Model (ONPM) where the best available paths are optimally selected using Particle Swarm Optimization (PSO). In conjunction with the proposed protection scheme, the proposed ONPM is intended for limited power WSN by optimally distributing the power usage among the network paths so that the throughput can be improved.
Optimize the Network Coding Paths to Enhance the Coding Protection in Wireles...IJCNCJournal
- The document proposes an optimized protection technique using network coding and rateless codes to enhance throughput and reduce overhead during data transfer in wireless multimedia sensor networks.
- It presents an Optimal Network Path Model (ONPM) that uses Particle Swarm Optimization to select the best available paths in a way that optimally distributes power usage among network paths to improve throughput.
- The performance of the proposed ONPM is evaluated through simulations and compared to existing algorithms, showing it can enhance coding protection and effectively optimize network paths to improve data transfer in wireless multimedia sensor networks.
Enhancement of outage probability for down link cooperative non-orthogonal m...IJECEIAES
Future wireless networks are expected to face several issues, but cooperative non-orthogonal multiple access (C-NOMA) is a promising technology that could help solve them by providing unprecedented levels of connection and system capacity. In this regard, the influence of the power location coefficient (PLC) for remote users adopting multiple-input-multiple-output (MIMO) and massive MIMO has been explored to provide effective performance. The goal of this study is to design fifth-generation (5G) downlink (DL) NOMA power domain (PD) networks with a variety of distances and PLCs for remote users and then to compare their outage probability (OP) performance versus signal to noise ratio (SNR). As a novel approach to improving OP performance rate and mitigating the influence of the PLC for remote users, DL C-NOMA is combined with 16×16, 32×23, and 64×64 MIMO and 128×128, 256×256, and 512×512 massive MIMO. The results were obtained that the 64×64 MIMO improves the OP for the remote user by 65.0E-03, while the 512×512 massive MIMO achieved an improvement that reaches 1.0E-06 for the PLC of 0.8 at SNR of 14 dB. The Rayleigh fading channels and MATLAB simulation tools were utilized to carry out the study work.
MULTI USER DETECTOR IN CDMA USING ELLIPTIC CURVE CRYPTOGRAPHYVLSICS Design
Code division multiple access (CDMA) is used in various radio communication techniques due to its advantages. In CDMA one of the most important processes is multi user detection (MUD). There are numerous methods for MUD in CDMA, but in most of the methods, they identify the exact user but the interference signal is high. One of the methods used for MUD in CDM A is elliptic curve cryptography (ECC). Normally, the multi user detector in CDMA using elliptic curve cryptography is performed by using one prime field. In ECC method the exact user is identified and also interference signal reduces comparing with other techniques. To reduce the interference signal to very low, here propose a new technique for MUD in CDMA using ECC. The proposed technique uses multiple prime numbers for key generation. By generating key using different prime numbers using ECC, the bit error rate was very low. The results shows the performance of the proposed for reduce in bit error rate for MUD in CDMA.
Analysis of System Capacity and Spectral Efficiency of Fixed-Grid NetworkIJCNCJournal
The document analyzes the system capacity and spectral efficiency of a fixed-grid optical network using different modulation formats. It simulates a fixed-grid network using polarization division multiplexing and transmits 100-200 Gbps data rates using PM-QPSK, PM-8QAM, and PM-16QAM modulation. The achieved spectral efficiencies were 2, 3, and 4 bits/s/Hz respectively. The modulation formats provided system capacities of 8-9, 12-13.5, and 16-18 Tbps, reaching transmission distances of 3000, 1300, and 700 km with a bit error rate below 2x10-3. It examines the received optical power and bandwidth requirements for different modulations in a fixed grid
Cross Layering using Reinforcement Learning in Cognitive Radio-based Industri...IJCNCJournal
The coupling of multiple protocol layers for a Cognitive Radio-based Industrial Internet of Ad-hoc Sensor Network, enables better interaction, coordination, and joint optimization of different protocols in achieving remarkable performance improvements. In this paper, network, and medium access control (MAC) layer functionalities are cross-layered by developing the joint strategy of routing and effective spectrum sensing and Dynamic Channel Selection (DCS) using the Reinforcement Learning (RL) algorithm. In an industrial ad-hoc scenario, the network layer utilizes the sensed spectrum and selected channel by MAC layer for next-hop routing. MAC layer utilizes the lowest known transmission delay of a channel for a single hop as computed by the network layer, which improves the MAC channel selection operation. The applied RLbased technique (Q learning) enables the CR Secondary Users (SUs) to sense, learn, and make the optimal decision on their environment of operations. The proposed RLCLD schemes improve the SU network performance up to 30% as compared to conventional methods.
CROSS LAYERING USING REINFORCEMENT LEARNING IN COGNITIVE RADIO-BASED INDUSTRI...IJCNCJournal
The coupling of multiple protocol layers for a Cognitive Radio-based Industrial Internet of Ad-hoc Sensor
Network, enables better interaction, coordination, and joint optimization of different protocols in achieving
remarkable performance improvements. In this paper, network, and medium access control (MAC) layer
functionalities are cross-layered by developing the joint strategy of routing and effective spectrum sensing
and Dynamic Channel Selection (DCS) using the Reinforcement Learning (RL) algorithm. In an industrial
ad-hoc scenario, the network layer utilizes the sensed spectrum and selected channel by MAC layer for
next-hop routing. MAC layer utilizes the lowest known transmission delay of a channel for a single hop as
computed by the network layer, which improves the MAC channel selection operation. The applied RLbased technique (Q learning) enables the CR Secondary Users (SUs) to sense, learn, and make the optimal
decision on their environment of operations. The proposed RLCLD schemes improve the SU network
performance up to 30% as compared to conventional methods.
This document summarizes a research paper on using time-domain signal cross-correlation for spectrum sensing in cognitive radio systems applied to vehicular ad-hoc networks (VANETs). It aims to address spectrum scarcity issues in VANETs by allowing vehicles to opportunistically access TV white space spectrum when licensed spectrum is unavailable. The time-domain symbol cross-correlation technique is analyzed for spectrum sensing performance over Rayleigh fading channels. Analytical expressions for average miss detection probability are derived and simulation results show the probability of miss detection decreases with increasing SNR and number of secondary users. The time-domain symbol cross-correlation method provides good spectrum sensing performance at low SNRs for cognitive radio in VANETs.
Iaetsd comparative study mimo ofdm, cdma-sdmaIaetsd Iaetsd
This document compares and contrasts MIMO OFDM, CDMA-SDMA, and multi-user detection techniques for wireless communication systems. It discusses how MIMO OFDM can achieve high data rates with frequency and antenna diversity. Space division multiple access (SDMA) is introduced as an application of MIMO that improves spectral efficiency by multiplexing signals based on spatial signatures. The document also examines multi-user detection methods like linear detection, minimum mean square error, and successive interference cancellation that are needed for robust SDMA performance as the number of users increases.
Analysis of System Capacity and Spectral Efficiency of Fixed-Grid NetworkIJCNCJournal
In this article, the performance of a fixed grid network is examined for various modulation formats to estimate the system's capacity and spectral efficiency. The optical In-phase Quadrature Modulator (IQM) structure is used to build a fixed grid network modulation, and the homodyne detection approach is used for the receiver. Data multiplexing is accomplished using the Polarization Division Multiplexed (PDM) technology. 100 Gbps, 150 Gbps, and 200 Gbps data rates are transmitted under these circumstances utilizing various modulation formats. Various pre-processing and signal recovery steps are explained by using modern digital signal processing systems. The achieved spectrum efficiencies for PM-QPSK, PM-8 QAM, and PM-16 QAM, respectively, were 2, 3, and 4 (bits/s)/Hz. Different modulation like PM-QPSK, PM-8-QAM, and PM-16-QAM each has system capacities of 8-9, 12-13.5, and 16-18 Tbps and it reaches transmission distances of 3000, 1300, and 700 kilometers with acceptable Bit Error Rate (BER≤ 2× 10-3) respectively. Peak optical power for received signal detection and full width at half maximum is noted for the different modulations under a fixed grind network.
DYNAMIC OPTIMIZATION OF OVERLAPAND- ADD LENGTH OVER MBOFDM SYSTEM BASED ON SN...cscpconf
An important role performed by Zero Padding (ZP) in multi-band OFDM (MB-OFDM) System.
This role show for low-complexity in résistance against multipath interference by reducing
inter-carrier interference (ICI) and eliminating the inter-symbol interference (ISI) Also, zeropadded
suffix can be used to eliminate ripples in the power spectral density in order to conform
to FCC requirements.
At the receiver of MB-OFDM system needs to use of a technique called as overlap-and-add
(OLA). Which maintain the circular convolution property and take the multipath energy of the
channel.
In this paper, we proposed a method of performing overlap-and-add length for zero padded
suffixes. Then, we studied the effect of this method, dynamic optimization of overlap-and-add
(OLA) equalization, on the performance of MBOFDM system on Bit Error Rate (BER) with
AWGN channel and Saleh-Valenzuela (S-V) Multipath channel Model.
In the dynamic optimization OLA, the Length of ZP depends on length of channel impulse
response (CIR). These measures, based on SNR, insert the ZP according to the measurement.
Dynamic optimization of length of ZP improves the Performance of MBOFDM system. In fact
we developed a technique to select the length of ZP as function of SNR and CIR
estimate(repetition). In our simulation this technique improve to 3 dB at BER=10-2 with a
multipath channels CM4.
An important role performed by Zero Padding (ZP) in multi-band OFDM (MB-OFDM) System.
This role show for low-complexity in résistance against multipath interference by reducing
inter-carrier interference (ICI) and eliminating the inter-symbol interference (ISI) Also, zeropadded
suffix can be used to eliminate ripples in the power spectral density in order to conform
to FCC requirements.
At the receiver of MB-OFDM system needs to use of a technique called as overlap-and-add
(OLA). Which maintain the circular convolution property and take the multipath energy of the
channel.
In this paper, we proposed a method of performing overlap-and-add length for zero padded
suffixes. Then, we studied the effect of this method, dynamic optimization of overlap-and-add
(OLA) equalization, on the performance of MBOFDM system on Bit Error Rate (BER) with
AWGN channel and Saleh-Valenzuela (S-V) Multipath channel Model.
In the dynamic optimization OLA, the Length of ZP depends on length of channel impulse
response (CIR). These measures, based on SNR, insert the ZP according to the measurement.
Dynamic optimization of length of ZP improves the Performance of MBOFDM system. In fact
we developed a technique to select the length of ZP as function of SNR and CIR
estimate(repetition). In our simulation this technique improve to 3 dB at BER=10-2 with a
multipath channels CM4.
This document summarizes a research paper that proposes using deep learning for joint symbol detection in cooperative non-orthogonal multiple access (C-NOMA) wireless networks. The deep learning-based detection (DLDet) performs multi-user symbol detection for both near and far users simultaneously based only on received pilot responses, without requiring additional channel estimation or an iterative detector. Simulation results show the DLDet approach outperforms conventional C-NOMA and threshold-based selective C-NOMA schemes, achieving performance gains of up to 10 dB and 3-7 dB respectively. The DLDet also provides robust detection across different fading channels, though it was trained for Rayleigh fading only, and outperforms the benchmark schemes even when they
Impulse Radio Ultra WideBand (IR-UWB) commu- nication has proven to be an important
technique for supporting high-rate, short-range, and low-power communication. In this paper, using
detailed models of typical IR-UWB transmitter and receiver structures, we model the energy
consumption per information bit in a single linkof an IR-UWB system, considering packet overhead,
retransmissions, and a Nakagami-m fading channel. Using this model, we minimize the energy
consumption per information bit by finding the optimum packet length and the optimum number of
RAKE fingers at the receiver for different transmission distances, using Differential Phase-shift keying
(DBPSK), Differential Pulse-position Modulation (DPPM) and On-off Keying (OOK), with coherent
and non-coherent detection. The increasing demand for wireless communication introduces efficient
spectrum utilization challenge. To address this challenge, cognitive radio (CR) is emerged as the key
technology; which enables opportunistic access to the spectrum. CR is a form of wireless
communication in which a transceiver can intelligently detect which communication channels are in
use and which are not, and instantly move into vacant channels while avoiding occupied ones..
This document discusses and compares wireless communication technologies including OFDMA, SC-FDMA, CDMA, and LTE. It provides an overview of these technologies, how they have evolved over time, and their performance. Key points discussed include how LTE uses OFDMA for downlinks and SC-FDMA for uplinks, the benefits of MIMO techniques for improving spectral efficiency, and methods for estimating signal-to-noise ratio to enable adaptive modulation schemes. The document also includes figures comparing parameters of various wireless standards.
ANALYSIS OF ROBUST MILTIUSER DETECTION TECHNIQUE FOR COMMUNICATION SYSTEMIJARIIE JOURNAL
This document summarizes a research paper that analyzes a robust multiuser detection technique called Group Based Successive Interference Cancellation (GSIC) for communication systems. GSIC is a nonlinear approach that applies successive interference cancellation processing to groups of signals based on their strength, rather than individual signals. This technique aims to improve the bit error rate compared to conventional successive interference cancellation schemes by reducing delay and increasing signal-to-noise ratio. The document provides background on multiuser detection and CDMA systems, describes the GSIC technique and methodology used to analyze it through MATLAB simulations, and reviews related work on successive interference cancellation approaches.
Optimal Channel and Relay Assignment in Ofdmbased Multi-Relay Multi-Pair Two-...ijcnes
Efficient utilization of radio resources in wireless networks is crucial and has been investigated extensively. This letter considers a wireless relay network where multiple user pairs conduct bidirectional communications via multiple relays based on orthogonal frequency-division multiplexing (OFDM) transmission. The joint optimization of channel and relay assignment, including subcarrier pairing, subcarrier allocation as well as relay selection, for total throughput maximization is formulated as a combinatorial optimization problem. Using a graph theoretical approach, we solve the problem optimally in polynomial time by transforming it into a maximum weighted bipartite matching (MWBM) problem. Simulation studies are carried out to evaluate the network total throughput versus transmit power per node and the number of relay nodes
NEW TECHNOLOGY FOR MACHINE TO MACHINE COMMUNICATION IN SOFTNET TOWARDS 5Gijwmn
Machine to Machine communication or M2M, refers to a model of communication where devices communicate directly with each other using the available wired or wireless channels. M2M is a new concept proposed under 3GPP(3rd Generation Partnership Project); several research are working on providing solutions for M2M communication for the 5G networks. Challenges associated with M2M communication are the lack of standards, security, poor infrastructure, interoperability and diverse architecture. In this paper, we propose a new mechanism called TM2M5G (The Machine to Machine for 5G) based on SOFTNET platform which results in support of 5G heterogeneous network. In this paper, we
propose the architecture for M2M communication based on SOFTNET and provide new features support like security algorithms for data transmission among devices and scheduling algorithm for seamless transmission of data packets over the network. Finallysimulation results ofthis algorithm based on a system level simulator, considering two different approaches for analyzing the parameters such as delay, throughput and bandwidth are presented.
NEW TECHNOLOGY FOR MACHINE TO MACHINE COMMUNICATION IN SOFTNET TOWARDS 5Gijwmn
Machine to Machine communication or M2M, refers to a model of communication where devices
communicate directly with each other using the available wired or wireless channels. M2M is a new
concept proposed under 3GPP(3rd Generation Partnership Project); several research are working on
providing solutions for M2M communication for the 5G networks. Challenges associated with M2M
communication are the lack of standards, security, poor infrastructure, interoperability and diverse
architecture. In this paper, we propose a new mechanism called TM2M5G (The Machine to Machine for
5G) based on SOFTNET platform which results in support of 5G heterogeneous network. In this paper, we
propose the architecture for M2M communication based on SOFTNET and provide new features support
like security algorithms for data transmission among devices and scheduling algorithm for seamless
transmission of data packets over the network. Finallysimulation results ofthis algorithm based on a system
level simulator, considering two different approaches for analyzing the parameters such as delay,
throughput and bandwidth are presented.
On the performance of non-orthogonal multiple access (NOMA) using FPGAIJECEIAES
In this paper, non-orthogonal multiple access (NOMA) is designed and implemented for the fifth generation (5G) of multi-user wireless communication. Field-programmable gate array (FPGA) is considered for the implementation of this technique for two users. NOMA is applied in downlink phase of the base-station (BS) by applying power allocation mechanism for far and near users, in which one signal contains the superposition of two scaled signals depending on the distance of each user from the BS. We assume an additive white Gaussian noise (AWGN) channel for each user in the presence of the interference due to the non-orthogonality between the two users’ signals. Therefore, successive-interference cancellation (SIC) is exploited to remove the undesired signal of the other user. The outage probability and the biterror rate performance are presented over different signal-to-interference-plus-noise ratio (SINR). Furthermore, Monte-Carlo simulations via Matlab are utilized to verify the results obtained by FPGA, which show exact-close match.
DYNAMIC OPTIMIZATION OF OVERLAP-AND-ADD LENGTH OVER MIMO MBOFDM SYSTEM BASED ...ijwmn
An important role performed by Zero Padding (ZP) in multi-band OFDM (MB-OFDM) System. This role
show for low-complexity in résistance against multipath interference by reducing inter-carrier interference
(ICI) and eliminating the inter-symbol interference (ISI) Also, zero-padded suffix can be used to eliminate
ripples in the power spectral density in order to conform to FCC requirements. At the receiver of MB-OFDM system needs to use of a technique called as overlap-and-add (OLA). Which maintain the circular convolution property and take the multipath energy of the channel.In this paper, we proposed a method of performing overlap-and-add length for zero padded suffixes. Then,we studied the effect of this method, dynamic optimization of overlap-and-add (OLA) equalization, on the performance of MIMO MBOFDM system on Bit Error Rate (BER) with AWGN channel and SalehValenzuela (S-V) Multipath channel Model.In the dynamic optimization OLA, the Length of ZP depends on length of channel impulse response (CIR).
These measures, based on SNR, insert the ZP according to the measurement.Dynamic optimization of length of ZP improves the Performance of MIMO MBOFDM system. In fact wedeveloped a technique to select the length of ZP as function of SNR and CIR estimate. In our simulation
this technique improve to 0.6 dB at BER=10-2 with a multipath channels CM4
Wideband Sensing for Cognitive Radio Systems in Heterogeneous Next Generation...CSCJournals
Mobile Next Generation Network (MNGN) is characterized as heterogeneous network where variety of access technologies are meant to coexist. Decisions on choosing an air interface that meets a particular need at a particular time will be shifted from the network’s side to (a more intelligent) user’s side. On top of that network operators and regularities have come to the realization that assigned spectrum bands are not utilized as they should be. Cognitive radio stands out as a candidate technology to address many emerging issues in MNGN such as capacity, quality of service and spectral efficiency. As a transmission strategy, cognitive radio systems depend greatly on sensing the radio environment. In this paper, we present a novel approach for interference characterization in cognitive radio networks based on wideband chirp signal. The results presented show that improved sensing accuracy is maintained at tolerable system complexity.
Rendezvous Sequence Generation Algorithm for Cognitive Radio Networks in Post...IJCNCJournal
Recent natural disasters have inflicted tremendous damage on humanity, with their scale progressively increasing and leading to numerous casualties. Events such as earthquakes can trigger secondary disasters, such as tsunamis, further complicating the situation by destroying communication infrastructures. This destruction impedes the dissemination of information about secondary disasters and complicates post-disaster rescue efforts. Consequently, there is an urgent demand for technologies capable of substituting for these destroyed communication infrastructures. This paper proposes a technique for generating rendezvous sequences to swiftly reconnect communication infrastructures in post-disaster scenarios. We compare the time required for rendezvous using the proposed technique against existing methods and analyze the average time taken to establish links with the rendezvous technique, discussing its significance. This research presents a novel approach enabling rapid recovery of destroyed communication infrastructures in disaster environments through Cognitive Radio Network (CRN) technology, showcasing the potential to significantly improve disaster response and recovery efforts. The proposed method reduces the time for the rendezvous compared to existing methods, suggesting that it can enhance the efficiency of rescue operations in post-disaster scenarios and contribute to life-saving efforts.
Blockchain Enforced Attribute based Access Control with ZKP for Healthcare Se...IJCNCJournal
The relationship between doctors and patients is reinforced through the expanded communication channels provided by remote healthcare services, resulting in heightened patient satisfaction and loyalty. Nonetheless, the growth of these services is hampered by security and privacy challenges they confront. Additionally, patient electronic health records (EHR) information is dispersed across multiple hospitals in different formats, undermining data sovereignty. It allows any service to assert authority over their EHR, effectively controlling its usage. This paper proposes a blockchain enforced attribute-based access control in healthcare service. To enhance the privacy and data-sovereignty, the proposed system employs attribute-based access control, zero-knowledge proof (ZKP) and blockchain. The role of data within our system is pivotal in defining attributes. These attributes, in turn, form the fundamental basis for access control criteria. Blockchain is used to keep hospital information in public chain but EHR related data in private chain. Furthermore, EHR provides access control by using the attributed based cryptosystem before they are stored in the blockchain. Analysis shows that the proposed system provides data sovereignty with privacy provision based on the attributed based access control.
More Related Content
Similar to PARTICLE SWARM OPTIMIZATION–LONG SHORTTERM MEMORY BASED CHANNEL ESTIMATION WITH HYBRID BEAM FORMING POWER TRANSFER IN WSN-IOT APPLICATIONS
Enhancement of outage probability for down link cooperative non-orthogonal m...IJECEIAES
Future wireless networks are expected to face several issues, but cooperative non-orthogonal multiple access (C-NOMA) is a promising technology that could help solve them by providing unprecedented levels of connection and system capacity. In this regard, the influence of the power location coefficient (PLC) for remote users adopting multiple-input-multiple-output (MIMO) and massive MIMO has been explored to provide effective performance. The goal of this study is to design fifth-generation (5G) downlink (DL) NOMA power domain (PD) networks with a variety of distances and PLCs for remote users and then to compare their outage probability (OP) performance versus signal to noise ratio (SNR). As a novel approach to improving OP performance rate and mitigating the influence of the PLC for remote users, DL C-NOMA is combined with 16×16, 32×23, and 64×64 MIMO and 128×128, 256×256, and 512×512 massive MIMO. The results were obtained that the 64×64 MIMO improves the OP for the remote user by 65.0E-03, while the 512×512 massive MIMO achieved an improvement that reaches 1.0E-06 for the PLC of 0.8 at SNR of 14 dB. The Rayleigh fading channels and MATLAB simulation tools were utilized to carry out the study work.
MULTI USER DETECTOR IN CDMA USING ELLIPTIC CURVE CRYPTOGRAPHYVLSICS Design
Code division multiple access (CDMA) is used in various radio communication techniques due to its advantages. In CDMA one of the most important processes is multi user detection (MUD). There are numerous methods for MUD in CDMA, but in most of the methods, they identify the exact user but the interference signal is high. One of the methods used for MUD in CDM A is elliptic curve cryptography (ECC). Normally, the multi user detector in CDMA using elliptic curve cryptography is performed by using one prime field. In ECC method the exact user is identified and also interference signal reduces comparing with other techniques. To reduce the interference signal to very low, here propose a new technique for MUD in CDMA using ECC. The proposed technique uses multiple prime numbers for key generation. By generating key using different prime numbers using ECC, the bit error rate was very low. The results shows the performance of the proposed for reduce in bit error rate for MUD in CDMA.
Analysis of System Capacity and Spectral Efficiency of Fixed-Grid NetworkIJCNCJournal
The document analyzes the system capacity and spectral efficiency of a fixed-grid optical network using different modulation formats. It simulates a fixed-grid network using polarization division multiplexing and transmits 100-200 Gbps data rates using PM-QPSK, PM-8QAM, and PM-16QAM modulation. The achieved spectral efficiencies were 2, 3, and 4 bits/s/Hz respectively. The modulation formats provided system capacities of 8-9, 12-13.5, and 16-18 Tbps, reaching transmission distances of 3000, 1300, and 700 km with a bit error rate below 2x10-3. It examines the received optical power and bandwidth requirements for different modulations in a fixed grid
Cross Layering using Reinforcement Learning in Cognitive Radio-based Industri...IJCNCJournal
The coupling of multiple protocol layers for a Cognitive Radio-based Industrial Internet of Ad-hoc Sensor Network, enables better interaction, coordination, and joint optimization of different protocols in achieving remarkable performance improvements. In this paper, network, and medium access control (MAC) layer functionalities are cross-layered by developing the joint strategy of routing and effective spectrum sensing and Dynamic Channel Selection (DCS) using the Reinforcement Learning (RL) algorithm. In an industrial ad-hoc scenario, the network layer utilizes the sensed spectrum and selected channel by MAC layer for next-hop routing. MAC layer utilizes the lowest known transmission delay of a channel for a single hop as computed by the network layer, which improves the MAC channel selection operation. The applied RLbased technique (Q learning) enables the CR Secondary Users (SUs) to sense, learn, and make the optimal decision on their environment of operations. The proposed RLCLD schemes improve the SU network performance up to 30% as compared to conventional methods.
CROSS LAYERING USING REINFORCEMENT LEARNING IN COGNITIVE RADIO-BASED INDUSTRI...IJCNCJournal
The coupling of multiple protocol layers for a Cognitive Radio-based Industrial Internet of Ad-hoc Sensor
Network, enables better interaction, coordination, and joint optimization of different protocols in achieving
remarkable performance improvements. In this paper, network, and medium access control (MAC) layer
functionalities are cross-layered by developing the joint strategy of routing and effective spectrum sensing
and Dynamic Channel Selection (DCS) using the Reinforcement Learning (RL) algorithm. In an industrial
ad-hoc scenario, the network layer utilizes the sensed spectrum and selected channel by MAC layer for
next-hop routing. MAC layer utilizes the lowest known transmission delay of a channel for a single hop as
computed by the network layer, which improves the MAC channel selection operation. The applied RLbased technique (Q learning) enables the CR Secondary Users (SUs) to sense, learn, and make the optimal
decision on their environment of operations. The proposed RLCLD schemes improve the SU network
performance up to 30% as compared to conventional methods.
This document summarizes a research paper on using time-domain signal cross-correlation for spectrum sensing in cognitive radio systems applied to vehicular ad-hoc networks (VANETs). It aims to address spectrum scarcity issues in VANETs by allowing vehicles to opportunistically access TV white space spectrum when licensed spectrum is unavailable. The time-domain symbol cross-correlation technique is analyzed for spectrum sensing performance over Rayleigh fading channels. Analytical expressions for average miss detection probability are derived and simulation results show the probability of miss detection decreases with increasing SNR and number of secondary users. The time-domain symbol cross-correlation method provides good spectrum sensing performance at low SNRs for cognitive radio in VANETs.
Iaetsd comparative study mimo ofdm, cdma-sdmaIaetsd Iaetsd
This document compares and contrasts MIMO OFDM, CDMA-SDMA, and multi-user detection techniques for wireless communication systems. It discusses how MIMO OFDM can achieve high data rates with frequency and antenna diversity. Space division multiple access (SDMA) is introduced as an application of MIMO that improves spectral efficiency by multiplexing signals based on spatial signatures. The document also examines multi-user detection methods like linear detection, minimum mean square error, and successive interference cancellation that are needed for robust SDMA performance as the number of users increases.
Analysis of System Capacity and Spectral Efficiency of Fixed-Grid NetworkIJCNCJournal
In this article, the performance of a fixed grid network is examined for various modulation formats to estimate the system's capacity and spectral efficiency. The optical In-phase Quadrature Modulator (IQM) structure is used to build a fixed grid network modulation, and the homodyne detection approach is used for the receiver. Data multiplexing is accomplished using the Polarization Division Multiplexed (PDM) technology. 100 Gbps, 150 Gbps, and 200 Gbps data rates are transmitted under these circumstances utilizing various modulation formats. Various pre-processing and signal recovery steps are explained by using modern digital signal processing systems. The achieved spectrum efficiencies for PM-QPSK, PM-8 QAM, and PM-16 QAM, respectively, were 2, 3, and 4 (bits/s)/Hz. Different modulation like PM-QPSK, PM-8-QAM, and PM-16-QAM each has system capacities of 8-9, 12-13.5, and 16-18 Tbps and it reaches transmission distances of 3000, 1300, and 700 kilometers with acceptable Bit Error Rate (BER≤ 2× 10-3) respectively. Peak optical power for received signal detection and full width at half maximum is noted for the different modulations under a fixed grind network.
DYNAMIC OPTIMIZATION OF OVERLAPAND- ADD LENGTH OVER MBOFDM SYSTEM BASED ON SN...cscpconf
An important role performed by Zero Padding (ZP) in multi-band OFDM (MB-OFDM) System.
This role show for low-complexity in résistance against multipath interference by reducing
inter-carrier interference (ICI) and eliminating the inter-symbol interference (ISI) Also, zeropadded
suffix can be used to eliminate ripples in the power spectral density in order to conform
to FCC requirements.
At the receiver of MB-OFDM system needs to use of a technique called as overlap-and-add
(OLA). Which maintain the circular convolution property and take the multipath energy of the
channel.
In this paper, we proposed a method of performing overlap-and-add length for zero padded
suffixes. Then, we studied the effect of this method, dynamic optimization of overlap-and-add
(OLA) equalization, on the performance of MBOFDM system on Bit Error Rate (BER) with
AWGN channel and Saleh-Valenzuela (S-V) Multipath channel Model.
In the dynamic optimization OLA, the Length of ZP depends on length of channel impulse
response (CIR). These measures, based on SNR, insert the ZP according to the measurement.
Dynamic optimization of length of ZP improves the Performance of MBOFDM system. In fact
we developed a technique to select the length of ZP as function of SNR and CIR
estimate(repetition). In our simulation this technique improve to 3 dB at BER=10-2 with a
multipath channels CM4.
An important role performed by Zero Padding (ZP) in multi-band OFDM (MB-OFDM) System.
This role show for low-complexity in résistance against multipath interference by reducing
inter-carrier interference (ICI) and eliminating the inter-symbol interference (ISI) Also, zeropadded
suffix can be used to eliminate ripples in the power spectral density in order to conform
to FCC requirements.
At the receiver of MB-OFDM system needs to use of a technique called as overlap-and-add
(OLA). Which maintain the circular convolution property and take the multipath energy of the
channel.
In this paper, we proposed a method of performing overlap-and-add length for zero padded
suffixes. Then, we studied the effect of this method, dynamic optimization of overlap-and-add
(OLA) equalization, on the performance of MBOFDM system on Bit Error Rate (BER) with
AWGN channel and Saleh-Valenzuela (S-V) Multipath channel Model.
In the dynamic optimization OLA, the Length of ZP depends on length of channel impulse
response (CIR). These measures, based on SNR, insert the ZP according to the measurement.
Dynamic optimization of length of ZP improves the Performance of MBOFDM system. In fact
we developed a technique to select the length of ZP as function of SNR and CIR
estimate(repetition). In our simulation this technique improve to 3 dB at BER=10-2 with a
multipath channels CM4.
This document summarizes a research paper that proposes using deep learning for joint symbol detection in cooperative non-orthogonal multiple access (C-NOMA) wireless networks. The deep learning-based detection (DLDet) performs multi-user symbol detection for both near and far users simultaneously based only on received pilot responses, without requiring additional channel estimation or an iterative detector. Simulation results show the DLDet approach outperforms conventional C-NOMA and threshold-based selective C-NOMA schemes, achieving performance gains of up to 10 dB and 3-7 dB respectively. The DLDet also provides robust detection across different fading channels, though it was trained for Rayleigh fading only, and outperforms the benchmark schemes even when they
Impulse Radio Ultra WideBand (IR-UWB) commu- nication has proven to be an important
technique for supporting high-rate, short-range, and low-power communication. In this paper, using
detailed models of typical IR-UWB transmitter and receiver structures, we model the energy
consumption per information bit in a single linkof an IR-UWB system, considering packet overhead,
retransmissions, and a Nakagami-m fading channel. Using this model, we minimize the energy
consumption per information bit by finding the optimum packet length and the optimum number of
RAKE fingers at the receiver for different transmission distances, using Differential Phase-shift keying
(DBPSK), Differential Pulse-position Modulation (DPPM) and On-off Keying (OOK), with coherent
and non-coherent detection. The increasing demand for wireless communication introduces efficient
spectrum utilization challenge. To address this challenge, cognitive radio (CR) is emerged as the key
technology; which enables opportunistic access to the spectrum. CR is a form of wireless
communication in which a transceiver can intelligently detect which communication channels are in
use and which are not, and instantly move into vacant channels while avoiding occupied ones..
This document discusses and compares wireless communication technologies including OFDMA, SC-FDMA, CDMA, and LTE. It provides an overview of these technologies, how they have evolved over time, and their performance. Key points discussed include how LTE uses OFDMA for downlinks and SC-FDMA for uplinks, the benefits of MIMO techniques for improving spectral efficiency, and methods for estimating signal-to-noise ratio to enable adaptive modulation schemes. The document also includes figures comparing parameters of various wireless standards.
ANALYSIS OF ROBUST MILTIUSER DETECTION TECHNIQUE FOR COMMUNICATION SYSTEMIJARIIE JOURNAL
This document summarizes a research paper that analyzes a robust multiuser detection technique called Group Based Successive Interference Cancellation (GSIC) for communication systems. GSIC is a nonlinear approach that applies successive interference cancellation processing to groups of signals based on their strength, rather than individual signals. This technique aims to improve the bit error rate compared to conventional successive interference cancellation schemes by reducing delay and increasing signal-to-noise ratio. The document provides background on multiuser detection and CDMA systems, describes the GSIC technique and methodology used to analyze it through MATLAB simulations, and reviews related work on successive interference cancellation approaches.
Optimal Channel and Relay Assignment in Ofdmbased Multi-Relay Multi-Pair Two-...ijcnes
Efficient utilization of radio resources in wireless networks is crucial and has been investigated extensively. This letter considers a wireless relay network where multiple user pairs conduct bidirectional communications via multiple relays based on orthogonal frequency-division multiplexing (OFDM) transmission. The joint optimization of channel and relay assignment, including subcarrier pairing, subcarrier allocation as well as relay selection, for total throughput maximization is formulated as a combinatorial optimization problem. Using a graph theoretical approach, we solve the problem optimally in polynomial time by transforming it into a maximum weighted bipartite matching (MWBM) problem. Simulation studies are carried out to evaluate the network total throughput versus transmit power per node and the number of relay nodes
NEW TECHNOLOGY FOR MACHINE TO MACHINE COMMUNICATION IN SOFTNET TOWARDS 5Gijwmn
Machine to Machine communication or M2M, refers to a model of communication where devices communicate directly with each other using the available wired or wireless channels. M2M is a new concept proposed under 3GPP(3rd Generation Partnership Project); several research are working on providing solutions for M2M communication for the 5G networks. Challenges associated with M2M communication are the lack of standards, security, poor infrastructure, interoperability and diverse architecture. In this paper, we propose a new mechanism called TM2M5G (The Machine to Machine for 5G) based on SOFTNET platform which results in support of 5G heterogeneous network. In this paper, we
propose the architecture for M2M communication based on SOFTNET and provide new features support like security algorithms for data transmission among devices and scheduling algorithm for seamless transmission of data packets over the network. Finallysimulation results ofthis algorithm based on a system level simulator, considering two different approaches for analyzing the parameters such as delay, throughput and bandwidth are presented.
NEW TECHNOLOGY FOR MACHINE TO MACHINE COMMUNICATION IN SOFTNET TOWARDS 5Gijwmn
Machine to Machine communication or M2M, refers to a model of communication where devices
communicate directly with each other using the available wired or wireless channels. M2M is a new
concept proposed under 3GPP(3rd Generation Partnership Project); several research are working on
providing solutions for M2M communication for the 5G networks. Challenges associated with M2M
communication are the lack of standards, security, poor infrastructure, interoperability and diverse
architecture. In this paper, we propose a new mechanism called TM2M5G (The Machine to Machine for
5G) based on SOFTNET platform which results in support of 5G heterogeneous network. In this paper, we
propose the architecture for M2M communication based on SOFTNET and provide new features support
like security algorithms for data transmission among devices and scheduling algorithm for seamless
transmission of data packets over the network. Finallysimulation results ofthis algorithm based on a system
level simulator, considering two different approaches for analyzing the parameters such as delay,
throughput and bandwidth are presented.
On the performance of non-orthogonal multiple access (NOMA) using FPGAIJECEIAES
In this paper, non-orthogonal multiple access (NOMA) is designed and implemented for the fifth generation (5G) of multi-user wireless communication. Field-programmable gate array (FPGA) is considered for the implementation of this technique for two users. NOMA is applied in downlink phase of the base-station (BS) by applying power allocation mechanism for far and near users, in which one signal contains the superposition of two scaled signals depending on the distance of each user from the BS. We assume an additive white Gaussian noise (AWGN) channel for each user in the presence of the interference due to the non-orthogonality between the two users’ signals. Therefore, successive-interference cancellation (SIC) is exploited to remove the undesired signal of the other user. The outage probability and the biterror rate performance are presented over different signal-to-interference-plus-noise ratio (SINR). Furthermore, Monte-Carlo simulations via Matlab are utilized to verify the results obtained by FPGA, which show exact-close match.
DYNAMIC OPTIMIZATION OF OVERLAP-AND-ADD LENGTH OVER MIMO MBOFDM SYSTEM BASED ...ijwmn
An important role performed by Zero Padding (ZP) in multi-band OFDM (MB-OFDM) System. This role
show for low-complexity in résistance against multipath interference by reducing inter-carrier interference
(ICI) and eliminating the inter-symbol interference (ISI) Also, zero-padded suffix can be used to eliminate
ripples in the power spectral density in order to conform to FCC requirements. At the receiver of MB-OFDM system needs to use of a technique called as overlap-and-add (OLA). Which maintain the circular convolution property and take the multipath energy of the channel.In this paper, we proposed a method of performing overlap-and-add length for zero padded suffixes. Then,we studied the effect of this method, dynamic optimization of overlap-and-add (OLA) equalization, on the performance of MIMO MBOFDM system on Bit Error Rate (BER) with AWGN channel and SalehValenzuela (S-V) Multipath channel Model.In the dynamic optimization OLA, the Length of ZP depends on length of channel impulse response (CIR).
These measures, based on SNR, insert the ZP according to the measurement.Dynamic optimization of length of ZP improves the Performance of MIMO MBOFDM system. In fact wedeveloped a technique to select the length of ZP as function of SNR and CIR estimate. In our simulation
this technique improve to 0.6 dB at BER=10-2 with a multipath channels CM4
Wideband Sensing for Cognitive Radio Systems in Heterogeneous Next Generation...CSCJournals
Mobile Next Generation Network (MNGN) is characterized as heterogeneous network where variety of access technologies are meant to coexist. Decisions on choosing an air interface that meets a particular need at a particular time will be shifted from the network’s side to (a more intelligent) user’s side. On top of that network operators and regularities have come to the realization that assigned spectrum bands are not utilized as they should be. Cognitive radio stands out as a candidate technology to address many emerging issues in MNGN such as capacity, quality of service and spectral efficiency. As a transmission strategy, cognitive radio systems depend greatly on sensing the radio environment. In this paper, we present a novel approach for interference characterization in cognitive radio networks based on wideband chirp signal. The results presented show that improved sensing accuracy is maintained at tolerable system complexity.
Similar to PARTICLE SWARM OPTIMIZATION–LONG SHORTTERM MEMORY BASED CHANNEL ESTIMATION WITH HYBRID BEAM FORMING POWER TRANSFER IN WSN-IOT APPLICATIONS (20)
Rendezvous Sequence Generation Algorithm for Cognitive Radio Networks in Post...IJCNCJournal
Recent natural disasters have inflicted tremendous damage on humanity, with their scale progressively increasing and leading to numerous casualties. Events such as earthquakes can trigger secondary disasters, such as tsunamis, further complicating the situation by destroying communication infrastructures. This destruction impedes the dissemination of information about secondary disasters and complicates post-disaster rescue efforts. Consequently, there is an urgent demand for technologies capable of substituting for these destroyed communication infrastructures. This paper proposes a technique for generating rendezvous sequences to swiftly reconnect communication infrastructures in post-disaster scenarios. We compare the time required for rendezvous using the proposed technique against existing methods and analyze the average time taken to establish links with the rendezvous technique, discussing its significance. This research presents a novel approach enabling rapid recovery of destroyed communication infrastructures in disaster environments through Cognitive Radio Network (CRN) technology, showcasing the potential to significantly improve disaster response and recovery efforts. The proposed method reduces the time for the rendezvous compared to existing methods, suggesting that it can enhance the efficiency of rescue operations in post-disaster scenarios and contribute to life-saving efforts.
Blockchain Enforced Attribute based Access Control with ZKP for Healthcare Se...IJCNCJournal
The relationship between doctors and patients is reinforced through the expanded communication channels provided by remote healthcare services, resulting in heightened patient satisfaction and loyalty. Nonetheless, the growth of these services is hampered by security and privacy challenges they confront. Additionally, patient electronic health records (EHR) information is dispersed across multiple hospitals in different formats, undermining data sovereignty. It allows any service to assert authority over their EHR, effectively controlling its usage. This paper proposes a blockchain enforced attribute-based access control in healthcare service. To enhance the privacy and data-sovereignty, the proposed system employs attribute-based access control, zero-knowledge proof (ZKP) and blockchain. The role of data within our system is pivotal in defining attributes. These attributes, in turn, form the fundamental basis for access control criteria. Blockchain is used to keep hospital information in public chain but EHR related data in private chain. Furthermore, EHR provides access control by using the attributed based cryptosystem before they are stored in the blockchain. Analysis shows that the proposed system provides data sovereignty with privacy provision based on the attributed based access control.
EECRPSID: Energy-Efficient Cluster-Based Routing Protocol with a Secure Intru...IJCNCJournal
A revolutionary idea that has gained significance in technology for Internet of Things (IoT) networks backed by WSNs is the " Energy-Efficient Cluster-Based Routing Protocol with a Secure Intrusion Detection" (EECRPSID). A WSN-powered IoT infrastructure's hardware foundation is hardware with autonomous sensing capabilities. The significant features of the proposed technology are intelligent environment sensing, independent data collection, and information transfer to connected devices. However, hardware flaws and issues with energy consumption may be to blame for device failures in WSN-assisted IoT networks. This can potentially obstruct the transfer of data. A reliable route significantly reduces data retransmissions, which reduces traffic and conserves energy. The sensor hardware is often widely dispersed by IoT networks that enable WSNs. Data duplication could occur if numerous sensor devices are used to monitor a location. Finding a solution to this issue by using clustering. Clustering lessens network traffic while retaining path dependability compared to the multipath technique. To relieve duplicate data in EECRPSID, we applied the clustering technique. The multipath strategy might make the provided protocol more dependable. Using the EECRPSID algorithm, will reduce the overall energy consumption, minimize the End-to-end delay to 0.14s, achieve a 99.8% Packet Delivery Ratio, and the network's lifespan will be increased. The NS2 simulator is used to run the whole set of simulations. The EECRPSID method has been implemented in NS2, and simulated results indicate that comparing the other three technologies improves the performance measures.
Analysis and Evolution of SHA-1 Algorithm - Analytical TechniqueIJCNCJournal
A 160-bit (20-byte) hash value, sometimes called a message digest, is generated using the SHA-1 (Secure Hash Algorithm 1) hash function in cryptography. This value is commonly represented as 40 hexadecimal digits. It is a Federal Information Processing Standard in the United States and was developed by the National Security Agency. Although it has been cryptographically cracked, the technique is still in widespread usage. In this work, we conduct a detailed and practical analysis of the SHA-1 algorithm's theoretical elements and show how they have been implemented through the use of several different hash configurations.
Optimizing CNN-BiGRU Performance: Mish Activation and Comparative AnalysisIJCNCJournal
Deep learning is currently extensively employed across a range of research domains. The continuous advancements in deep learning techniques contribute to solving intricate challenges. Activation functions (AF) are fundamental components within neural networks, enabling them to capture complex patterns and relationships in the data. By introducing non-linearities, AF empowers neural networks to model and adapt to the diverse and nuanced nature of real-world data, enhancing their ability to make accurate predictions across various tasks. In the context of intrusion detection, the Mish, a recent AF, was implemented in the CNN-BiGRU model, using three datasets: ASNM-TUN, ASNM-CDX, and HOGZILLA. The comparison with Rectified Linear Unit (ReLU), a widely used AF, revealed that Mish outperforms ReLU, showcasing superior performance across the evaluated datasets. This study illuminates the effectiveness of AF in elevating the performance of intrusion detection systems.
An Hybrid Framework OTFS-OFDM Based on Mobile Speed EstimationIJCNCJournal
The Future wireless communication systems face the challenging task of simultaneously providing high-quality service (QoS) and broadband data transmission, while also minimizing power consumption, latency, and system complexity. Although Orthogonal Frequency Division Multiplexing (OFDM) has been widely adopted in 4G and 5G systems, it struggles to cope with a significant delay and Doppler spread in high mobility scenarios. To address these challenges, a novel waveform named Orthogonal Time Frequency Space (OTFS). Designers aim to outperform OFDM by closely aligning signals with the channel behaviour. In this paper, we propose a switching strategy that empowers operators to select the most appropriate waveform based on an estimated speed of the mobile user. This strategy enables the base station to dynamically choose the waveform that best suits the mobile user’s speed. Additionally, we suggest retaining an Integrated Sensing and Communication (ISAC) radar approach for accurate Doppler estimation. This provides precise information to facilitate the waveform selection procedure. By leveraging the switching strategy and harnessing the Doppler estimation capabilities of an ISAC radar.Our proposed approach aims to enhance the performance of wireless communication systems in high mobility cases. Considering the complexity of waveform processing, we introduce an optimized hybrid system that combines OTFS and OFDM, resulting in reduced complexity while still retaining performance benefits.This hybrid system presents a promising solution for improving the performance of wireless communication systems in higher mobility.The simulation results validate the effectiveness of our approach, demonstrating its potential advantages for future wireless communication systems. The effectiveness of the proposed approach is validated by simulation results as it will be illustrated.
Enhanced Traffic Congestion Management with Fog Computing - A Simulation-Base...IJCNCJournal
Accurate latency computation is essential for the Internet of Things (IoT) since the connected devices generate a vast amount of data that is processed on cloud infrastructure. However, the cloud is not an optimal solution. To overcome this issue, fog computing is used to enable processing at the edge while still allowing communication with the cloud. Many applications rely on fog computing, including traffic management. In this paper, an Intelligent Traffic Congestion Mitigation System (ITCMS) is proposed to address traffic congestion in heavily populated smart cities. The proposed system is implemented using fog computing and tested in a crowdedCairo city. The results obtained indicate that the execution time of the simulation is 4,538 seconds, and the delay in the application loop is 49.67 seconds. The paper addresses various issues, including CPU usage, heap memory usage, throughput, and the total average delay, which are essential for evaluating the performance of the ITCMS. Our system model is also compared with other models to assess its performance. A comparison is made using two parameters, namely throughput and the total average delay, between the ITCMS, IOV (Internet of Vehicle), and STL (Seasonal-Trend Decomposition Procedure based on LOESS). Consequently, the results confirm that the proposed system outperforms the others in terms of higher accuracy, lower latency, and improved traffic efficiency.
Rendezvous Sequence Generation Algorithm for Cognitive Radio Networks in Post...IJCNCJournal
Recent natural disasters have inflicted tremendous damage on humanity, with their scale progressively increasing and leading to numerous casualties. Events such as earthquakes can trigger secondary disasters, such as tsunamis, further complicating the situation by destroying communication infrastructures. This destruction impedes the dissemination of information about secondary disasters and complicates post-disaster rescue efforts. Consequently, there is an urgent demand for technologies capable of substituting for these destroyed communication infrastructures. This paper proposes a technique for generating rendezvous sequences to swiftly reconnect communication infrastructures in post-disaster scenarios. We compare the time required for rendezvous using the proposed technique against existing methods and analyze the average time taken to establish links with the rendezvous technique, discussing its significance. This research presents a novel approach enabling rapid recovery of destroyed communication infrastructures in disaster environments through Cognitive Radio Network (CRN) technology, showcasing the potential to significantly improve disaster response and recovery efforts. The proposed method reduces the time for the rendezvous compared to existing methods, suggesting that it can enhance the efficiency of rescue operations in post-disaster scenarios and contribute to life-saving efforts.
Vehicle Ad Hoc Networks (VANETs) have become a viable technology to improve traffic flow and safety on the roads. Due to its effectiveness and scalability, the Wingsuit Search-based Optimised Link State Routing Protocol (WS-OLSR) is frequently used for data distribution in VANETs. However, the selection of MultiPoint Relays (MPRs) plays a pivotal role in WS-OLSR's performance. This paper presents an improved MPR selection algorithm tailored to WS-OLSR, designed to enhance the overall routing efficiency and reduce overhead. The analysis found that the current OLSR protocol has problems such as redundancy of HELLO and TC message packets or failure to update routing information in time, so a WS-OLSR routing protocol based on improved-MPR selection algorithm was proposed. Firstly, factors such as node mobility and link changes are comprehensively considered to reflect network topology changes, and the broadcast cycle of node HELLO messages is controlled through topology changes. Secondly, a new MPR selection algorithm is proposed, considering link stability issues and nodes. Finally, evaluate its effectiveness in terms of packet delivery ratio, end-to-end delay, and control message overhead. Simulation results demonstrate the superior performance of our improved MR selection algorithm when compared to traditional approaches.
May 2024, Volume 16, Number 3 - The International Journal of Computer Network...IJCNCJournal
The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
Vehicle Ad Hoc Networks (VANETs) have become a viable technology to improve traffic flow and safety on the roads. Due to its effectiveness and scalability, the Wingsuit Search-based Optimised Link State Routing Protocol (WS-OLSR) is frequently used for data distribution in VANETs. However, the selection of MultiPoint Relays (MPRs) plays a pivotal role in WS-OLSR's performance. This paper presents an improved MPR selection algorithm tailored to WS-OLSR, designed to enhance the overall routing efficiency and reduce overhead. The analysis found that the current OLSR protocol has problems such as redundancy of HELLO and TC message packets or failure to update routing information in time, so a WS-OLSR routing protocol based on improved-MPR selection algorithm was proposed. Firstly, factors such as node mobility and link changes are comprehensively considered to reflect network topology changes, and the broadcast cycle of node HELLO messages is controlled through topology changes. Secondly, a new MPR selection algorithm is proposed, considering link stability issues and nodes. Finally, evaluate its effectiveness in terms of packet delivery ratio, end-to-end delay, and control message overhead. Simulation results demonstrate the superior performance of our improved MR selection algorithm when compared to traditional approaches.
A Novel Medium Access Control Strategy for Heterogeneous Traffic in Wireless ...IJCNCJournal
So far, Wireless Body Area Networks (WBANs) have played a pivotal role in driving the development of intelligent healthcare systems with broad applicability across various domains. Each WBAN consists of one or more types of sensors that can be embedded in clothing, attached directly to the body, or even implanted beneath an individual's skin. These sensors typically serve asingle application. However, the traffic generated by each sensor may have distinct requirements. This diversity necessitates a dual approach: tailored treatment based on the specific needs of each traffic typeand the fulfillment of application requirements, such asreliability and timeliness. Never the less, the presence of energy constraints and the unreliable nature of wireless communications make QoS provisioning under such networks a non-trivial task. In this context, the current paper introduces a novel Medium AccessControl (MAC) strategy for the regular traffic applications of WBANs, designed to significantly enhance efficiency when compared to the established MAC protocols IEEE 802.15.4 and IEEE 802.15.6, with a particular focus on improving reliability, timeliness, and energy efficiency.
May_2024 Top 10 Read Articles in Computer Networks & Communications.pdfIJCNCJournal
The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
A Topology Control Algorithm Taking into Account Energy and Quality of Transm...IJCNCJournal
The efficient use of energy in wireless sensor networks is critical for extending node lifetime. The network topology is one of the factors that have a significant impact on the energy usage at the nodes and the quality of transmission (QoT) in the network. We propose a topology control algorithm for software-defined wireless sensor networks (SDWSNs) in this paper. Our method is to formulate topology control algorithm as a nonlinear programming (NP) problem with the objective to optimizing two metrics, maximum communication range, and desired degree. This NP problem is solved at the SDWSN controller by employing the genetic algorithm (GA) to determine the best topology. The simulation results show that the proposed algorithm outperforms the MaxPower algorithm in terms of average node degree and energy expansion ratio.
Multi-Server user Authentication Scheme for Privacy Preservation with Fuzzy C...IJCNCJournal
The integration of artificial intelligence technology with a scalable Internet of Things (IoT) platform facilitates diverse smart communication services, allowing remote users to access services from anywhere at any time. The multi-server environment within IoT introduces a flexible security service model, enabling users to interact with any server through a single registration. To ensure secure and privacy preservation services for resources, an authentication scheme is essential. Zhao et al. recently introduced a user authentication scheme for the multi-server environment, utilizing passwords and smart cards, claiming resilience against well-known attacks. This paper conducts cryptanalysis on Zhao et al.'s scheme, focusing on denial of service and privacy attacks, revealing a lack of user-friendliness. Subsequently, we propose a new multi-server user authentication scheme for privacy preservation with fuzzy commitment over the IoT environment, addressing the shortcomings of Zhao et al.'s scheme. Formal security verification of the proposed scheme is conducted using the ProVerif simulation tool. Through both formal and informal security analyses, we demonstrate that the proposed scheme is resilient against various known attacks and those identified in Zhao et al.'s scheme.
Advanced Privacy Scheme to Improve Road Safety in Smart Transportation SystemsIJCNCJournal
In -Vehicle Ad-Hoc Network (VANET), vehicles continuously transmit and receive spatiotemporal data with neighboring vehicles, thereby establishing a comprehensive 360-degree traffic awareness system. Vehicular Network safety applications facilitate the transmission of messages between vehicles that are near each other, at regular intervals, enhancing drivers' contextual understanding of the driving environment and significantly improving traffic safety. Privacy schemes in VANETs are vital to safeguard vehicles’ identities and their associated owners or drivers. Privacy schemes prevent unauthorized parties from linking the vehicle's communications to a specific real-world identity by employing techniques such as pseudonyms, randomization, or cryptographic protocols. Nevertheless, these communications frequently contain important vehicle information that malevolent groups could use to Monitor the vehicle over a long period. The acquisition of this shared data has the potential to facilitate the reconstruction of vehicle trajectories, thereby posing a potential risk to the privacy of the driver. Addressing the critical challenge of developing effective and scalable privacy-preserving protocols for communication in vehicle networks is of the highest priority. These protocols aim to reduce the transmission of confidential data while ensuring the required level of communication. This paper aims to propose an Advanced Privacy Vehicle Scheme (APV) that periodically changes pseudonyms to protect vehicle identities and improve privacy. The APV scheme utilizes a concept called the silent period, which involves changing the pseudonym of a vehicle periodically based on the tracking of neighboring vehicles. The pseudonym is a temporary identifier that vehicles use to communicate with each other in a VANET. By changing the pseudonym regularly, the APV scheme makes it difficult for unauthorized entities to link a vehicle's communications to its real-world identity. The proposed APV is compared to the SLOW, RSP, CAPS, and CPN techniques. The data indicates that the efficiency of APV is a better improvement in privacy metrics. It is evident that the AVP offers enhanced safety for vehicles during transportation in the smart city.
April 2024 - Top 10 Read Articles in Computer Networks & CommunicationsIJCNCJournal
The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
DEF: Deep Ensemble Neural Network Classifier for Android Malware DetectionIJCNCJournal
Malware is one of the threats to security of computer networks and information systems. Since malware instances are available sufficiently, there is increased interest among researchers on usage of Artificial Intelligence (AI). Of late AI-enabled methods such as machine learning (ML) and deep learning paved way for solving many real-world problems. As it is a learning-based approach, accumulated training samples help in improving thequality of training and thus leveraging malware detection accuracy. Existing deep learning methods are focusing on learning-based malware detection systems. However, there is need for improving the state of the art through ensemble approach. Towards this end, in this paper we proposed a framework known as Deep Ensemble Framework (DEF) for automatic malware detection. The framework obtains features from training samples. From given malware instance a grayscale image is generated. There is another process to extract the opcode sequences. Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) techniques are used to obtain grayscale image and opcode sequence respectively. Afterwards, a stacking ensemble is employed in order to achieve efficient malware detection and classification. Malware samples collected fromthe Internet sources and Microsoft are used for theempirical study. An algorithm known as Ensemble Learning for Automatic Malware Detection (EL-AML) is proposed to realize our framework. Another algorithm named Pre-Process is proposed to assist the EL-AML algorithm for obtaining intermediate features required by CNN and LSTM.Empirical study reveals that our framework outperforms many existing methods in terms of speed-up and accuracy.
High Performance NMF Based Intrusion Detection System for Big Data IOT TrafficIJCNCJournal
With the emergence of smart devices and the Internet of Things (IoT), millions of users connected to the network produce massive network traffic datasets. These vast datasets of network traffic, Big Data are challenging to store, deal with and analyse using a single computer. In this paper we developed parallel implementation using a High Performance Computer (HPC) for the Non-Negative Matrix Factorization technique as an engine for an Intrusion Detection System (HPC-NMF-IDS). The large IoT traffic datasets of order of millions samples are distributed evenly on all the computing cores for both storage and speedup purpose. The distribution of computing tasks involved in the Matrix Factorization takes into account the reduction of the communication cost between the computing cores. The experiments we conducted on the proposed HPC-IDS-NMF give better results than the traditional ML-based intrusion detection systems. We could train the HPC model with datasets of one million samples in only 31 seconds instead of the 40 minutes using one processor), that is a speed up of 87 times. Moreover, we have got an excellent detection accuracy rate of 98% for KDD dataset.
A Novel Medium Access Control Strategy for Heterogeneous Traffic in Wireless ...IJCNCJournal
So far, Wireless Body Area Networks (WBANs) have played a pivotal role in driving the development of intelligent healthcare systems with broad applicability across various domains. Each WBAN consists of one or more types of sensors that can be embedded in clothing, attached directly to the body, or even implanted beneath an individual's skin. These sensors typically serve asingle application. However, the traffic generated by each sensor may have distinct requirements. This diversity necessitates a dual approach: tailored treatment based on the specific needs of each traffic typeand the fulfillment of application requirements, such asreliability and timeliness. Never the less, the presence of energy constraints and the unreliable nature of wireless communications make QoS provisioning under such networks a non-trivial task. In this context, the current paper introduces a novel Medium AccessControl (MAC) strategy for the regular traffic applications of WBANs, designed to significantly enhance efficiency when compared to the established MAC protocols IEEE 802.15.4 and IEEE 802.15.6, with a particular focus on improving reliability, timeliness, and energy efficiency.
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSIJNSA Journal
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
Batteries -Introduction – Types of Batteries – discharging and charging of battery - characteristics of battery –battery rating- various tests on battery- – Primary battery: silver button cell- Secondary battery :Ni-Cd battery-modern battery: lithium ion battery-maintenance of batteries-choices of batteries for electric vehicle applications.
Fuel Cells: Introduction- importance and classification of fuel cells - description, principle, components, applications of fuel cells: H2-O2 fuel cell, alkaline fuel cell, molten carbonate fuel cell and direct methanol fuel cells.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Comparative analysis between traditional aquaponics and reconstructed aquapon...bijceesjournal
The aquaponic system of planting is a method that does not require soil usage. It is a method that only needs water, fish, lava rocks (a substitute for soil), and plants. Aquaponic systems are sustainable and environmentally friendly. Its use not only helps to plant in small spaces but also helps reduce artificial chemical use and minimizes excess water use, as aquaponics consumes 90% less water than soil-based gardening. The study applied a descriptive and experimental design to assess and compare conventional and reconstructed aquaponic methods for reproducing tomatoes. The researchers created an observation checklist to determine the significant factors of the study. The study aims to determine the significant difference between traditional aquaponics and reconstructed aquaponics systems propagating tomatoes in terms of height, weight, girth, and number of fruits. The reconstructed aquaponics system’s higher growth yield results in a much more nourished crop than the traditional aquaponics system. It is superior in its number of fruits, height, weight, and girth measurement. Moreover, the reconstructed aquaponics system is proven to eliminate all the hindrances present in the traditional aquaponics system, which are overcrowding of fish, algae growth, pest problems, contaminated water, and dead fish.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
TIME DIVISION MULTIPLEXING TECHNIQUE FOR COMMUNICATION SYSTEMHODECEDSIET
Time Division Multiplexing (TDM) is a method of transmitting multiple signals over a single communication channel by dividing the signal into many segments, each having a very short duration of time. These time slots are then allocated to different data streams, allowing multiple signals to share the same transmission medium efficiently. TDM is widely used in telecommunications and data communication systems.
### How TDM Works
1. **Time Slots Allocation**: The core principle of TDM is to assign distinct time slots to each signal. During each time slot, the respective signal is transmitted, and then the process repeats cyclically. For example, if there are four signals to be transmitted, the TDM cycle will divide time into four slots, each assigned to one signal.
2. **Synchronization**: Synchronization is crucial in TDM systems to ensure that the signals are correctly aligned with their respective time slots. Both the transmitter and receiver must be synchronized to avoid any overlap or loss of data. This synchronization is typically maintained by a clock signal that ensures time slots are accurately aligned.
3. **Frame Structure**: TDM data is organized into frames, where each frame consists of a set of time slots. Each frame is repeated at regular intervals, ensuring continuous transmission of data streams. The frame structure helps in managing the data streams and maintaining the synchronization between the transmitter and receiver.
4. **Multiplexer and Demultiplexer**: At the transmitting end, a multiplexer combines multiple input signals into a single composite signal by assigning each signal to a specific time slot. At the receiving end, a demultiplexer separates the composite signal back into individual signals based on their respective time slots.
### Types of TDM
1. **Synchronous TDM**: In synchronous TDM, time slots are pre-assigned to each signal, regardless of whether the signal has data to transmit or not. This can lead to inefficiencies if some time slots remain empty due to the absence of data.
2. **Asynchronous TDM (or Statistical TDM)**: Asynchronous TDM addresses the inefficiencies of synchronous TDM by allocating time slots dynamically based on the presence of data. Time slots are assigned only when there is data to transmit, which optimizes the use of the communication channel.
### Applications of TDM
- **Telecommunications**: TDM is extensively used in telecommunication systems, such as in T1 and E1 lines, where multiple telephone calls are transmitted over a single line by assigning each call to a specific time slot.
- **Digital Audio and Video Broadcasting**: TDM is used in broadcasting systems to transmit multiple audio or video streams over a single channel, ensuring efficient use of bandwidth.
- **Computer Networks**: TDM is used in network protocols and systems to manage the transmission of data from multiple sources over a single network medium.
### Advantages of TDM
- **Efficient Use of Bandwidth**: TDM all
TIME DIVISION MULTIPLEXING TECHNIQUE FOR COMMUNICATION SYSTEM
PARTICLE SWARM OPTIMIZATION–LONG SHORTTERM MEMORY BASED CHANNEL ESTIMATION WITH HYBRID BEAM FORMING POWER TRANSFER IN WSN-IOT APPLICATIONS
1. International Journal of Computer Networks & Communications (IJCNC) Vol.14, No.5, September 2022
DOI: 10.5121/ijcnc.2022.14505 65
PARTICLE SWARM OPTIMIZATION–LONG SHORT-
TERM MEMORY BASED CHANNEL ESTIMATION
WITH HYBRID BEAM FORMING POWER TRANSFER
IN WSN-IOT APPLICATIONS
Reginald Jude Sixtus J and Tamilarasi Muthu
Department of Electronics and Communication Engineering,
Puducherry Technological University, Puducherry, India.
ABSTRACT
Non-Orthogonal Multiple Access (NOMA) helps to overcome various difficulties in future technology
wireless communications. NOMA, when utilized with millimeter wave multiple-input multiple-output
(MIMO) systems, channel estimation becomes extremely difficult. For reaping the benefits of the NOMA
and mm-Wave combination, effective channel estimation is required. In this paper, we propose an
enhanced particle swarm optimization based long short-term memory estimator network (PSO-
LSTMEstNet), which is a neural network model that can be employed to forecast the bandwidth required in
the mm-Wave MIMO network. The prime advantage of the LSTM is that it has the capability of
dynamically adapting to the functioning pattern of fluctuating channel state. The LSTM stage with adaptive
coding and modulation enhances the BER.PSO algorithm is employed to optimize input weights of LSTM
network. The modified algorithm splits the power by channel condition of every single user. Participants
will be first sorted into distinct groups depending upon respective channel conditions, using a hybrid
beamforming approach. The network characteristics are fine-estimated using PSO-LSTMEstNet after a
rough approximation of channels parameters derived from the received data
KEYWORDS
Signal to Noise Ratio (SNR), Bit Error Rate (BER),mm-Wave, MIMO, NOMA, deep learning, optimization.
1. INTRODUCTION
With the increase in the requirement of wireless spectrum, the underdeveloped mm-Wave has
gained attention due to its enormous throughput as well as better signal economy [1]. Since the
transponder could correct for considerable signal attenuation utilizing the combinational gain
supplied mostly by Omni- directional antenna elements, it tends to be the most sought technology
in 5G transceivers [2]. The mm-Wave technology helps to reduce computational burden and
power utility. To eliminate the conflicts with some of the existing users, every radio wave link
accommodates one user at a time. [3]. As the percentage of users expands, nonlinear operations
classify the signals for every single user [4]. However, NOMA technologies could circumvent
such fundamental constraints by employing coherence programming with successive interfering
cancelation (SIC) at the receiver [5]. Multi-input signal identification is made possible mostly by
the capabilities of neural networks rather than that of the classic interference cancellation
method [6]. Transfer learning has currently gained popularity in the field of machine learning [7].
2. International Journal of Computer Networks & Communications (IJCNC) Vol.14, No.5, September 2022
66
Inter-symbol interference may occur due to wireless channels with multipath fading. the channel
estimation techniques are classified into two namely, blind and pilot-based estimation [8].
Without the assistance of a preamble or pilot signal, the wavelet coefficients of the receiver side
were used in fading channels [9]. To determine the performance indicators, a learning series
containing existing data symbols are introduced at the beginning of broadcasting [10].
Figure 1. Sequencing the pilot data from user equipment
Figure 1 shows pilot signals from various user equipment. Block-type and comb-type are the
basic categories of pilot-oriented channel estimation [11-13]. To achieve channel estimation,
OFDM symbols are regularly sent with pilots across every subcarrier in block type. Since pilot
frequencies were injected into every sub-channel of precoding over a specific period time, the
frame pilot scheme is well adapted for intensity and slow multi-path fading [14]. Each symbol
under these aforementioned categories contains more pilot symbols on the frequently distributed
subcarriers. From the literature, it is inferred that the Comb-type pilot arrangements are better
than block-type pilot arrangements. MMSE methods surpass LS algorithms in most cases, and
they're more complicated [15].
Deep learning has gained a wide range of popularity due to its merit and the deep neural network
embedded wireless communication system acts as a black box for the transmission and reception
of the signal. Limited experimental and numerical results alone exist to justify the contribution of
DL in studying major wireless system functional components methods seem to lack evident
analytical sources to examine their advantages as well as limitations. A necessity arises to
analyze the excellent performance of numerous tasks that are performed by DL method in order
to still enhance its performance as well as to incorporate it for various scenarios. It is important to
have complete cognizance about the limitations of DL in terms of wireless communication
networks to have a better cognizance of suitable scenarios that are apt for DL-enabled
communication systems. One of the prime concerns to be taken into consideration is the ability of
the data-driven DL method to cope with the algorithms utilized in the field of wireless
communication which are the due to outcome of human intervention. Signal and coding theories
based on theoretical and practical approach helps to address the impairments such as channel
fading, interference and noise in PHY communications. It seems to be uncertain that the black
box DL method can outperform the white box DL approach. The DL methods have widely
suppressed traditional signal processing techniques which contribute to optimum performance
even without expertise.
The Motivation of this research work is briefed as follows, it seems to be a matter of concern that
very sparse literature findings exists for earlier research that back deep neural networks (DNN)
3. International Journal of Computer Networks & Communications (IJCNC) Vol.14, No.5, September 2022
67
can outperform commonly used signal processing methods. The necessity arises to generate
sufficient theoretical findings to justify the capability of DL-based communication systems. At
present, more researches carried out suggest that DL methods are best suited for channel
estimation due to its merit and frequent deployment of neural network with wireless
communication system seem to be the recent trend which seems to be efficient though. Recent
successful researches have proven DLL as an effective technique corresponding to channel
estimation. This seems to be a major boost to rely upon and employ DL methods in order to
perform effective channel estimation.
The following observations are considered to perform the pilot-based channel estimation by
employing artificial intelligence.
The wireless communication model with appropriate hybrid beamforming employs the PSO-
LSTMEstNet to achieve effective channel estimation (CE). Particle swarm optimization tunes the
pilot impulses of the network, as opposed to a standard optimizer with a a specific learning rate.
A multi-antenna downstream device is utilized in MIMO-NOMA mm-Wave broadcast
architecture.
This paper is presented as follows: Section 2, illustrates the literature for optimization and neural
network-based channel estimation with its limitations. Section 3 briefs the proposed PSO-
LSTMEstNet model for efficient channel estimation. The empirical study is provided through
figure representations in section 4. Finally, section 5 concludes the work by providing suitable
concluding remarks.
2. RELATED WORKS
This research concentrates on improving the spectral efficiency of the mm-Wave MIMO–NOMA
channel using a novel optimization technique hybrid beamforming scheme. The existing
literature associated with the mm-Wave optimization method and artificial intelligence-based
channel estimation methods were explained.
In comparison to traditional CE algorithms, the researchers in [16] presented a deep learning
(DL) framework to enhance CE effectiveness and decrease computational costs. The researchers
designed a convolutional neural network for MIMO (CNN-MIMO) that takes an incomplete
channel matrix as input. The drawback is that it does not affect on either diversity increase or
computation cost. The researchers designed a convolutional neural network for MIMO (CNN-
MIMO) that considers an incomplete channel matrix as input. The drawback is that it has no
effect on either diversity or computation cost. In [17], a generative adversarial network (GAN) is
built for low-dimensional space using optimal digital and analog precoders. Through
conceptualizing multimodal spatial multiplexing like a trans optical solution and instead
arranging subsequent loop as a nodule, the investigators were keen to minimize search
complexity. As a consequence, a unique model-based DNN with domain expertise is created. The
major constraint is that, when the number of mobile terminals to BS antennae ratio is near to each
other, it exhibits over CE performance. In [18], a Convolutional Deep Stacking Network (CDSN)
is employed to remove the knowledge about the coherence, a rigorous method was provided to
rebuild the scarce impulses first from measuring matrices. A deep fully connected neural network
was employed in [19]. From the observations, it is inferred that such model is more effective
than typical CS modeling techniques. A new LSTM system was proposed in [20], for solving an
optimal control problem, and it justifies that the provided process surpasses standard dense
overhaul techniques used for the investigation on actual statistics. The backpropagation (BP)
approach was presented in [21] for constructing a multicellular feedforward neural network. A
deep learning-based approach enabling intuitive channel quality can be estimated & rapid
4. International Journal of Computer Networks & Communications (IJCNC) Vol.14, No.5, September 2022
68
retrieval of broadcast signals were presented in [22]. The authors recommend an approximation
message transmission structure for MIMO devices in [23]. This approach dramatically enhances
the effectiveness of restoration as well as the reduction trade-off by instantly taking cognizance
of spatial information immediately by merging sample covariance in MIMO carriers.
Table-1 comparison between various existing methods
Author Method accuracy BER
Balevi et al. [16] convolutional neural
network
94.3% 32dB
Chen et al., [17] generative
adversarial network
(GAN)
87.3% -0.458
Palangi et al., [18] Convolutional Deep
Stacking Network
(CDSN)
91.4% -123
Mousavi et al., [19] deep fully-connected
neural network
90.3% 15 dB, 20 dB, 25
dB, and 30 db;
MSE=10-5
Rajendran et al.,
[20]
LSTM 87.2% -0.432
Taspinar et al., [21] multicellular
feedforward neural
network
90% 15 dB, BER=0.5
Ye et al., [22] approximation
message
transmission
structure
88.5% 15 dB, 20 dB, 25
dB, and 30 db;
BER=10-2
He et al., [23] spatial information 84.5% 15 dB, 20 dB, 25
dB, and 30 db;
MSE=10-3
The fundamental issue of hybrid detection in MIMO is to develop an equipment stage with low
volatility, perceived control, outstanding performance, and maximum throughput. At present,
very few methods are analyzed which can combat the issue with its own limitations
corresponding to complexity and real time execution. ML identification is regarded as the best
technique to combat BER through exhaustive search irrespective of its complexity which is
exponentially larger than the number of transmission and reception radio lines. Direct
approximations such as, zero-forcing (ZF) as well as MMSE, on the other hand, have a lesser
intricacy but a large execution tragedy. The utilization of mm Wave in wireless communication
systems facilitates the need for interconnectivity. Most of the researches carried out suggest an
unrealistic approach to employ multiple users with a requirement of single antenna per user. In
order to design channel estimation algorithms, the multiple access technique that is employed
must be taken into account. Therefore, additional work must be devoted to the pilot
contamination challenge that has the potential to restrict the number of scheduled users while
degrading channel forecast accuracy.
3. SYSTEM MODEL
The input data is first passed to a converter block, which converts serial data to parallel data. The
data is then passed via a 64-QAM block, which uses a single radio wave to indicate six bits of
5. International Journal of Computer Networks & Communications (IJCNC) Vol.14, No.5, September 2022
69
data by altering parallel data, where K symbols form a modulated data block [24]. A MIMO
encoder/decoder block is shown, with a prefix included to counteracting multipath fading. The
modulator is linked to the sub carrier block, which comprises of numerous pilot blocks. The
Particle swarm optimization approach is used to identify the best pilot. The input for PSO is set
of pilot signals coming from a 64-QAM modulators [25]. The optimal pilot signals are given to
the LSTM network for efficient channel estimation as shown in figure-2. The optimal pilot
signals can be denoted as {opt(pi1),opt(pi2),…..opt(pin)} which is the input for LSTM.
Figure-2 Particle swarm optimised LSTM channel estimator network block diagram (PSO-LSTMEstNet)
3.1. Pilot signals arrangement with sparsity in MIMO-NOMA
Data transmission results from a base station (BS) on M transmitters that use MIMO systems to
broadcast the input messages, with each radio transmitter's duration being N cycles, within W(0 <
W < K) which W(0 < W < K) signals and the channel width L have been selected as the data
transmission pilot. The i the transmission directional antennas pilot design pio_(k), k = 1, 2, ...,
N, where pio(k)∩pio(l) = ∅, If k ≤ l.
The impact of channel estimation by utilising the fragmented properties of the channels and
minimal pilot symbols, thus improves bandwidth consumption.
(1)
As a result, researchers evaluate the sparsity first and then choose those components that fall
inside that region. Because the amplification factors of the network tapping were larger than just
the background signal at greater signal-to-noise ratios, the recovered scalar components were
organized on highest to the lowest. The disparity between entities that interact is being used to
measure the number of components chosen for such repetition as well as to approximate the
sparseness progressively. Since they may contain data signal, the items preceding the highest
divergence were chosen for such an extended version.
3.2. Optimal pilot design using Particle Swarm optimization method
Training symbols are sent to aid pilot-aided channel estimation (PACE). The transmit vector
can be expressed as when stacked in a matrix. To ensure a full rank, a
minimum of training symbols must be conveyed. The training matrix is made up of orthogonal
sequences that have been subjected to where μ is the signal strength assigned to the
training matrix. Since the optimization problem (P1) is non-convex, traditional convex
optimization methods cannot be applied. Therefore, in this paper, we leverage the IPSO
mechanism to solve it.
6. International Journal of Computer Networks & Communications (IJCNC) Vol.14, No.5, September 2022
70
Lets start by periodically making a series of i.e., , i=1,2,....K, where another
component indicates an approximate solutions in (P1) while K is the predetermined overall
density = . The metaheuristic optimization adjusts the component
placement pbesti and the optimal solutions resolution gbest fitness evaluation value. In the tth
repetition, the trajectories of components are changed as follows:
(2)
(3)
where and indicates the particle's position and speed. in the (t − 1)-th iteration. w
is the weight vector, which would be employed to keep the particle's movement reluctance
constant since it can increase the subspace. In generally, the parameter is dynamically modified
within every know prior on the optimisation findings. The training parameters c1 and c2 refer to
the quantum state stride length as it moves more toward the ideal place. When [0,1], r1 & r2 are
equally dispersed. Each variable is floating number, fitness widow is
determined using fitness function in widow so,
(4)
The widow denotes the portion of data received across the channel, while denotes the total
number of pilots assigned to the channel, the are used to tally the overall
number of channels. The optimization technique begins with the size candidate
widow matrix generated by the spider's first population. The parents are chosen at random to
carry out the procreation process through mating.
Procreate- This step reproduces the array with alpha named as widow array of random
numbers, that contains the offspring as shown in the equation where and denotes
parents and the offspring refers by and
(5)
(6)
The process is repeated for times, in randomly manner.
Cannibalism- The first sort of cannibalism in the algorithm is sexual cannibalism, in
which a black widow spider eats her spouse during mating. The fitness values of women
and males are used to identify them in this method. The second type of cannibalism is
sibling cannibalism, in which stronger particles eat their weaker siblings. This method
establishes a cannibalism rating depending on the number of survivors and uses the
fitness value to determine if the spider hatchlings are robust or feeble.
Mutation- At this point, choose an arbitrary number of individuals to represent the
mutation population. At the array, each of the chosen solutions replaces approximately
two elements.
Convergence- Three stopping conditions are assumed, as with every evolutionary
algorithm: Predetermined repetitions (A). (B) The Observation that the fitness value of
the better widow employed for varied repeats does not change. (C) Attain a specified
level of precision.
7. International Journal of Computer Networks & Communications (IJCNC) Vol.14, No.5, September 2022
71
Parameter setting- Procreation Rate (PR), Cannibalism Rate (CR), and Mutation Rate
(MR) are the variables specified in the PSO algorithm. To improve the algorithm's
performance and achieve greater results, parameters must be altered appropriately.
3.3. LSTM network-based channel estimation
Pilot pattern is the foundation for further examination in pilot-aided channel estimate algorithms
for OFDM systems. The block pilot pattern effectively overcomes frequency-selective fading by
inserting pilot symbols into all subcarriers in an OFDM signal,
Step-1 Initialize the weights (w) and bias (b)
Epochs (E) ,
Step-2 Update the training sets-
Step-3 Include the pilot signals-
Repeat the above steps-1 to step-3
Step-4 Calculate the output layer
Step-5 Compute the cost function
E=
Step-6 compute the partial derivation for weight and bias
Until reach iteration =I(c)
Return the training samples calculation
If
Step-7 I(c)> Else
Step-8 Restart the training process
endif
3.3.1. Structure of LSTM network
A MIMO wireless communication system has been considered. The signal that is delivered at the
receiver's end is written as,
While n represents AWGN, H is the network error signal, and x represents the incoming signal.
The encoder, hidden units, and output vector make up the LSTM network model. The input is
accepted by the encoder. The LSTM cells make up the buried layer. The predictive performance
are shown in the output layer. Input, forget, and output gates are all present
The control signal determines when fresh data may be recorded in the current block as well as
keeps undesired data out of the main memory. The update gate ft checks its prior state has
been forgotten (i-1). After that the memory is updated (i.e) to the forget gate and the input gate
function together. The resultant gate determines what data will be sent out. The information of
these gates in an LSTM network matches the equations beneath.
(7)
8. International Journal of Computer Networks & Communications (IJCNC) Vol.14, No.5, September 2022
72
(8)
(9)
(10)
Where , , , denotes the weights matrices for the previous short-term state . ,
, , are the weight matrices in the current input state , and , , , and are the
bias terms. The current long-term state of the network can be calculated as
(11)
And the output y of the network is
(12)
Upon that output side, a converter is required to transform the codeword containing the received
signal onto concurrent data feeds. The Inverse Fourier Transform will then be used to transfer the
waveform into the time-frequency domain. A coding scheme must be used to lessen the effects of
cross-functional and cross-interference. The width of the CP should be bigger than just the
maximum propagation latency of the stream. It is designated the spread spectrum network of a
sampling region bounded by sophisticated randomized variables . Following that,
the impulse response can indeed be analyzed as follows:
(13)
wherein seems to be the control input, convolution is cyclic, and
seems to be the integral gain. Inside the fourier transform, the impulse response could be
described:
(14)
where, the FFT of , , and are , and , respectively.
The output ( of LSTM network can be expressed as
(15)
Whereas represents the LSTM channel's downstream hidden column during schedule t-1,
whereas represents the LSTM channel's backwards inputs at prime time t. & LSTM(•)
signify together all parameters and transformations functions of the LSTM network,
correspondingly.
The initial stage in LSTM-based predictions would be to calculate the carrier for such currently
obtained OFDM signal employing originally expected performance indicators, with the i-th
Memory system supply marked as .
This early phase in LSTM-based forecasting is to guess the network again for present receiving
OFDM signal employing originally expected performance indicators, with the i-th LSTM unit
output marked by .
9. International Journal of Computer Networks & Communications (IJCNC) Vol.14, No.5, September 2022
73
(16)
is generated by converting a complex value to a real value and stacking the
real and imaginary values in a single vector. After that, using the ith
received OFDM signal, pilot
aided estimation is performed in the LSTM estimated channel. To get the optimum performance,
the suggested LSTM training is carried out with SNR = 40 dB. This is because when the training
is carried out with a high SNR value, the LSTM is capable of learning the channel statistics better
and has a good generalization capacity.
3.3.2. Construction of PSO-LSTMEstNet
The number of OFDM symbols is used as the time sequence number since the LSTM network
requires symbols as input. The data is sent into a 1D CNN network after pre-processing, and
feature vectors are retrieved using 1D-CNN. Because the continuous response is directly
estimated in time-domain channel estimation, when contrasted to modifications that occur
estimate, the source data does have an additional latency element. Channels estimate in the
frequency response is not the same as fading channels in the temporal domain, the variables to be
estimated are compressed using a 1D Maxpooling layer. The information is moved to the LSTM
model post background subtraction & attribute dimensionality minimization, as well as the
optimized pilot information, is delivered right to the LSTM model like illustrated in figure 3.
The carrier configuration information matrix is used as training dataset to the training stage
throughout this study. The CSI matrices are represented by as time-frequency fading
channels as well as as as transfer function data transmission. Least Squares (LS) is
used to compute the CSI at precoding, whereas the CSI at information bits is set to 0. As a result,
for bandwidth fading channels and for time and frequency domains
channel model can be used as the output to the training stage. The LSTM unit requires a temporal
relationship, result, the CSI is represented as such and turned into a series.
Figure 3. Architecture of PSO-LSTMEstNet
(17)
10. International Journal of Computer Networks & Communications (IJCNC) Vol.14, No.5, September 2022
74
where denotes the CSI at the OFDM symbol. Because multichannel data
collected is a complicated waveform, it must be pre-processed before ever being fed into the
knowledge construction structure. The received information is transformed by distinguishing the
complex numbers and
The incoming data is pre-processed before being sent to CNN for extraction of the frequencies
feature space. The main purpose of CNN is to extract then select a periodic feature
representation. To retrieve the feature representation, the Deep network uses filters to perform a
linear transformation on G'. As once evaluation is complete by the Deep cnn, the calculated
results remain unchanged, and it is presented as .The output dimensions of the
CNN will be decreased by the Maxplooing network for time-domain channel estimation. When
the Maxpooling network's pooling window size is set to as the data dimension after
pooling becomes
Channel estimation- Based on historical and current input as well as future data, the proposed
PSO-LSTMEstNet learning network seeks to anticipate the current CSI. Because the LSTM
network excels at learning sequence data, it is employed to predict the current CSI in this study.
The CSI at the later instant is anticipated by the CSI at the prior moment in forwarding
prediction. The CSI at the prior time is anticipated by the CSI at the later moment in the
backward prediction, and the forward and backward pilot information is completely utilized to
increase the accuracy of the channel estimation. Each time step of the LSTM network includes an
output for channel estimation. In order to train the PSO-LSTMEstNet, we use the end-to-end
approach to obtain all the weights and biases in the PSO-LSTMEstNet. We use Particle Swarm
Optimization (PSO) algorithm to update the set of pilot design parameters for the PSO-
LSTMEstNet network. This algorithm is different from the traditional optimization algorithm
with fixed learning rate. Through training, can to adaptively update the learning rate.
3.4. Algorithm- PSO-LSTMEstNet
Step-1 Initialize the weights (w) and bias (b)
Epochs (E) ,
Step-2 Update the training sets-
Step-3 Include the pilot signals-
Repeat the above steps-1 to step-3
Step-4 Calculate the output layer
Step-5 Compute the cost function
E=
Step-6 compute the partial derivation for weight and bias
Until reach iteration =I(c)
Return the training samples calculation
If
Step-7 I(c)> Else
Step-8 Restart the training process
endif
11. International Journal of Computer Networks & Communications (IJCNC) Vol.14, No.5, September 2022
75
4. EXPERIMENTAL ANALYSIS
The experimental analysis were carried out using MATLAB software and the parameters used for
analysis are Bit Error Rate (BER), Computational time, Signal to Noise Ratio (SNR) Symbol
Error Rate (SER). Three common techniques—the Convolutional Deep Stacking Network
(CDSN), the Multi-layered Perceptron (MLP) neural network, and the Generative Adversarial
Network—are used to compare the results obtained for these factors (GAN). The simulation
parameter for channel estimation is displayed in Table 1.
Table 2. Simulation parameters
Parameters Values
The overall amount of sub -
carriers
1543
Type of modulation BPSK, QPSK, 16-QAM, 64-QAM
Pilot inserting sort Convolution
Intermittent sort of guard Cyclic prefix
Guard frequency duration 432
Noise form White Gaussian noise
Signal to Noise Ratio (SNR)
The signal-to-noise ratio (SNR) is frequently given in dB, and is characterized as the proportion
of transmit strength to signal strength. A signal-to-noise proportion larger than 1:1 (more than 0
dB) shows there's more transmission over interference.
Figure 4. Analysis of Signal to Noise Ratio (SNR)
Figure 4, represents the analysis of Signal to Noise Ratio (SNR) between PSO-LSTMEstNet and
various corresponding neural networks. In this analysis, the comparison is performed concerning
different modulation schemes to perfectly examine the effectiveness of SNR with corresponding
BER. The modulation technique 64 QAM employed here is taken as the reference for comparing
SNR for the specified neural networks. The simulated findings, incur that on an average of 10dB
of BER, SNR of 10-2
is achieved by the suggested PSO-LSTMEstNet. From the analysis, it is
evident that the suggested model is more efficient than the rest of the neural network models.
12. International Journal of Computer Networks & Communications (IJCNC) Vol.14, No.5, September 2022
76
Figure 5. Analysis of Bit Error Rate (BER)
The comparative analysis of bit error rate, between suggested PSO-LSTMEstNet and various
networks such as Convolutional Deep Stacking Network (CDSN), Multi-layered perceptron
(MLP) neural network, Generative Adversarial Network (GAN) is performed. The various
modulation techniques along with their corresponding SNR is taken into consideration for
analysis. In order to observe the outcome of simulated findings, 64 QAM is fixed as a reference
index. On an average, it is observed that BER of 10-2
is obtained at 10db.The above findings
ensure that the suggested network is efficient.
Time complexity is a type of computational effort that specifies how the amount of time is
required by a system to a execute particular operation. Table 4 depicts the comparison of
computational time between proposed PSO-LSTMEstNet and existing Convolutional Deep
Stacking Network (CDSN), Multi-layered perceptron (MLP) neural network, Generative
Adversarial Network (GAN).
Table 4. Comparison of computational time
Modulation
techniques
CDSN MLP GAN PSO-LSTMEstNet
BPSK 53 52 49 45
QPSK 61 58 55 52
16-QAM 67 63 59 55
64-QAM 72 69 65 61
13. International Journal of Computer Networks & Communications (IJCNC) Vol.14, No.5, September 2022
77
`
Figure 6. Analysis of computational time
The analysis of computational time between PSO-LSTMEstNet and various networks such as
Convolutional Deep Stacking Network (CDSN), Multi-layered perceptron (MLP) neural network,
and Generative Adversarial Network (GAN) is depicted in figure 6. Various modulation schemes
are taken into consideration for comparison that includes BPSK, QPSK, 16-QAM and 64-QAM.
From the observation based on simulated findings, the computational time of PSO-LSTMEstNet
is found to be minimal, the rest of the networks that were subjected to comparison. Thus, with
reduced computational time which is a major feature, the PSO-LSTMEstNet is proved to be
efficient.
Figure 7. Comparison between SNR vs BER
Gathering information through wireless transmission is not a major challenge. The prime concern
is whether the proposed method is capable of predicting mm Wave channel as well as received
signal. .With the current massive developments in the field of deep learning that comprises of
efficient techniques such a Bayesian neural networks, deep convolutional neural networks and
recurrent neural networks which seem to be promising and is widely employed due its
exceptional performance.
14. International Journal of Computer Networks & Communications (IJCNC) Vol.14, No.5, September 2022
78
5. CONCLUSION
In this paper, The PSO-LSTMEstNet model is proposed to enhance the spectral efficiency of the
MIMO- NOMA for mm-Wave applications. The model enhances performance by combining a
deep learning technique with an optimization strategy to improve system performance. The
optimization method paved the way for LSTMEstNet approach in the mm-Wave channel system
and hybrid beam formation with large-scale antennas. The LSTM model is employed where the
channel conditions vary frequently at different stages, particularly in the training stage. For
enhanced spectral efficiency and reduced hardware complexity, hybrid beamforming approaches
are employed. From the simulated findings, the outcome of comparative analysis signifies that
PSO-LSTMEstNet exhibits enhanced performance with corresponding parameters such as SNR,
BER and computational time. The computational time is observed to be minimal which terms the
network to be efficient.
ACKNOWLEDGMENTS
The Department of Electronics and Communication Engineering at Puducherry Technological
University in Puducherry, India, has supported the authors' work in this area.
CONFLICTS OF INTEREST
The authors declare no conflict of interest.
REFERENCES
[1] M. Xiao, S. Mumtaz, Y. Huang, L. Dai, Y. Li, M. Mattaiou, G. K. Karagiannidis, E. Bjornson, K.
Yang, C. I, and A. Ghosh, “Millimeter Wave Communications for Future Mobile Networks,” IEEE J.
Sel. Areas Commun., vol. 35, no. 9, pp. 1909–1935, Sep. 2017.
[2] N.Veeraiah and B.Tirumala Krishna “Trust-aware Fuzzy Clus-Fuzzy NB: intrusion detection scheme
based on fuzzy clustering and Bayesian rule,,” Wireless Networks, vol.25, no.07, pp.4021–
4035,2019.
[3] L. Wei, R. Q. Hu, Y. Qian, and G. Wu, “Key elements to enable millimeter wave communications for
5G wireless systems,” IEEE Wireless Commun., vol. 21, no. 6, pp. 136–143, Dec. 2014.
[4] S. Han, C. L. I, Z. Xu, and C. Rowell, “Large-scale antenna systems with hybrid precodinganalog and
digital beamforming for millimeter wave 5G,” IEEE Commun. Mag., vol. 53, no. 1, pp. 186–194,
Jan. 2015.
[5] S Jin, X Liang, KK Wong, X Gao, and Q Zhu,“Ergodic rate analysis for multipair massive MIMO
two-way relay networks,” IEEE Trans. Wireless Commun., vol. 14, no. 3, pp. 1480–1491, Mar. 2015.
[6] L Fan, S Jin, CK Wen, and H Zhang, “Uplink achievable rate for massive MIMO systems with low-
resolution ADC,” IEEE Commun. Lett., vol. 19, no. 12, pp. 2186–2189, Oct. 2015.
[7] S Jin, X Wang, Z Li, KK Wong, Y Huang, and X Tang, “On massive MIMO zero-forcing transceiver
using time-shifted pilots,” IEEE Trans. Veh. Technol., vol. 65, no. 1, pp. 59–74, Jan. 2016.
[8] Neenavath Veeraiah and B. Tirumala Krishna “Intrusion Detection Based on Piecewise Fuzzy C-
Means Clustering and Fuzzy Naïve Bayes Rule,” Resbee Publishers Multimedia Research (MR),
vol.01, no.01,pp.27-32,2018.
[9] R. Cao, B. Liu, F. Gao, and X. Zhang, “A low-complex one-snapshot DOA estimation algorithm with
massive ULA,” IEEE commun. Lett. vol. 21, no. 5, pp. 1071–1074, Jan. 2017
[10] Ye, H.; Li, G.Y.; Juang, B.H. Power of Deep Learning for Channel Estimation and Signal Detection
in OFDM Systems. IEEE Wirel. Commun
[11] Wang, C. Research and Application of Traffic Sign Detection and Recognition Based on Deep
Learning. In Proceedings of the International Conference on Robots & Intelligent System
(ICRIS2018), Amsterdam, The Netherlands, 21–23 February 2018.
[12] S. Sobhi-Givi, M. G. Shayesteh, and H. Kalbkhani, “Energy-Efficient Power Allocation and User
Selection for mmWave-NOMA Transmission in M2M Communications Underlaying Cellular
15. International Journal of Computer Networks & Communications (IJCNC) Vol.14, No.5, September 2022
79
Heterogeneous Networks,” IEEE Transactions on Vehicular Technology, vol. 69, no. 9, pp. 9866–
9881, 2020.
[13] K. Belbase, C. Tellambura, and H. Jiang, “Coverage analysis of cooperative NOMA in millimeter
wave networks,” IEEE Communications Letters, vol. 23, no. 12, pp. 2154–2158, 2019.
[14] N. Veeraiah and B. T. Krishna, "Selfish node detection IDSM based approach using individual master
cluster node," 2018 2nd International Conference on Inventive Systems and Control (ICISC), 2018,
pp. 427-431.
[15] Elbir, A. M., &Papazafeiropoulos, A. K. (2019). Hybrid precoding for multiuser millimeter wave
massive MIMO systems: A deep learning approach. IEEE Transactions on Vehicular Technology,
69(1), 552-563.
[16] Balevi, E., & Andrews, J. G. (2021),”Unfolded Hybrid BeamformingWith GAN Compressed Ultra-
Low Feedback Overhead”, IEEE Transactions on Wireless Communications, 20(12), 8381-8392.
[17] Chen, S., Ng, S. X., Khalaf, E., Morfeq, A., &Alotaibi, N. (2021). Particle swarm optimization
assisted B-spline neural network based predistorter design to enable transmit precoding for nonlinear
MIMO downlink. Neurocomputing, 458, 336-348.
[18] Palangi, Hamid, Rabab Ward, and Li Deng, "Convolutional deep stacking networks for distributed
compressive sensing", Signal Processing 131 (2017): 181-189.
[19] Mousavi, Ali, Gautam Dasarathy, and Richard G. Baraniuk. "Deepcodec: Adaptive sensing and
recovery via deep convolutional neural networks." arXiv preprint arXiv: 1707.03386 (2017).
[20] Rajendran, W. Meert, D. Giustiniano, V. Lenders, and S. Pollin, “Deep learning models for wireless
signal classification with distributed lowcost spectrum sensors,” IEEE Trans. Cognitive Commun.
and Networking, vol. 4, no. 3, pp. 433-445,Sept. 2018.
[21] N. Taspinar and M. N. Seyman, “Back propagation neural network approach for channel estimation
in OFDM system”, in Proc. Wireless Commun., Netw. Inf. Security (WCNIS), June 2010, pp. 265–
268.
[22] H. Ye, G. Y. Li, and B.-H. Juang, “Power of deep learning for channel estimation and signal
detection in OFDM systems,” IEEE Wireless Commun. Lett., vol. 7, pp. 114–117, Feb. 2018.
[23] H. He, C. Wen, S. Jin, and G. Y. Li, “Deep learning-based channel estimation for beamspace
mmWave massive MIMO systems,” IEEE Wireless Commun. Lett., vol. 7, pp. 852–855, Oct. 2018.
[24] T. Wang, C. Wen, S. Jin, and G. Y. Li, “Deep learning-based CSI feedback approach for time-
varying massive MIMO channels,” IEEE Wireless Commun. Lett., vol. 8, pp. 416–419, Apr. 2019.
[25] N.Veeraiah and B.T.Krishna “An approach for optimal-secure multi-path routing and intrusion
detection in MANET,” Evolutionary Intelligence, vol.15, pp.1313–1327, 2022.