In this paper, we investigate the joint cooperative spectrum sensing and access design problem for multi-channel cognitive radio networks. A general heterogeneous setting is considered where the probabilities that different channels are available, SNRs of the signals received at secondary users (SUs) due to transmissions from primary users (PUs) for different users and channels can be different. We assume a cooperative sensing strategy with a general a-out-of-b aggregation rule and design a synchronized MAC protocol so that SUs can exploit available channels. We analyze the sensing performance and the throughput achieved by the joint sensing and access design. Based on this analysis, we develop algorithms to find optimal parameters for the sensing and access protocols and to determine channel assignment for SUs to maximize the system throughput. Finally, numerical results are presented to verify the effectiveness of our design and demonstrate the relative performance of our proposed algorithms and the optimal ones.
Tech report: Fair Channel Allocation and Access Design for Cognitive Ad Hoc N...Polytechnique Montreal
supplement to Globecom paper: L. T. Tan and L. B. Le, ``Fair Channel Allocation and Access Design for Cognitive Ad Hoc Networks,'' in 2012 IEEE Global Communications Conference (IEEE GLOBECOM 2012), Anaheim, California, USA, pp. 1162-1167, December, 2012.
This document summarizes a research paper on fair channel allocation in cognitive radio ad hoc networks. It discusses:
1) A channel allocation problem where each node is assigned a subset of channels to access periodically using a MAC protocol, with the goal of maximizing fair sharing of spectrum among network flows.
2) An optimal brute-force search algorithm for solving this NP-hard problem and its exponential complexity.
3) The development of low-complexity channel allocation algorithms and an analytical throughput model to evaluate performance.
Fair channel allocation and access design for cognitive ad hoc networksPolytechnique Montreal
The document discusses fair channel allocation and access design for cognitive radio ad hoc networks. It considers a scenario where network nodes can access at most one channel at a time. It analyzes the complexity of the optimal brute-force search algorithm for this NP-hard channel allocation problem. It then develops low-complexity algorithms and a throughput model to analyze their performance in achieving fair spectrum sharing. Specifically, it proposes a non-overlapping channel assignment algorithm and an overlapping channel assignment algorithm combined with a MAC protocol to resolve channel access contention.
Channel Assignment With Access Contention Resolution for Cognitive Radio Netw...Polytechnique Montreal
In this paper, we consider the channel assignment problem for cognitive radio networks with hardware-constrained secondary users (SUs). In particular, we assume that SUs exploit spectrum holes on a set of channels where each SU can use at most one available channel for communication. We present the optimal brute-force search algorithm to solve the corresponding nonlinear integer optimization problem and analyze its complexity. Because the optimal solution has exponential complexity with the numbers of channels and SUs, we develop two low-complexity channel assignment algorithms that can efficiently utilize the spectrum holes. In the first algorithm, SUs are assigned distinct sets of channels. We show that this algorithm achieves the maximum throughput limit if the number of channels is sufficiently large. In addition, we propose an overlapping channel assignment algorithm that can improve the throughput performance compared with its nonoverlapping channel assignment counterpart. Moreover, we design a distributed medium access control (MAC) protocol for access contention resolution and integrate it into the overlapping channel assignment algorithm. We then analyze the saturation throughput and the complexity of the proposed channel assignment algorithms. We also present several potential extensions, including the development of greedy channel assignment algorithms under the max-min fairness criterion and throughput analysis, considering sensing errors. Finally, numerical results are presented to validate the developed theoretical results and illustrate the performance gains due to the proposed channel assignment algorithms.
Joint Cooperative Spectrum Sensing and MAC Protocol Design for Multi-channel ...Polytechnique Montreal
In this paper, we propose a semi-distributed cooperative spectrum sen
sing (SDCSS) and channel access framework
for multi-channel cognitive radio networks (CRNs). In particular, we c
onsider a SDCSS scheme where secondary
users (SUs) perform sensing and exchange sensing outcomes with ea
ch other to locate spectrum holes. In addition,
we devise the
p
-persistent CSMA-based cognitive MAC protocol integrating the SDCSS to
enable efficient spectrum
sharing among SUs. We then perform throughput analysis and develop
an algorithm to determine the spectrum
sensing and access parameters to maximize the throughput for a given
allocation of channel sensing sets. Moreover,
we consider the spectrum sensing set optimization problem for SUs to maxim
ize the overall system throughput. We
present both exhaustive search and low-complexity greedy algorithms
to determine the sensing sets for SUs and
analyze their complexity. We also show how our design and analysis can be
extended to consider reporting errors.
Finally, extensive numerical results are presented to demonstrate the sig
nificant performance gain of our optimized
design framework with respect to non-optimized designs as well as the imp
acts of different protocol parameters on
the throughput performance.
The document summarizes the research scope and contributions of the author's PhD dissertation on medium access control (MAC) protocols for cognitive radio networks (CRNs). It discusses four past research areas: (1) CMAC protocol design with parallel spectrum sensing, (2) CMAC protocol with sequential sensing, (3) CMAC protocol with cooperative sensing, and (4) asynchronous full-duplex CMAC protocol. It also outlines three potential future research directions: (1) multi-channel MAC protocol design for full-duplex CRNs, (2) cross-layer CMAC and routing design for multi-hop CRNs, and (3) joint cognitive protocol and data processing design for smart grid applications.
In this paper, we consider the joint optimal sensing
and distributed MAC protocol design for cognitive radio
networks. Specifically, we design a synchronized MAC protocol
for dynamic spectrum sharing among multiple secondary
users, which incorporates spectrum sensing for protecting active
primary users. We perform saturation throughput analysis for
the proposed MAC protocol that explicitly captures spectrum
sensing performance. Then, we find its optimal configuration
by formulating a throughput maximization problem subject to
detection probability constraints for primary users. In particular,
the optimal solution of this optimization problem returns the
required sensing time for primary users’ protection and optimal
contention window for maximizing total throughput of the
secondary network. Finally, numerical results are presented to
illustrate a significant performance gain of the optimal sensing
and protocol configuration.
A COMPARATIVE PERFORMANCE STUDY OF OFDM SYSTEM WITH THE IMPLEMENTATION OF COM...ijcsa
This paper presents a comparative performance analysis of wireless orthogonal frequency division multiplexing (OFDM) system with the implementation of comb type pilot-based channel estimation algorithm over frequency selective multi-path fading channels. The Minimum Mean Square Error (MMSE) method is used for the estimation of channel at pilot frequencies. For the estimation of channel at data frequencies different interpolation techniques such as low-pass, linear, and second order interpolation are employed. The OFDM system simulation has been carried out with Matlab and the performance is analyzed in terms of bit error rate (BER) for various signal mapping (BPSK, QPSK, 4QAM, 16QAM, and 64QAM) and channel (Rayleigh and Rician) conditions. The impact of selecting number of channel taps on the BER performance is also investigated.
Tech report: Fair Channel Allocation and Access Design for Cognitive Ad Hoc N...Polytechnique Montreal
supplement to Globecom paper: L. T. Tan and L. B. Le, ``Fair Channel Allocation and Access Design for Cognitive Ad Hoc Networks,'' in 2012 IEEE Global Communications Conference (IEEE GLOBECOM 2012), Anaheim, California, USA, pp. 1162-1167, December, 2012.
This document summarizes a research paper on fair channel allocation in cognitive radio ad hoc networks. It discusses:
1) A channel allocation problem where each node is assigned a subset of channels to access periodically using a MAC protocol, with the goal of maximizing fair sharing of spectrum among network flows.
2) An optimal brute-force search algorithm for solving this NP-hard problem and its exponential complexity.
3) The development of low-complexity channel allocation algorithms and an analytical throughput model to evaluate performance.
Fair channel allocation and access design for cognitive ad hoc networksPolytechnique Montreal
The document discusses fair channel allocation and access design for cognitive radio ad hoc networks. It considers a scenario where network nodes can access at most one channel at a time. It analyzes the complexity of the optimal brute-force search algorithm for this NP-hard channel allocation problem. It then develops low-complexity algorithms and a throughput model to analyze their performance in achieving fair spectrum sharing. Specifically, it proposes a non-overlapping channel assignment algorithm and an overlapping channel assignment algorithm combined with a MAC protocol to resolve channel access contention.
Channel Assignment With Access Contention Resolution for Cognitive Radio Netw...Polytechnique Montreal
In this paper, we consider the channel assignment problem for cognitive radio networks with hardware-constrained secondary users (SUs). In particular, we assume that SUs exploit spectrum holes on a set of channels where each SU can use at most one available channel for communication. We present the optimal brute-force search algorithm to solve the corresponding nonlinear integer optimization problem and analyze its complexity. Because the optimal solution has exponential complexity with the numbers of channels and SUs, we develop two low-complexity channel assignment algorithms that can efficiently utilize the spectrum holes. In the first algorithm, SUs are assigned distinct sets of channels. We show that this algorithm achieves the maximum throughput limit if the number of channels is sufficiently large. In addition, we propose an overlapping channel assignment algorithm that can improve the throughput performance compared with its nonoverlapping channel assignment counterpart. Moreover, we design a distributed medium access control (MAC) protocol for access contention resolution and integrate it into the overlapping channel assignment algorithm. We then analyze the saturation throughput and the complexity of the proposed channel assignment algorithms. We also present several potential extensions, including the development of greedy channel assignment algorithms under the max-min fairness criterion and throughput analysis, considering sensing errors. Finally, numerical results are presented to validate the developed theoretical results and illustrate the performance gains due to the proposed channel assignment algorithms.
Joint Cooperative Spectrum Sensing and MAC Protocol Design for Multi-channel ...Polytechnique Montreal
In this paper, we propose a semi-distributed cooperative spectrum sen
sing (SDCSS) and channel access framework
for multi-channel cognitive radio networks (CRNs). In particular, we c
onsider a SDCSS scheme where secondary
users (SUs) perform sensing and exchange sensing outcomes with ea
ch other to locate spectrum holes. In addition,
we devise the
p
-persistent CSMA-based cognitive MAC protocol integrating the SDCSS to
enable efficient spectrum
sharing among SUs. We then perform throughput analysis and develop
an algorithm to determine the spectrum
sensing and access parameters to maximize the throughput for a given
allocation of channel sensing sets. Moreover,
we consider the spectrum sensing set optimization problem for SUs to maxim
ize the overall system throughput. We
present both exhaustive search and low-complexity greedy algorithms
to determine the sensing sets for SUs and
analyze their complexity. We also show how our design and analysis can be
extended to consider reporting errors.
Finally, extensive numerical results are presented to demonstrate the sig
nificant performance gain of our optimized
design framework with respect to non-optimized designs as well as the imp
acts of different protocol parameters on
the throughput performance.
The document summarizes the research scope and contributions of the author's PhD dissertation on medium access control (MAC) protocols for cognitive radio networks (CRNs). It discusses four past research areas: (1) CMAC protocol design with parallel spectrum sensing, (2) CMAC protocol with sequential sensing, (3) CMAC protocol with cooperative sensing, and (4) asynchronous full-duplex CMAC protocol. It also outlines three potential future research directions: (1) multi-channel MAC protocol design for full-duplex CRNs, (2) cross-layer CMAC and routing design for multi-hop CRNs, and (3) joint cognitive protocol and data processing design for smart grid applications.
In this paper, we consider the joint optimal sensing
and distributed MAC protocol design for cognitive radio
networks. Specifically, we design a synchronized MAC protocol
for dynamic spectrum sharing among multiple secondary
users, which incorporates spectrum sensing for protecting active
primary users. We perform saturation throughput analysis for
the proposed MAC protocol that explicitly captures spectrum
sensing performance. Then, we find its optimal configuration
by formulating a throughput maximization problem subject to
detection probability constraints for primary users. In particular,
the optimal solution of this optimization problem returns the
required sensing time for primary users’ protection and optimal
contention window for maximizing total throughput of the
secondary network. Finally, numerical results are presented to
illustrate a significant performance gain of the optimal sensing
and protocol configuration.
A COMPARATIVE PERFORMANCE STUDY OF OFDM SYSTEM WITH THE IMPLEMENTATION OF COM...ijcsa
This paper presents a comparative performance analysis of wireless orthogonal frequency division multiplexing (OFDM) system with the implementation of comb type pilot-based channel estimation algorithm over frequency selective multi-path fading channels. The Minimum Mean Square Error (MMSE) method is used for the estimation of channel at pilot frequencies. For the estimation of channel at data frequencies different interpolation techniques such as low-pass, linear, and second order interpolation are employed. The OFDM system simulation has been carried out with Matlab and the performance is analyzed in terms of bit error rate (BER) for various signal mapping (BPSK, QPSK, 4QAM, 16QAM, and 64QAM) and channel (Rayleigh and Rician) conditions. The impact of selecting number of channel taps on the BER performance is also investigated.
The document analyzes and optimizes random sensing order in cognitive radio systems. It presents the following:
- A Markov model is used to evaluate the average throughput of secondary users and average interference between secondary and primary users under a random sensing order policy.
- An optimization problem is formulated to maximize secondary network throughput while keeping interference below a threshold.
- A distributed adaptive algorithm is developed to optimize the network performance in a non-stationary environment. It outperforms static optimization by following wireless channel variations.
- Numerical results demonstrate the algorithm achieves substantial performance gains without centralized control or message passing between users. Fully distributed optimization can efficiently utilize spectrum in cognitive radio networks.
This document proposes an improved position-based power aware routing algorithm for mobile ad-hoc networks. It introduces using a weighted metric of remaining battery power, speed, and distance of nodes to determine routes. The existing MFR (Most Forward within Radius) algorithm does not consider factors like battery power and speed differences, which can lead to unreliable communication or packet loss. The proposed algorithm uses a weighted combination of distance, velocity, and battery power metrics to select routes, aiming to balance load, increase network lifetime, and improve network performance compared to MFR. Simulation results showed the proposed algorithm reduces packet loss and increases throughput compared to MFR.
Classical Discrete-Time Fourier TransformBased Channel Estimation for MIMO-OF...IJCSEA Journal
In this document, we look at various time domain channel estimation methods with this constraint of null carriers at spectrumborders.We showin detail howto gauge the importance of the “border effect” depending on the number of null carriers, which may vary from one system to another. Thereby we assess the limit of the technique discussed when the number of null carriers is large. Finally the DFT with the truncated singular value decomposition (SVD) technique is proposed to completely eliminate the impact of the null subcarriers whatever their number. A technique for the determination of the truncation threshold for any MIMO-OFDM system is also proposed.
This document compares different wavelength assignment algorithms in WDM networks. It proposes a new Least Used Wavelength Conversion algorithm that aims to reduce blocking probability. The algorithm uses least-used wavelength assignment until blocking occurs, then introduces wavelength conversion to reduce blocking. Simulation results show the proposed algorithm has lower blocking probability than first-fit, random, most-used and best-fit algorithms. Blocking probability is evaluated under different network loads and number of wavelengths, demonstrating that blocking decreases with more wavelengths or lower loads.
Performance Analysis of Ultra Wideband Receivers for High Data Rate Wireless ...graphhoc
The document discusses performance comparisons of different receiver structures for high data rate ultra wideband communication systems. It analyzes Rake, MMSE, and Rake-MMSE receivers using MATLAB simulations on IEEE 802.15.3a channel models. The Rake-MMSE receiver combines advantages of Rake fingers and equalization to combat inter-symbol interference. Simulation results show the Rake-MMSE receiver achieves a lower bit error rate than Rake or MMSE receivers alone. The number of Rake fingers improves performance at low-medium SNR, while more equalizer taps help at high SNR.
OPTIMIZED COOPERATIVE SPECTRUM-SENSING IN CLUSTERED COGNITIVE RADIO NETWORKSijwmn
This document summarizes research on optimized cooperative spectrum sensing in clustered cognitive radio networks. The key points are:
1) Secondary users are grouped into clusters and transmit a power function of their observations to a fusion center on orthogonal channels to detect the presence of primary users.
2) The goal is to maximize the probability of detection for a given false alarm probability by optimizing the number of clusters, power function exponent, and linear combining coefficients at the fusion center.
3) Analytical expressions for the probability of detection and false alarm are derived based on the conditional mean and variance of the combined signal at the fusion center under the two hypotheses.
Channel assignment for throughput maximization in cognitive radio networks Polytechnique Montreal
In this paper, we consider the channel allocation problem for throughput maximization in cognitive radio networks with hardware-constrained secondary users. Specifically, we assume that secondary users exploit spectrum holes on a set of channels where each secondary user can use at most one available channel for communication. We develop two channel assignment algorithms that can efficiently utilize spectrum opportunities on these channels. In the first algorithm, secondary users are assigned distinct sets of channels. We show that this algorithm achieves the maximum throughput limit if the number of channels is sufficiently large. In addition, we propose an overlapping channel assignment algorithm, that can improve the throughput performance compared to the non-overlapping channel assignment algorithm. In addition, we design a distributed MAC protocol for access contention resolution and integrate the derived MAC protocol overhead into the second channel assignment algorithm. Finally, numerical results are presented to validate the theoretical results and illustrate the performance gain due to the overlapping channel assignment algorithm.
Distributed MAC Protocol for Cognitive Radio Networks: Design, Analysis, and ...Polytechnique Montreal
In this paper, we investigate the joint optimal sensing and distributed Medium Access Control (MAC) protocol design problem for cognitive radio (CR) networks. We consider both scenarios with single and multiple channels. For each scenario, we design a synchronized MAC protocol for dynamic spectrum sharing among multiple secondary users (SUs), which incorporates spectrum sensing for protecting active primary users (PUs). We perform saturation throughput analysis for the corresponding proposed MAC protocols that explicitly capture the spectrum-sensing performance. Then, we find their optimal configuration by formulating throughput maximization problems subject to detection probability constraints for PUs. In particular, the optimal solution of the optimization problem returns the required sensing time for PUs' protection and optimal contention window to maximize the total throughput of the secondary network. Finally, numerical results are presented to illustrate developed theoretical findings in this paper and significant performance gains of the optimal sensing and protocol configuration.
Iaetsd a novel scheduling algorithms for mimo based wireless networksIaetsd Iaetsd
This document proposes new scheduling algorithms for MIMO wireless networks to improve system performance. It discusses designing practical user scheduling algorithms to maximize capacity in MIMO systems. Various MAC scheduling policies are implemented and modified to provide distributed traffic control, robustness against interference, and increased efficiency of resource utilization. Simulations using MATLAB compare the different policies and draw important results and conclusions. The paper suggests new priority scheduling and partially fair scheduling algorithms incorporating awareness of interference to improve system-level performance in MIMO wireless networks.
Effective capacity in cognitive radio broadcast channelsMarwan Hammouda
Abstract—In this paper, we investigate effective capacity by
modeling a cognitive radio broadcast channel with one secondary transmitter (ST) and two secondary receivers (SRs) under quality-of-service constraints and interference power limitations.We initially describe three different ooperative channel sensing strategies with different ard-decision combining algorithms at the ST, namely OR, Majority, and AND rules. Since the channel sensing occurs with possible errors, we consider a combined
interference power constraint by which the transmission power of the secondary users (SUs) is bounded when the channel is sensed as both busy and idle. Furthermore, regarding the channel sensing decision and its correctness, there exist ...
Effect of Channel Variations on the Spectral Efficiency of Multiuser Diversit...IDES Editor
This document analyzes how the spectral efficiency of a multiuser diversity MIMO system is affected when the channel type deviates from Rayleigh fading to Nakagami-m fading. It simulates a system with different MIMO configurations and compares the average user data rates under absolute and proportional SNR scheduling schemes at 0dB, 10dB, and 20dB. The results show that user data rates decrease the most at 0dB SNR as the channel type changes from Rayleigh to Nakagami-m fading, with higher m values leading to greater losses.
Routing in All-Optical Networks Using Recursive State Space Techniquesipij
In this papr, we have minimized the effects of failures on network performace, by using suitable Routing
and Wavelenghth Assignment(RWA) method without disturbing other performance criteria such as blocking
probability(BP) and network management(NM). The computation complexity is reduced by using Kalaman
Filter(KF) techniques. The minimum reconfiguration probability routing (MRPR) algorithm must be
able to select most reliable routes and assign wavelengths to connections in a manner that utilizes the light
path(LP) established efficiently considering all possible requests.
This document proposes using multiple input multiple output (MIMO) antennas for spectrum sensing in cognitive radio to improve detection performance. It summarizes that MIMO antennas can increase the probability of detection and decrease the probability of missed detection of primary users. The document then reviews common spectrum sensing techniques and their limitations. It presents a cognitive radio algorithm that implements spectrum sensing using MIMO antennas with different antenna configurations on primary and secondary users. Simulation results show the probability of detection increases and probability of missed detection decreases with higher MIMO antenna diversity order.
Implementation of Vacate on Demand Algorithm in Various Spectrum Sensing Netw...IJERA Editor
In present days the wireless communications are widely increases because of this reason spectrum utilization can be rapidly increased.For efficient usage of spectrum we can implement the Vacate on demand algorithm in different networks. CR users also need to sense the spectrum and vacate the channel upon the detection of the PU‟s presence to protectPUs from harmful interference. To achieve these fundamental CR functions, CR users usually coordinate with each other by using a common medium for control message exchange ensuring a priority of PUs over CR users. This paper presents the Vacate on Demand (VD) algorithm which enables dynamic spectrum access and ensures to vacate the assigned channel in case of PU activity and move the CR user to some other vacant channel to make spectrum available to PUs as well as to CR users. The basic idea is to use a ranking table of the available channels based on the PU activity detected on each channel. To improve the spectrum efficiency we can implement the Vacate on demand algorithm in MANET Network.
This document summarizes and compares four detection algorithms for spatial modulation with multiple active transmit antennas (MASM): 1) Maximum likelihood (ML) detection, which performs an exhaustive search over all possible symbol vectors; 2) A decorrelator-based suboptimal detection method; 3) An ordered block minimum mean square error (OB-MMSE) detection method; 4) A proposed simplified ML detection method based on symbol cancellation and multi-level subset searching. Through simulations, the proposed detector is found to perform the same as ML detection down to bit error rates of 10-6, with lower complexity than ML detection and OB-MMSE for most configurations.
Improving the selection of MPRs in OLSR protocol: a survey of methods and tec...IJECEIAES
This document summarizes 13 different approaches that have been proposed to improve the selection of Multi Point Relays (MPRs) in the Optimized Link State Routing (OLSR) protocol for mobile ad hoc networks (MANETs). The standard OLSR MPR selection algorithm is limited as it only considers connectivity and does not account for other important node characteristics and metrics. The summarized approaches aim to select MPRs based on additional criteria like energy level, bandwidth, mobility, link quality, location, and trust to make the routing process more efficient and robust. Simulation results indicate that considering multiple metrics can reduce overhead, improve throughput, extend network lifetime, and secure the routing protocol from malicious nodes.
This document presents a geometric progression algorithm for adjacent band power allocation in OFDM-based cognitive radio. The objectives are to minimize interference from secondary users to primary users through optimal transmit power allocation and a novel channel assignment method. The proposed algorithm allocates power to center subcarriers using waterfilling and distributes remaining power to adjacent subcarriers geometrically. Simulation results show the algorithm achieves higher capacity than subcarrier nulling and introduces less interference to primary users compared to an existing method. In conclusion, an analytic closed-form solution is derived for optimal power allocation and the geometric progression algorithm is presented and verified through simulations.
Multiuser MIMO Gaussian Channels: Capacity Region and DualityShristi Pradhan
In this paper, I present the MIMO channel for single user case, discuss the decomposition of MIMO into parallel independent channels, and estimate the MIMO channel capacity. Then, I discuss on computation of capacity region for multiuser MIMO broadcast and multiple access channel and plot capacity regions for two users case. I conclude by showing the duality relationship between the multiple access and broadcast channel and show its significance for numerical standpoint.
A CRITICAL REVIEW OF THE ROUTING PROTOCOLS FOR COGNITIVE RADIO NETWORKS AND A...cscpconf
We present a critical review and analysis of different categories of routing protocols for cognitive radio networks. We first classify the available solutions to two broad categories: those
based on full spectrum knowledge (typically used to establish performance benchmarks) and those based on local spectrum knowledge (used for real-time implementation). The full spectrum knowledge based routing solutions are analyzed from a graph-theoretic point of view, and we review the layered graph, edge coloring and conflict graph models. We classify the various local spectrum knowledge based routing protocols into the following five categories: Minimum power, Minimum delay, Maximum throughput, Geographic and Class-based routing. A total of 25 routing protocols proposed for cognitive radio networks have been reviewed. We discuss the working principle and analyze the pros and cons of the routing protocols. Finally, we propose an idea of a load balancing-based local spectrum knowledge-based routing protocol for cognitive radio ad hoc networks.
The document proposes an energy saving multipath routing protocol (ESMRP) for wireless sensor networks. ESMRP uses a load balancing algorithm to discover multiple node-disjoint paths from sensor nodes to a sink node based on calculated node strengths. It then transmits data along the paths either by single path load balancing or splitting messages across multiple paths with error correction. Simulation results show that ESMRP consumes less energy and has higher delivery ratios than previous protocols.
The document discusses four MAC protocol designs for cognitive radio networks:
1) CMAC protocol with parallel spectrum sensing.
2) CMAC protocol with sequential sensing.
3) CMAC protocol with cooperative sensing.
4) Asynchronous full-duplex CMAC protocol.
For each design, the document analyzes throughput and optimizes sensing and access parameters to maximize throughput while protecting primary users. Numerical results demonstrate throughput improvements from the different MAC protocol designs.
Performance Evaluation Cognitive Medium Access Control Protocolsijtsrd
This document evaluates the performance of two cognitive medium access control (CMAC) protocols: common control-multi channel CMAC protocol and non-common control-multi channel CMAC protocol. It analyzes 30 CMAC protocols based on their features such as number of radios used, prior knowledge of licensed/secondary user systems, and spectrum access techniques. A simulation is conducted using NS2 to compare the throughput and packet delivery ratio of the two protocols. Results show the common control protocol outperforms the non-common control protocol, and that throughput increases with larger packet sizes for both protocols.
The document analyzes and optimizes random sensing order in cognitive radio systems. It presents the following:
- A Markov model is used to evaluate the average throughput of secondary users and average interference between secondary and primary users under a random sensing order policy.
- An optimization problem is formulated to maximize secondary network throughput while keeping interference below a threshold.
- A distributed adaptive algorithm is developed to optimize the network performance in a non-stationary environment. It outperforms static optimization by following wireless channel variations.
- Numerical results demonstrate the algorithm achieves substantial performance gains without centralized control or message passing between users. Fully distributed optimization can efficiently utilize spectrum in cognitive radio networks.
This document proposes an improved position-based power aware routing algorithm for mobile ad-hoc networks. It introduces using a weighted metric of remaining battery power, speed, and distance of nodes to determine routes. The existing MFR (Most Forward within Radius) algorithm does not consider factors like battery power and speed differences, which can lead to unreliable communication or packet loss. The proposed algorithm uses a weighted combination of distance, velocity, and battery power metrics to select routes, aiming to balance load, increase network lifetime, and improve network performance compared to MFR. Simulation results showed the proposed algorithm reduces packet loss and increases throughput compared to MFR.
Classical Discrete-Time Fourier TransformBased Channel Estimation for MIMO-OF...IJCSEA Journal
In this document, we look at various time domain channel estimation methods with this constraint of null carriers at spectrumborders.We showin detail howto gauge the importance of the “border effect” depending on the number of null carriers, which may vary from one system to another. Thereby we assess the limit of the technique discussed when the number of null carriers is large. Finally the DFT with the truncated singular value decomposition (SVD) technique is proposed to completely eliminate the impact of the null subcarriers whatever their number. A technique for the determination of the truncation threshold for any MIMO-OFDM system is also proposed.
This document compares different wavelength assignment algorithms in WDM networks. It proposes a new Least Used Wavelength Conversion algorithm that aims to reduce blocking probability. The algorithm uses least-used wavelength assignment until blocking occurs, then introduces wavelength conversion to reduce blocking. Simulation results show the proposed algorithm has lower blocking probability than first-fit, random, most-used and best-fit algorithms. Blocking probability is evaluated under different network loads and number of wavelengths, demonstrating that blocking decreases with more wavelengths or lower loads.
Performance Analysis of Ultra Wideband Receivers for High Data Rate Wireless ...graphhoc
The document discusses performance comparisons of different receiver structures for high data rate ultra wideband communication systems. It analyzes Rake, MMSE, and Rake-MMSE receivers using MATLAB simulations on IEEE 802.15.3a channel models. The Rake-MMSE receiver combines advantages of Rake fingers and equalization to combat inter-symbol interference. Simulation results show the Rake-MMSE receiver achieves a lower bit error rate than Rake or MMSE receivers alone. The number of Rake fingers improves performance at low-medium SNR, while more equalizer taps help at high SNR.
OPTIMIZED COOPERATIVE SPECTRUM-SENSING IN CLUSTERED COGNITIVE RADIO NETWORKSijwmn
This document summarizes research on optimized cooperative spectrum sensing in clustered cognitive radio networks. The key points are:
1) Secondary users are grouped into clusters and transmit a power function of their observations to a fusion center on orthogonal channels to detect the presence of primary users.
2) The goal is to maximize the probability of detection for a given false alarm probability by optimizing the number of clusters, power function exponent, and linear combining coefficients at the fusion center.
3) Analytical expressions for the probability of detection and false alarm are derived based on the conditional mean and variance of the combined signal at the fusion center under the two hypotheses.
Channel assignment for throughput maximization in cognitive radio networks Polytechnique Montreal
In this paper, we consider the channel allocation problem for throughput maximization in cognitive radio networks with hardware-constrained secondary users. Specifically, we assume that secondary users exploit spectrum holes on a set of channels where each secondary user can use at most one available channel for communication. We develop two channel assignment algorithms that can efficiently utilize spectrum opportunities on these channels. In the first algorithm, secondary users are assigned distinct sets of channels. We show that this algorithm achieves the maximum throughput limit if the number of channels is sufficiently large. In addition, we propose an overlapping channel assignment algorithm, that can improve the throughput performance compared to the non-overlapping channel assignment algorithm. In addition, we design a distributed MAC protocol for access contention resolution and integrate the derived MAC protocol overhead into the second channel assignment algorithm. Finally, numerical results are presented to validate the theoretical results and illustrate the performance gain due to the overlapping channel assignment algorithm.
Distributed MAC Protocol for Cognitive Radio Networks: Design, Analysis, and ...Polytechnique Montreal
In this paper, we investigate the joint optimal sensing and distributed Medium Access Control (MAC) protocol design problem for cognitive radio (CR) networks. We consider both scenarios with single and multiple channels. For each scenario, we design a synchronized MAC protocol for dynamic spectrum sharing among multiple secondary users (SUs), which incorporates spectrum sensing for protecting active primary users (PUs). We perform saturation throughput analysis for the corresponding proposed MAC protocols that explicitly capture the spectrum-sensing performance. Then, we find their optimal configuration by formulating throughput maximization problems subject to detection probability constraints for PUs. In particular, the optimal solution of the optimization problem returns the required sensing time for PUs' protection and optimal contention window to maximize the total throughput of the secondary network. Finally, numerical results are presented to illustrate developed theoretical findings in this paper and significant performance gains of the optimal sensing and protocol configuration.
Iaetsd a novel scheduling algorithms for mimo based wireless networksIaetsd Iaetsd
This document proposes new scheduling algorithms for MIMO wireless networks to improve system performance. It discusses designing practical user scheduling algorithms to maximize capacity in MIMO systems. Various MAC scheduling policies are implemented and modified to provide distributed traffic control, robustness against interference, and increased efficiency of resource utilization. Simulations using MATLAB compare the different policies and draw important results and conclusions. The paper suggests new priority scheduling and partially fair scheduling algorithms incorporating awareness of interference to improve system-level performance in MIMO wireless networks.
Effective capacity in cognitive radio broadcast channelsMarwan Hammouda
Abstract—In this paper, we investigate effective capacity by
modeling a cognitive radio broadcast channel with one secondary transmitter (ST) and two secondary receivers (SRs) under quality-of-service constraints and interference power limitations.We initially describe three different ooperative channel sensing strategies with different ard-decision combining algorithms at the ST, namely OR, Majority, and AND rules. Since the channel sensing occurs with possible errors, we consider a combined
interference power constraint by which the transmission power of the secondary users (SUs) is bounded when the channel is sensed as both busy and idle. Furthermore, regarding the channel sensing decision and its correctness, there exist ...
Effect of Channel Variations on the Spectral Efficiency of Multiuser Diversit...IDES Editor
This document analyzes how the spectral efficiency of a multiuser diversity MIMO system is affected when the channel type deviates from Rayleigh fading to Nakagami-m fading. It simulates a system with different MIMO configurations and compares the average user data rates under absolute and proportional SNR scheduling schemes at 0dB, 10dB, and 20dB. The results show that user data rates decrease the most at 0dB SNR as the channel type changes from Rayleigh to Nakagami-m fading, with higher m values leading to greater losses.
Routing in All-Optical Networks Using Recursive State Space Techniquesipij
In this papr, we have minimized the effects of failures on network performace, by using suitable Routing
and Wavelenghth Assignment(RWA) method without disturbing other performance criteria such as blocking
probability(BP) and network management(NM). The computation complexity is reduced by using Kalaman
Filter(KF) techniques. The minimum reconfiguration probability routing (MRPR) algorithm must be
able to select most reliable routes and assign wavelengths to connections in a manner that utilizes the light
path(LP) established efficiently considering all possible requests.
This document proposes using multiple input multiple output (MIMO) antennas for spectrum sensing in cognitive radio to improve detection performance. It summarizes that MIMO antennas can increase the probability of detection and decrease the probability of missed detection of primary users. The document then reviews common spectrum sensing techniques and their limitations. It presents a cognitive radio algorithm that implements spectrum sensing using MIMO antennas with different antenna configurations on primary and secondary users. Simulation results show the probability of detection increases and probability of missed detection decreases with higher MIMO antenna diversity order.
Implementation of Vacate on Demand Algorithm in Various Spectrum Sensing Netw...IJERA Editor
In present days the wireless communications are widely increases because of this reason spectrum utilization can be rapidly increased.For efficient usage of spectrum we can implement the Vacate on demand algorithm in different networks. CR users also need to sense the spectrum and vacate the channel upon the detection of the PU‟s presence to protectPUs from harmful interference. To achieve these fundamental CR functions, CR users usually coordinate with each other by using a common medium for control message exchange ensuring a priority of PUs over CR users. This paper presents the Vacate on Demand (VD) algorithm which enables dynamic spectrum access and ensures to vacate the assigned channel in case of PU activity and move the CR user to some other vacant channel to make spectrum available to PUs as well as to CR users. The basic idea is to use a ranking table of the available channels based on the PU activity detected on each channel. To improve the spectrum efficiency we can implement the Vacate on demand algorithm in MANET Network.
This document summarizes and compares four detection algorithms for spatial modulation with multiple active transmit antennas (MASM): 1) Maximum likelihood (ML) detection, which performs an exhaustive search over all possible symbol vectors; 2) A decorrelator-based suboptimal detection method; 3) An ordered block minimum mean square error (OB-MMSE) detection method; 4) A proposed simplified ML detection method based on symbol cancellation and multi-level subset searching. Through simulations, the proposed detector is found to perform the same as ML detection down to bit error rates of 10-6, with lower complexity than ML detection and OB-MMSE for most configurations.
Improving the selection of MPRs in OLSR protocol: a survey of methods and tec...IJECEIAES
This document summarizes 13 different approaches that have been proposed to improve the selection of Multi Point Relays (MPRs) in the Optimized Link State Routing (OLSR) protocol for mobile ad hoc networks (MANETs). The standard OLSR MPR selection algorithm is limited as it only considers connectivity and does not account for other important node characteristics and metrics. The summarized approaches aim to select MPRs based on additional criteria like energy level, bandwidth, mobility, link quality, location, and trust to make the routing process more efficient and robust. Simulation results indicate that considering multiple metrics can reduce overhead, improve throughput, extend network lifetime, and secure the routing protocol from malicious nodes.
This document presents a geometric progression algorithm for adjacent band power allocation in OFDM-based cognitive radio. The objectives are to minimize interference from secondary users to primary users through optimal transmit power allocation and a novel channel assignment method. The proposed algorithm allocates power to center subcarriers using waterfilling and distributes remaining power to adjacent subcarriers geometrically. Simulation results show the algorithm achieves higher capacity than subcarrier nulling and introduces less interference to primary users compared to an existing method. In conclusion, an analytic closed-form solution is derived for optimal power allocation and the geometric progression algorithm is presented and verified through simulations.
Multiuser MIMO Gaussian Channels: Capacity Region and DualityShristi Pradhan
In this paper, I present the MIMO channel for single user case, discuss the decomposition of MIMO into parallel independent channels, and estimate the MIMO channel capacity. Then, I discuss on computation of capacity region for multiuser MIMO broadcast and multiple access channel and plot capacity regions for two users case. I conclude by showing the duality relationship between the multiple access and broadcast channel and show its significance for numerical standpoint.
A CRITICAL REVIEW OF THE ROUTING PROTOCOLS FOR COGNITIVE RADIO NETWORKS AND A...cscpconf
We present a critical review and analysis of different categories of routing protocols for cognitive radio networks. We first classify the available solutions to two broad categories: those
based on full spectrum knowledge (typically used to establish performance benchmarks) and those based on local spectrum knowledge (used for real-time implementation). The full spectrum knowledge based routing solutions are analyzed from a graph-theoretic point of view, and we review the layered graph, edge coloring and conflict graph models. We classify the various local spectrum knowledge based routing protocols into the following five categories: Minimum power, Minimum delay, Maximum throughput, Geographic and Class-based routing. A total of 25 routing protocols proposed for cognitive radio networks have been reviewed. We discuss the working principle and analyze the pros and cons of the routing protocols. Finally, we propose an idea of a load balancing-based local spectrum knowledge-based routing protocol for cognitive radio ad hoc networks.
The document proposes an energy saving multipath routing protocol (ESMRP) for wireless sensor networks. ESMRP uses a load balancing algorithm to discover multiple node-disjoint paths from sensor nodes to a sink node based on calculated node strengths. It then transmits data along the paths either by single path load balancing or splitting messages across multiple paths with error correction. Simulation results show that ESMRP consumes less energy and has higher delivery ratios than previous protocols.
The document discusses four MAC protocol designs for cognitive radio networks:
1) CMAC protocol with parallel spectrum sensing.
2) CMAC protocol with sequential sensing.
3) CMAC protocol with cooperative sensing.
4) Asynchronous full-duplex CMAC protocol.
For each design, the document analyzes throughput and optimizes sensing and access parameters to maximize throughput while protecting primary users. Numerical results demonstrate throughput improvements from the different MAC protocol designs.
Performance Evaluation Cognitive Medium Access Control Protocolsijtsrd
This document evaluates the performance of two cognitive medium access control (CMAC) protocols: common control-multi channel CMAC protocol and non-common control-multi channel CMAC protocol. It analyzes 30 CMAC protocols based on their features such as number of radios used, prior knowledge of licensed/secondary user systems, and spectrum access techniques. A simulation is conducted using NS2 to compare the throughput and packet delivery ratio of the two protocols. Results show the common control protocol outperforms the non-common control protocol, and that throughput increases with larger packet sizes for both protocols.
This document proposes and analyzes a distributed medium access control (MAC) protocol for full-duplex cognitive radio networks. The key aspects of the proposed protocol are:
1) It employs frame fragmentation, dividing each data packet into multiple fragments, to enable secondary users to perform spectrum sensing during data transmission and detect primary user activity in a timely manner.
2) Secondary users use a backoff mechanism similar to 802.11 to contend for channel access. The winning secondary user then transmits data fragments while sensing for primary users between fragments.
3) The document develops a mathematical model to analyze the throughput performance of the protocol and proposes an algorithm to optimize protocol parameters like fragment time and transmit power to maximize throughput
Multiple Group Handling Cognitive Radio Network With High AccuracyIRJET Journal
This document proposes adaptive grouping algorithms for cooperative spectrum sensing in cognitive radio networks with heterogeneous sensing abilities among secondary users. It formulates the throughput efficiency maximization problem and proposes three assignment algorithms - Channel Selection Best User Assignment (CSBUA), Best User Assignment for Channel Selection 1 (BUACS1), and Best User Assignment for Channel Selection 2 (BUACS2) - to assign heterogeneous secondary users to groups to maximize throughput while maintaining sensing accuracy. Simulation results show the proposed algorithms achieve comparable performance to the optimal solution with lower complexity and outperform existing non-adaptive and sequential sensing schemes.
Stochastic analysis of random ad hoc networks with maximum entropy deploymentsijwmn
In this paper, we present the first stochastic analysis of the link performance of an ad hoc network modelled
by a single homogeneous Poisson point process (HPPP). According to the maximum entropy principle, the
single HPPP model is mathematically the best model for random deployments with a given node density.
However, previous works in the literature only consider a modified model which shows a discrepancy in the
interference distribution with the more suitable single HPPP model. The main contributions of this paper
are as follows. 1) It presents a new mathematical framework leading to closed form expressions of the
probability of success of both one-way transmissions and handshakes for a deployment modelled by a
single HPPP. Our approach, based on stochastic geometry, can be extended to complex protocols. 2) From
the obtained results, all confirmed by comparison to simulated data, optimal PHY and MAC layer
parameters are determined and the relations between them is described in details. 3) The influence of the
routing protocol on handshake performance is taken into account in a realistic manner, leading to the
confirmation of the intuitive result that the effect of imperfect feedback on the probability of success of a
handshake is only negligible for transmissions to the first neighbour node.
ENERGY EFFICIENCY OF MIMO COOPERATIVE NETWORKS WITH ENERGY HARVESTING SENSOR ...ijasuc
This paper addresses the maximizing network lifetime problem in wireless sensor networks (WSNs) taking
into account the total Symbol Error rate (SER) at destination. Therefore, efficient power management is
needed for extend network lifetime. Our approach consists to provide the optimal transmission power
using the orthogonal multiple access channels between each sensor. In order to deeply study the
properties of our approach, firstly, the simple case is considered; the information sensed by the source
node passes by a single relay before reaching the destination node. Secondly, global case is studied; the
information passes by several relays. We consider, in the previous both cases, that the batteries are nonrechargeable. Thirdly, we spread our work the case where the batteries are rechargeable with unlimited
storage capacity. In all three cases, we suppose that Maximum Ratio Combining (MRC) is used as a
detector, and Amplify and Forward (AF) as a relaying strategy. Simulation results show the viability of
our approach which the network lifetime is extended of more than 70.72%when the batteries are non
rechargeable and 100.51% when the batteries are rechargeable in comparison with other traditional
method.
ENERGY EFFICIENCY OF MIMO COOPERATIVE NETWORKS WITH ENERGY HARVESTING SENSOR ...ijasuc
This paper addresses the maximizing network lifetime problem in wireless sensor networks (WSNs) taking
into account the total Symbol Error rate (SER) at destination. Therefore, efficient power management is
needed for extend network lifetime. Our approach consists to provide the optimal transmission power
using the orthogonal multiple access channels between each sensor. In order to deeply study the
properties of our approach, firstly, the simple case is considered; the information sensed by the source
node passes by a single relay before reaching the destination node. Secondly, global case is studied; the
information passes by several relays. We consider, in the previous both cases, that the batteries are nonrechargeable. Thirdly, we spread our work the case where the batteries are rechargeable with unlimited
storage capacity. In all three cases, we suppose that Maximum Ratio Combining (MRC) is used as a
detector, and Amplify and Forward (AF) as a relaying strategy. Simulation results show the viability of
our approach which the network lifetime is extended of more than 70.72%when the batteries are non
rechargeable and 100.51% when the batteries are rechargeable in comparison with other traditional
method.
Bio-inspired route estimation in cognitive radio networks IJECEIAES
Cognitive radio is a technique that was originally created for the proper use of the radio electric spectrum due its underuse. A few methods were used to predict the network traffic to determine the occupancy of the spectrum and then use the ‘holes’ between the transmissions of primary users. The goal is to guarantee a complete transmission for the second user while not interrupting the trans-mission of primary users. This study seeks the multifractal generation of traffic for a specific radio electric spectrum as well as a bio-inspired route estimation for secondary users. It uses the MFHW algorithm to generate multifractal traces and two bio-inspired algo-rithms: Ant Colony Optimization and Max Feeding to calculate the secondary user’s path. Multifractal characteristics offer a predic-tion, which is 10% lower in comparison with the original traffic values and a complete transmission for secondary users. In fact, a hybrid strategy combining both bio-inspired algorithms promise a reduction in handoff. The purpose of this research consists on deriving future investigation in the generation of multifractal traffic and a mobility spectrum using bio-inspired algorithms.
Design and analysis of routing protocol for cognitive radio ad hoc networks i...IJECEIAES
Multi-hop routing protocol in cognitive radio mobile ad hoc networks (CRMANETs) is a critical issue. Furthermore, the routing metric used in multi-hop CRMANETs should reflect the bands availability, the links quality, the PU activities and quality of service (QoS) requirements of SUs. For the best of our knowledge, many of researchers investigated the performance of the different routing protocols in a homogeneous environment only. In this paper, we propose a heterogeneous cognitive radio routing protocol (HCR) operates in heterogeneous environment (i.e. the route from source to destination utilize the licensed and unlicensed spectrum bands). The proposed routing protocol is carefully developed to make a tradeoff between the channel diversity of the routing path along with the CRMANETs throughput. Using simulations, we discuss the performance of the proposed HCR routing protocol and compare it with the AODV routing protocol using a discrete-event simulation which we developed using JAVA platform.
Cooperative-hybrid detection of primary user emulators in cognitive radio net...IJECEIAES
Primary user emulator (PUE) attack occurs in Cognitive Radio Networks (CRNs) when a malicious secondary user (SU) poses as a primary user (PU) in order to deprive other legitimate SUs the right to free spectral access for opportunistic communication. In most cases, these legitimate SUs are unable to effectively detect PUEs because the quality of the signals received from a PUE may be severely attenuated by channel fading and/or shadowing. Consequently, in this paper, we have investigated the use of cooperative spectrum sensing (CSS) to improve PUE detection based on a hybrid localization scheme. We considered different pairs of secondary users (SUs) over different received signal strength (RSS) values to evaluate the energy efficiency, accuracy, and speed of the new cooperative scheme. Based on computer simulations, our findings suggest that a PUE can be effectively detected by a pair of SUs with a low Root Mean Square Error rate of 0.0047 even though these SUs may have close RSS values within the same cluster. Furthermore, our scheme performs better in terms of speed, accuracy and low energy consumption rates when compared with other PUE detection schemes. Thus, it is a viable proposition to better detect PUEs in CRNs.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
This document discusses quality of service analysis for secondary users in a cognitive radio system using an interweave access scenario. It presents a continuous time Markov chain model to calculate blocking probability and forced termination probability for secondary users. The model is analyzed for both fixed payload length and exponentially distributed payload lengths. Numerical results show that blocking probability and forced termination probability are greater for fixed payload length compared to exponentially distributed payload length.
This document presents a study on analyzing quality of service (QoS) parameters for secondary users in an interweave cognitive radio access scenario using a continuous time Markov chain (CTMC) model. The QoS parameters of blocking probability and force termination probability are calculated for both fixed payload length and exponential distribution payload length. Numerical results show that the blocking probability and force termination probability are greater for fixed payload length compared to exponential distribution payload length. CTMC models are developed to represent the system states and derive closed-form expressions for the QoS parameters for both payload scenarios. Graphs of the analytical results demonstrate the trends in blocking probability and force termination probability as payload length and other parameters are varied.
Shared Spectrum Throughput for Secondary UsersCSCJournals
The throughput performance of secondary users sharing radio spectrum with a licensed primary user is analyzed in this work. An asynchronous transmission, sensing and backoff protocol is proposed for the secondary user and modeled as a six state Markov process. The model parameters are derived as a function of the duty cycle and average duration that the channel is unoccupied by the primary user. The secondary user parameters include its continuous transmission duration or packet size and its backoff window size. The model results show that the probabilities of the secondary user being in the transmit state are relatively invariant to the duty cycle compared to the probability of being in the backoff state, particularly at low to moderate secondary packet sizes. The secondary user throughput is expressed as a function of the aforementioned parameters and shown to change significantly with duty cycle and secondary packet sizes. It is found that at very low duty cycles, the throughput variation is insensitive to backoff duration being random or fixed. The proposed transmission and sensing method is also shown to outperform a periodic sensing protocol. The regions of the parameter space wherein the backoff and retransmit probabilities of the secondary user are bounded by specified performance metrics are derived. The sensitivity of the throughput in the presence of a cooperative and non- cooperative secondary user is also investigated.
This document summarizes a simulation of wireless sensor networks to analyze power-efficient protocols and algorithms. It describes simulating three techniques - power control, closest-first and farthest-first routing algorithms, and sleep mode. The simulation analyzes these techniques individually and together to evaluate their impact on network lifetime and mean delay.
A SEMI BLIND CHANNEL ESTIMATION METHOD BASED ON HYBRID NEURAL NETWORKS FOR UP...ijwmn
The paper describes how to improve channel estimation in Single Carrier Frequency Division Multiple
Access (SC-FDMA) system, using a Hybrid Artificial Neural Networks (HANN). The 3rd Generation
Partnership Project (3GPP) standards for uplink Long Term Evolution Advanced (LTE-A) uses pilot based
channel estimation technique. This kind of channel estimation method suffers from a considerable loss
ofbitrate due to pilot insertion; all data frame sent contains reference signal. The HANN converts data
aided channel estimator to semi blind channel estimator. To increase convergence speed, HANN uses some
channel propagation Fuzzy Rules to initialize Neural Network parameters before learning instead of a
random initialization, so its learning phase ismore rapidly compared to classic ANN.HANN allows more
bandwidth efficient and less complexity. Simulation results show that HANN has better computational
efficiency than the Minimum Mean Square Error (MMSE) estimator and has faster convergence than
classic Neural Networks estimators.
Multi-slot Coded ALOHA with Irregular Degree.pdfYAAKOVSOLOMON1
This document proposes an improvement to the Multi-slot Coded ALOHA (MuSCA) random multiple access scheme for satellite communications. The improvement involves applying variable code rates and irregular user degree distributions, where the code rate and degree for each user are selected according to a probability distribution. This allows the system to achieve higher throughput compared to the original MuSCA scheme and other related schemes like Contention Resolution Diversity Slotted ALOHA (CRDSA). The document describes how the system would work, including encoding data into codewords that are split into multiple bursts and transmitted on random slots, and decoding the received signal using successive interference cancellation. It analyzes the potential throughput gain from optimizing the irregular degree distribution.
Channel feedback scheduling for wireless communicationseSAT Journals
Abstract Opportunistic scheduling can significantly improve wireless network performance by exploiting the underlying channel condition. There has been a lot of work on opportunistic scheduling, but the problem of finding the right feedback mechanism to convey channel information has largely been untouched. In emerging multichannel systems, the per-channel feedback induces a substantial amount of feedback overhead and requires high computational complexity. To reduce the feedback overhead, we consider an opportunistic feedback strategy that activates the channel feedback opportunistically according to the channel condition. Then, we combine the opportunistic feedback with the best-n channel feedback scheme where a mobile user chooses the best n channels and transfers this information to the base station. We analyze the throughput and the amount of channel feedback information for proportionally fair opportunistic scheduling under Rayleigh fading i.i.d. channels. The numerical results confirm that our partial feedback schemes achieve a remarkable reduction in the amount of feedback information without significant throughput degradation, thereby saving the scarce wireless bandwidth and limited battery power.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
An Energy–Efficient Heuristic based Routing Protocol in Wireless Sensor Netw...AM Publications,India
Energy consumption is the critical issue to determine the lifetime of Wireless sensor networks (WSNs), due to limited batteries power resource of sensor nodes. The optimization of energy consumption is involves reduction of energy consumption in order to prolong the lifetime of the network as much as possible. However, to minimize the overall energy consumption of the sensor network, different types of routing protocols have been proposed. This paper proposes an energy efficient routing protocol using the A-star search algorithm to find the optimal path from the source node to the sink node. Simulation results with Matlab show that our proposed protocol is efficient in terms of total energy consumption and network lifetime compared with fuzzy approach.
Similar to General analytical framework for cooperative sensing and access trade-off optimization (20)
This document discusses the joint design of data compression and medium access control (MAC) protocol for smart grids with renewable energy sources. It proposes using compressed sensing (CS) techniques to compress reported power injection data from multiple nodes in both space and time, and adapting the 802.15.4 MAC protocol to enable efficient data transmission and reliable data reconstruction. An analytical model is developed to determine optimal MAC parameter configurations that minimize reporting delay while achieving reliable data recovery. Numerical results are presented to demonstrate performance gains over existing solutions in terms of reporting delay, energy consumption, and bandwidth usage.
Design and Optimal Configuration of Full-Duplex MAC Protocol for Cognitive Ra...Polytechnique Montreal
In this paper, we propose an adaptive medium access control (MAC) protocol for
full-duplex (FD) cognitive radio networks in which FD secondary users (SUs) perform channel contention
followed by concurrent spectrum sensing and transmission, and transmission only with maximum power
in two different stages (called the FD sensing and transmission stages, respectively) in each contention
and access cycle. The proposed FD cognitive MAC (FDC-MAC) protocol does not require synchronization
among SUs, and it efciently utilizes the spectrum and mitigates the self-interference in the FD transceiver.
We develop a mathematical model to analyze the throughput performance of the FDC-MAC protocol, where
both half-duplex (HD) transmission and FD transmission modes are considered in the transmission stage.
Then, we study the FDC-MAC conguration optimization through adaptively controlling the spectrum
sensing duration and transmit power level in the FD sensing stage.We prove that there exists optimal sensing
time and transmit power to achieve the maximum throughput, and we develop an algorithm to congure
the proposed FDC-MAC protocol. Extensive numerical results are presented to illustrate the optimal
FDC-MAC conguration and the impacts of protocol parameters and the self-interference cancellation
quality on the throughput performance. Moreover, we demonstrate the signicant throughput gains of the
FDC-MAC protocol with respect to the existing HD MAC and single-stage FD MAC protocols
This dissertation investigates design and optimization issues for cognitive medium access control (CMAC) protocols in cognitive radio networks. It presents four main contributions:
1) A CMAC protocol for parallel spectrum sensing that maximizes throughput for single-channel and multi-channel scenarios.
2) A CMAC protocol and channel assignment algorithm for sequential sensing that maximizes network throughput in hardware-constrained networks.
3) A distributed CMAC protocol integrated with cooperative sensing to improve spectrum utilization for multi-channel heterogeneous networks. Impacts of reporting errors are also considered.
4) An asynchronous full-duplex CMAC protocol that enables simultaneous sensing and access to maximize throughput by adapting sensing time and transmit powers based on detected primary user activity
The document proposes a full-duplex cognitive MAC (FDC-MAC) protocol for cognitive radio networks. The protocol consists of two stages: (1) a FD sensing stage where secondary users perform concurrent spectrum sensing and transmission at a controlled power level to mitigate self-interference, and (2) a transmission stage where secondary users transmit at maximum power if the sensing stage indicated an available channel. The document develops a mathematical model to analyze the throughput performance of the FDC-MAC protocol and proves that there exists an optimal sensing time and transmit power configuration to maximize throughput. Extensive simulation results demonstrate significant throughput gains of the FDC-MAC protocol over half-duplex and single-stage full-duplex MAC protocols.
This document proposes a joint design of data compression and MAC protocol for smart grids using compressed sensing. It aims to minimize reporting time while reliably reconstructing power injection data from multiple nodes. Specifically, it employs two-dimensional compressed sensing to compress correlated power data in space and time. It also adapts the 802.15.4 MAC protocol frame structure to enable efficient data transmission for reconstruction. An analytical model is developed to optimize MAC parameters and guarantee reliable data reconstruction with minimum reporting delay.
In order to improve sensing performance when the noise variance is not known, this paper considers a so-called
blind spectrum sensing technique that is based on eigenvalue models. In this paper, we employed the spiked population
models in order to identify the miss detection probability. At first, we try to estimate the unknown noise variance
based on the blind measurements at a secondary location. We then investigate the performance of detection, in terms
of both theoretical and empirical aspects, after applying this estimated noise variance result. In addition, we study the
effects of the number of SUs and the number of samples on the spectrum sensing performance.
Using Subspace Pursuit Algorithm to Improve Performance of the Distributed Co...Polytechnique Montreal
This paper applies a compressed algorithm to improve the spectrum sensing performance of cognitive radio technology.
At the fusion center, the recovery error in the analog to information converter (AIC) when reconstructing the
transmit signal from the received time-discrete signal causes degradation of the detection performance. Therefore, we
propose a subspace pursuit (SP) algorithm to reduce the recovery error and thereby enhance the detection performance.
In this study, we employ a wide-band, low SNR, distributed compressed sensing regime to analyze and evaluate the
proposed approach. Simulations are provided to demonstrate the performance of the proposed algorithm.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms.
Capacity Performance Analysis for Decode-and-Forward OFDMDual-Hop SystemPolytechnique Montreal
In this paper, we propose an exact analytical technique to evaluate the average capacity of a dual-hop OFDM relay system with decode-and-forward protocol in an independent and identical distribution (i.i.d.) Rayleigh fading channel. Four schemes, (no) matching “and” or “or” (no) power allocation, will be considered. First, the probability density function (pdf) for the end-to-end power channel gain for each scheme is described. Then, based on these pdf functions, we will give the expressions of the average capacity. Monte Carlo simulation results will be shown to confirm the analytical results for both the pdf functions and average capacities.
Performance of cognitive radio networks with maximal ratio combining over cor...Polytechnique Montreal
This document analyzes the performance of cognitive radio networks using maximal ratio combining over correlated Rayleigh fading channels. It presents a simple analytical method to derive closed-form expressions for the probabilities of detection and false alarm. The key findings are:
1) The detection probability is a monotonically increasing function of the number of antennas, as more antennas provides more diversity gain.
2) Antenna correlation degrades the sensing performance compared to independent antennas. Higher correlation results in lower detection probability.
3) Complementary receiver operating characteristic curves illustrate that both higher signal-to-noise ratio and lower antenna correlation improve detection performance by increasing the detection probability and decreasing the probability of miss at a given false alarm probability.
A novel and efficient mixed-signal compressed sensing for wide-band cognitive...Polytechnique Montreal
In cognitive radio (CR) networks, unlicensed (cognitive) users can exploit the licensed frequency bands by using spectrum sensing techniques to identify spectrum holes. This paper proposes a distributed compressive spectrum sensing scheme, in which the modulated wide-band converter can apply compressed sensing (CS) directly to analog signals at the sub-Nyquist rate and the central fusion receives signals from multiple CRs and exploits the multiple-measurements-vectors (MMV) subspace pursuit (M-SP) algorithm to jointly reconstruct the spectral support of the wide-band signal. This support is then used to detect whether the licensed bands are occupy or not. Finally, extensive simulation results show the advantages of the proposed scheme. Besides, we also compare the performance of M-SP with M-orthogonal matching pursuit (M-OMP) algorithms.
Projected Barzilai-Borwein Methods Applied to Distributed Compressive Spectru...Polytechnique Montreal
Cognitive radio allows unlicensed (cognitive) users to use licensed frequency bands by exploiting spectrum sensing techniques to detect whether or not the licensed (primary) users are present. In this paper, we present a compressed sensing applied to spectrum-occupancy detection in wide-band applications. The collected analog signals from each cognitive radio (CR) receiver at a fusion center are transformed to discrete-time signals by using analog-to-information converter (AIC) and then employed to calculate the autocorrelation. For signal reconstruction, we exploit a novel approach to solve the optimization problem consisting of minimizing both a quadratic (l2) error term and an l1-regularization term. In specific, we propose the Basic gradient projection (GP) and projected Barzilai-Borwein (PBB) algorithm to offer a better performance in terms of the mean squared error of the power spectrum density estimate and the detection probability of licensed signal occupancy.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
6. 3 +
Fig. 1. Network model (PU: primary user, SU: secondary user)
to pair i of SUs simply as SU i. We assume that each SU
can exploit multiple available channels for transmission (e.g.,
by using OFDM technology). We will design a synchronized
MAC protocol for channel access. We assume that each chan-
nel is either in the idle or busy state for each predetermined
periodic interval, which is called a cycle in this paper.
We further assume that each pair of SUs can overhear trans-
missions from other pairs of SUs (i.e., collocated networks).
There are M primary users (PUs) each of which may or may
not use one corresponding channel for its data transmission
in any cycle. In addition, it is assumed that transmission from
any pair of SUs on a particular channel will affect the primary
receiver which receives data on that channel. The network
setting under investigation is shown in Fig. 1.
B. Cooperative Spectrum Sensing
We assume that each SU i is assigned in advance a set
of channels Si where it senses all channels in this assigned
list at beginning of each cycle. Optimization of such channel
assignment will be considered in the next section. Upon
completing the channel sensing, each SU i sends the idle/busy
states of all channels in Si to the access point (AP) for further
processing. The AP upon collecting sensing results from all
SUs will decide idle/busy status for all channels. Then, the AP
broadcasts the list of available channels to all SUs. SUs are
assumed to rely on a distributed MAC protocol to perform
access resolution where the winning SU transmits data by
using all available channels. Detailed MAC protocol design
will be elaborated later.
Let H0 and H1 denote the events that a particular PU is
idle and active, respectively (i.e., the corresponding channel
is available and busy, respectively) in a cycle. In addition,
let Pj (H0) and Pj (H1) = 1 − Pj (H0) be the probabil-
ities that channel j is available and not available for all
SUs, respectively. We assume that SUs employ an energy
detection scheme and let fs be the sampling frequency used
in the sensing period for all SUs. There are two important
performance measures, which are used to quantify the sensing
performance, namely detection and false alarm probabilities.
In particular, detection event occurs when a SU successfully
senses a busy channel and false alarm represents the situation
when a spectrum sensor returns a busy status for an idle
channel (i.e., a transmission opportunity is overlooked).
Assume that transmission signals from PUs are complex-
valued PSK signals while the noise at the SUs is indepen-
dent and identically distributed circularly symmetric complex
Gaussian CN (0, N0) [4]. Then, the detection and false alarm
probabilities for the channel j at SU i can be calculated as [4]
Pij
d εij
, τij
= Q
εij
N0
− γij
− 1
τijfs
2γij + 1
, (1)
Pij
f εij
, τij
= Q
εij
N0
− 1 τijfs
= Q 2γij + 1Q−1
Pij
d εij
, τij
+ τijfsγij
, (2)
where i ∈ [1, N] is the index of a SU link, j ∈ [1, M] is
the index of a channel, εij
is the detection threshold for an
energy detector, γij
is the signal-to-noise ratio (SNR) of the
PU’s signal at the SU, fs is the sampling frequency, N0 is the
noise power, τij
is the sensing interval of SU i on channel j,
and Q (.) is defined as Q (x) = 1/
√
2π
∞
x
exp −t2
/2 dt.
We assume that a general cooperative sensing scheme,
namely a-out-of-b rule, is employed by the AP to determine
the idle/busy status of each channel based on reported sensing
results from all SUs. Under this scheme, the AP will declare
that a channel is available if a or more SUs out of b SUs report
that the underlying channel is available. The a-out-of-b rule
covers different other rules including OR, AND and Majority
rules as special cases. In particular, when a = 1, it is OR
rule; when a = b, it is AND rule; and when a = b/2 , it is
Majority rule. Let consider channel j. Let SU
j denote the set
of SUs that sense channel j and bj = SU
j be the number of
SUs sensing channel j. Then the AP’s decision on the status of
channel j will result in detection and false alarm probabilities
for this channel, which can be calculated as, respectively [8]
Pj
d εj
, τj
, aj =
bj
l=aj
Cl
bj
k=1 i1∈Φk
l
Pi1j
d
i2∈SU
j Φk
l
¯Pi2j
d (3)
Pj
f εj
, τj
, aj =
bj
l=aj
Cl
bj
k=1 i1∈Φk
l
Pi1j
f
i2∈SU
j Φk
l
¯Pi2j
f (4)
where Φk
l in (3) and (4) are particular sets with l SUs whose
sensing outcomes indicate that channel j is busy given that
this channel is indeed busy and idle, respectively; εj
= εij
,
τj
= τij
, i ∈ SU
j . For brevity, Pj
d εj
, τj
, aj and
Pj
f εj
, τj
, aj are written as Pj
d and Pj
f in the following.
C. MAC Protocol Design
We assume that time is divided into fixed-size cycles and
it is assumed that SUs can perfectly synchronize with each
other (i.e., there is no synchronization error) [12]. We propose
a synchronized multi-channel MAC protocol for dynamic
spectrum sharing as follows. The MAC protocol has three
phases in each cycle utilizing one control channel, which is
assumed to be always available, as illustrated in Fig. 2. In
the first phase, namely the sensing phase of length τ, all SUs
simultaneously perform spectrum sensing on their assigned
1698
7. 3
2QH FFOH
WLPH
6HQVLQJ 61
',)6
$.
6,)6
'$7$2175HSRUW
%URDGFDVW
'$7$217
'$7$
'$7$'$7$'
RQWURO FKDQQHO
WLPH
' 'DWD FKDQQHO 217 RQWHQWLRQ
Fig. 2. Timing diagram of the proposed multi-channel MAC protocol
channels. Here, we have τ = maxi τi, where τi = j∈Si
τij
is total sensing time of SU i, τij is the sensing time of SU i
on channel j, and Si is the set of channels assigned for SU
i. All SUs exchange beacon signals on the control channel to
achieve synchronization in the second phase. Then, each SU
reports its sensing results to the AP on the control channel.
The AP collects sensing results from all SUs; decide idle/status
for all channels; and broadcast this information to all SUs on
the control channel.
In the third phase, SUs participate in the contention and
the winning SU will transmit data on all vacant channels. We
assume that the length of each cycle is sufficiently large so that
SUs can transmit several packets during the data transmission
phase. During the data transmission phase, we assume that ac-
tive SUs employ a standard contention technique to capture the
channel similar to that in the CSMA/CA protocol. Exponential
backoff with minimum contention window W and maximum
backoff stage m0 [13] is employed in the contention phase.
For brevity, we refer to W simply as contention window in
the following. Specifically, suppose that the current backoff
stage of a particular SU is i then it starts the contention
by choosing a random backoff time uniformly distributed in
the range [0, 2i
W − 1], 0 ≤ i ≤ m0. This user then starts
decrementing its backoff time counter while carrier sensing
transmissions from other SUs on vacant channels.
Let σ denote a mini-slot interval, each of which corre-
sponds one unit of the backoff time counter. Upon hearing a
transmission from any SU, each SU will “freeze” its backoff
time counter and reactivate when the channel is sensed idle
again. Otherwise, if the backoff time counter reaches zero, the
underlying SU wins the contention. Here, two-way handshake
will be employed to transmit one data packet on the available
channel. After sending the data packet the transmitter expects
an acknowledgment (ACK) from the receiver to indicate a
successful reception of the packet. Standard small intervals,
namely DIFS and SIFS, are used before backoff time decre-
ments and ACK packet transmission as described in [13].
III. PERFORMANCE ANALYSIS, DESIGN, AND
OPTIMIZATION
A. Throughput Analysis
We assume that all SUs transmit data packets of the same
length. Let E denote the average number of vacant channels
that are correctly detected by the AP. Suppose T (τ, W) denote
the throughput achieved by all N SUs on an imaginary single-
channel network where the channel is always available. Then,
the normalized throughput per one channel achieved by our
MAC protocol can be calculated as
NT = T (τ, W)
1
M
E (5)
Here, E can be calculated as follows:
E =
M
m=1
Cm
M
i=1 j1∈Ψi
m
Pj1
(H0)
j2∈SΨi
m
Pj2
(H1) (6)
×
m
n=1
Cn
m
i1=1
n
j3∈Θ
i1
n
¯Pj3
f
j4∈Ψi
mΘ
i1
n
Pj4
f (7)
where S is the set of all M channels. The quantity (6)
represents the probability that there are m available channels,
which may or may not be correctly detected by SUs and the
AP. Here, Ψi
m denotes a particular set of m available channels
whose index is i. The second quantity (7) describes the product
of n and the probability that there are n available channels
according to the sensing decision of the AP (so the remaining
available channels are overlooked due to sensing errors) where
Θi1
n denotes the i1-th set with n available channels.
In the following, we describe how to calculate T (τ, W) by
using the technique developed by Bianchi in [13]. In particular,
we approximately assume a fixed transmission probability φ
in a generic slot time. Bianchi shows that this transmission
probability can be computed from the following two equations
[13]
φ =
2 (1 − 2p)
(1 − 2p) (W + 1) + Wp (1 − (2p)
m0
)
, (8)
p = 1 − (1 − φ)
n−1
, (9)
where m0 is the maximum backoff stage, p is the conditional
collision probability (i.e., the probability that a collision is
observed when a data packet is transmitted on the channel).
For our system, there are N SUs participating in contention in
the third phase, the probability that at least one SU transmits
its data packet can be written as
Pt = 1 − (1 − φ)
N
. (10)
However, the probability that a transmission occurring on the
channel is successful given there is at least one SU transmitting
can be written as
Ps =
Nφ (1 − φ)
N−1
Pt
. (11)
The average duration of a generic slot time can be calculated
as
¯Tsd = (1 − Pt) Te + PtPsTs + Pt (1 − Ps) Tc, (12)
where Te = σ, Ts and Tc represent the duration of an empty
slot, the average time the channel is sensed busy due to a
successful transmission, and the average time the channel is
sensed busy due to a collision, respectively. These quantities
can be calculated under the basic access mechanism as [13]
⎧
⎪⎨
⎪⎩
Ts =T1
s =H+PS+SIFS+2PD+ACK+DIFS
Tc =T1
c =H+PS+DIFS+PD
H =HPHY +HMAC
, (13)
1699
8. 4
where HPHY and HMAC are the packet headers for physical and
MAC layers, PS is the packet size in transmission time, which
is assumed to be fixed in this paper, PD is the propagation
delay, SIFS is the length of a short interframe space, DIFS
is the length of a distributed interframe space, ACK is the
length of an acknowledgment. Recall that these parameters
are measured in units of bits or μs due to bit rate = 1 Mbps.
Based on these quantities, we have
T (τ, W) =
T − τ − TR
¯Tsd
PsPtPS
T
, (14)
where TR = Ntr+tb, tr is the report time from each SU to the
AP, tb the broadcast time from the AP to all SUs. Recall that
τ = maxi τi
is the total the sensing time. . denotes the floor
function and recall that T is the duration of a cycle. Note that
T −τ−TR
¯Tsd
denotes the average number of generic slot times
in one particular cycle excluding the sensing and reporting
phase. Here, we omit the length of the synchronization phase,
which is assumed to be negligible.
B. Cooperative Sensing and Access Optimization
We discuss optimization of cooperative sensing and access
parameters to maximize the normalized throughput under
sensing constraints for PUs. In particular, the throughput
maximization problem can be stated as follows:
max
τij ,W
NT (τ, W) (15)
s.t. Pj
d εj
, τj
, aj ≥ Pj
d, j ∈ [1, M] (16)
0 τij
≤ T, 0 W ≤ Wmax, (17)
where Pj
d is the detection probability for channel j at the AP,
Wmax is the maximum contention window and recall that T
is the cycle interval.
Algorithm 1 SENSING AND ACCESS OPTIMIZATION
1: Assume we have the sets of all SU i, {Si}. Initialize τij
,
j ∈ Si.
2: For each integer value of W ∈ [1, Wmax], find ¯τij
as
3: for i = 1 to N do
4: Fix all τi1j
, i1 = i.
5: Find optimal ¯τij
as ¯τij
= argmax
0τij ≤T
NT τij
, W .
6: end for
7: The final solution ¯W, ¯τij
is determined as ¯W, ¯τij
=
argmax
W,¯τij
NT ¯τij
, W .
We propose a low-complexity algorithm (Alg. 1) to find an
efficient solution for the optimization problem (15, 16, 17).
In particular, for each potential value of W ∈ [1, Wmax], we
search for the best τij
to maximize the total throughput. This is
done by a sequential search technique. Then, the final solution
is determined by the best combination of τij
, W for different
values of W. Numerical results reveal that Alg. 1 can always
find the optimal solution of the underlying problem.
C. Channel Assignment for Throughput Maximization
So far we have assumed a fixed channel assignment based
on which SUs perform sensing. In this section, we attempt to
determine an efficient channel assignment solution by solving
the following problem
max
{Si}
NT ¯τij
, ¯W, {Si} (18)
Algorithm 2 CHANNEL ASSIGNMENT ALGORITHM
1: Run Alg. 1 for temporary assignments Si = S, i ∈ [1, N]
to get ¯W, ¯τij
. Employ Hungarian algorithm [14] to
determine the first channel assignment for each SU so
that each channel is assigned to exactly one SU where the
cost of assigning channel j to SU i is ¯τij
. This results in
initial channel assignment sets {Si} for different SU i.
2: continue := 1, k := 1.
3: while continue = 1 do
4: Calculate the normalized throughput with optimized
parameter setting by using Alg. 1 as NT th =
NT ¯τij
, ¯W, Si .
5: Each SU i calculates the increase of throughput if it
is assigned one further potential channel j as ΔTij =
NT ¯τij
, ¯W, S1
i − NT th where S1
i = Si ∪ j and
¯τij
, ¯W are determined by using Alg. 1 for assignment
sets S1
i and Sl, l = i.
6: Find the “best” assignment (¯i, ¯j) as (¯i, ¯j) =
argmax
i,j∈SSi
ΔTij.
7: if ΔT¯i¯j δ then
8: Assign channel ¯j to SU ¯i (Si = S1
i ).
9: k = k + 1.
10: else
11: continue := 0
12: end if
13: end while
14: if k 1 then
15: Return to step 2.
16: else
17: STOP Alg.
18: end if
1) Brute-force Search Algorithm: Since the possible num-
ber of channel assignments is finite, we can employ the brute-
force search to determine the optimal channel assignment
solution and its protocol parameters. This can be done by
determining the best configuration parameters under each
channel assignment (i.e., using Alg. 1) then comparing the
throughput achieved by different channel assignments to find
the best one.
We now quantify the complexity of this optimal brute-force
search algorithm. The number of possible assignments is equal
to the following: How many ways are there to fill 1/0 to the
elements of an NxM matrix. It can verify that the number
of ways is 2MN
. Therefore, the complexity of the optimal
brute-force search algorithm is O 2MN
. Moreover, for each
case, we must run Alg. 1 to determine the sensing and access
parameters.
1700
9. 5
2) Low-complexity Algorithm: We propose a low-
complexity algorithm to find an efficient channel assignment
solution, which is described in Alg. 2. In step 1, we run
Hungarian algorithm to perform the first channel assignment
for each SU i. The complexity of this operation can be
upper-bounded by O M2
N (see [14] for more details). In
each assignment in the loop (i.e., Steps 2-13), each SU i
calculates the increases of throughput due to different potential
channel assignments, and selects the one resulting in the
maximum increase. Hence, the complexity involved in these
assignments is upper-bounded by MN since there are at most
M channels to choose for each of N SUs. Also, the number of
assignments to perform is upper bounded by MN. Therefore,
the complexity of this loop is upper-bounded by M2
N2
.
Suppose we run these assignments for r times before the
algorithm terminates. Therefore, the complexity of Alg. 2 can
be upper-bounded by O M2
N + rM2
N2
= O rM2
N2
,
which is much lower than that of the brute-force search
algorithm.
IV. NUMERICAL RESULTS
To obtain numerical results, we take key parameters for
the MAC protocols from Table II in [13]. Other parameters
are chosen as follows: cycle time is T = 100ms; mini-
slot (i.e., generic empty slot time) is σ = 20μs; sampling
frequency for spectrum sensing is fs = 6MHz; bandwidth
of PUs’ QPSK signals is 6MHz; tr = 80μs and tb = 80μs.
The target detection probabilities for channel j Pj
d in (16)
are chosen randomly in the intervals [0.95, 0.99]. In order to
calculate E in (6)-(7), we need to determine Pj
f for different
j, which can be done as follows. We set the equality for (16),
i.e., Pj
d εj
, τj
, aj = Pj
d (see [2] for detailed explanation)
and assume that detection probabilities Pij
d = Pj∗
d are equal
to each other from which we can calculate Pj∗
d by using
(3). Then, we can determine Pj
f by using (4) and (2). The
signal-to-noise ratio of PU signals at SUs γij
= SNRij
p
are chosen randomly in the range [−15, −20]dB and the
maximum backoff stage is m0 = 3.
We first compare the throughput performance achieved by
the brute-force search and low-complexity algorithms (i.e.,
Alg. 2) for channel assignment. In particular, in Table I
we show the normalized throughput NT versus probabilities
Pj (H0) for these two algorithms. Here, the probabilities
Pj (H0) for different channels j are chosen to be the same
and we choose M = 4 channels and N = 4 SUs. This
figure confirms that the throughput gaps between our greedy
algorithm and the brute-force optimal search algorithm are
quite small, which is about 1% in all cases. These results
confirm that our proposed greedy algorithm works well for
small systems (i.e., small M and N).
We now investigate the performance of our proposed algo-
rithm for larger systems. In Figs. 3, 4, 5, and 6, we consider
the network setting with N = 10 and M = 4. We divide SUs
into 2 groups where SUs have received SNRs due to PU i’s
signal equal to γij
= −15dB and γij
= −10dB in the two
groups, respectively. We use a combination {i, j} to represent
10
−3
10
−2
10
2
10
4
0.4
0.5
0.6
0.7
0.8
Sensing time (τ43
)Contention
window (W)
Throughput(NT)
0.45
0.5
0.55
0.6
0.65
0.7
N T opt(0.0037, 254) = 0.7389
Fig. 3. Normalized throughput versus contention window W and sensing
time τ for m = 3, N = 10, M = 4.
−15 −14 −13 −12 −11 −10 −9 −8 −7 −6 −5
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
SNR (Δγ)
Throughput(T)
Majority rule
OR rule
AND rule
Fig. 4. Normalized throughput versus SNR shift Δγ for m = 3, N = 10,
M = 4 under 3 aggregation rules.
−15 −10 −5 0
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
SNR (Δγ)
Throughput(NT)
Majority rule − OPT
1% T − Non−OPT
2% T − Non−OPT
5% T − Non−OPT
10% T − Non−OPT
Fig. 5. Normalized throughput versus SNR shift Δγ for m = 3, N = 10,
M = 4 for optimized and non-optimized scenarios.
−15 −10 −5 0
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
SNR (Δγ)
Throughput(T)
Majority rule − OPT
Case 1
Case 2
Case 3
Fig. 6. Normalized throughput versus SNR shift Δγ for m = 3, N = 10,
M = 4 for optimized and RR channel assignments.
the scenario where channel j is assigned to and sensed by
SU i. The following combinations are set corresponding to
γij
= −10dB: channel 1: {1, 1} , {2, 1} , {3, 1}; channel 2:
{2, 2} , {4, 2} , {5, 2}; channel 3: {4, 3} , {6, 3} , {7, 3}; and
channel 4: {1, 4} , {3, 4} , {6, 4} , {8, 4} , {9, 4} , {10, 4}. The
remaining combinations correspond to the SINR value γij
=
−15dB. To obtain results for different values of SNRs, we
shift both SNRs (-10dB and -15dB) by Δγ. For example, when
Δγ = −10, the resulting SNR values are γij
= −25dB and
1701
10. 6
TABLE I
THROUGHPUT VS PROBABILITY Pj (H0) (MXN=4X4)
Pj (H0)
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Greedy 0.0838 0.1677 0.2515 0.3353 0.4191 0.5030 0.5868 0.6707 0.7545 0.8383
NT Optimal 0.0846 0.1692 0.2544 0.3384 0.4239 0.5082 0.5935 0.6769 0.7623 0.8479
Gap (%) 1.0090 0.9187 1.1293 0.9142 1.1294 1.0261 1.1266 0.9159 1.0261 1.1266
TABLE II
ROUND-ROBIN CHANNEL ASSIGNMENT (X DENOTES AN ASSIGNMENT)
1
2
3
4
5
6
7
8
9
10
Case 1
1 2 3 4
x
x
x
x
x
x
x
x
x
x
Case 2
1 2 3 4
x x
x x
x x
x
x x
x x
x x
x
x x
x x
Case 3
1 2 3 4
x x x
x x x
x x
x
x x x
x x x
x x
x
x x x
x x x
γij
= −20dB.
Fig. 3 presents the normalized throughput NT versus con-
tention window W and sensing time τij
for the combination
{4, 3} and Δγ = −5 (the parameters of other combinations
are set at optimal values). Therefore, this figure shows the
normalized throughput NT versus W and only τ43
. We show
the optimal configuration ¯τ43
, ¯W , which maximizes the
normalized throughput NT of the proposed MAC protocol.
It can be observed that the normalized throughput NT is
less sensitive to the contention window W while it decreases
significantly as the sensing time τ43
deviates from the optimal
value.
In Fig. 4, we compare the throughput performance as the
AP employs there different aggregation rules, namely AND,
OR, and Majority rules. The three throughput curves in this
figure represent the optimized normalized throughputs (i.e., by
using Algs. 1 and 2). It can be seen that The Majority rule
achieves the highest throughput among the three. In Fig. 5, we
compare the throughput performances under the optimized and
the non-optimized scenarios. For the non-optimized scenario,
we also employ Alg. 2 for channel assignment; however we
do not use Alg.1 to choose optimal sensing/access parameters.
Instead, τij
is chosen from the following values: 1%T, 2%T,
5%T and 10%T, where T is the cycle time. Again, the
optimized normalized throughput is higher than that due to
non-optimized scenarios. Finally, Fig. 6 demonstrates the
relative throughput performance of our proposed algorithm and
the round-robin (RR) channel assignment strategies. For RR
channel assignments, we allocate channels for users, which
is described in Table II. For all RR channel assignments, we
employ Alg. 1 to determine optimal sensing/access parameters.
Again, the optimized design achieve much higher throughput
than those due to RR channel assignments.
V. CONCLUSION
We propose a general analytical framework for coopera-
tive sensing and access design and optimization in cognitive
radio networks. We analyze the throughput performance of
the proposed design, and develop an algorithm to find its
sensing/access parameters. Moreover, we present both optimal
brute-force search and low-complexity algorithms to determine
efficient channel assignments. Then, we analyze the com-
plexity of different algorithms and evaluate their throughput
performance via numerical studies.
REFERENCES
[1] C. Cormiob and K. R. Chowdhurya, “A survey on MAC protocols for
cognitive radio networks,” Elsevier Ad Hoc Networks, vol. 7, no. 7, pp.
1315-1329, Sept. 2009.
[2] L. T. Tan and L. B. Le, “Distributed mac protocol for cognitive radio
networks: Design, analysis, and optimization,” IEEE Transactions on
Vehicular Technology, vol.60, no.8, pp. 3990-4003, 2011.
[3] L. T. Tan and L. B. Le, “Channel assignment with access contention
resolution for cognitive radio networks,” IEEE Transactions on Vehicular
Technology, vol.61, no.6, pp. 2808-2823, 2012.
[4] Y.-C. Liang, Y. Zeng, E. C. Y. Peh, and A. T. Hoang, “Sensing-
throughput tradeoff for cognitive radio networks”, IEEE Trans. Wireless
Commun., vol. 7, no. 4, pp. 1326-1337, April 2008.
[5] G. Ganesan and Y. Li, “Cooperative spectrum sensing in cognitive radio.
Part I: Two user networks,” IEEE Trans. Wireless Commun., vol. 6, no.
6, pp. 22042213, Jun. 2007
[6] Z. Quan, S. Cui, and A. H. Sayed, “Optimal linear cooperation for
spectrum sensing in cognitive radio networks,” IEEE J. Sel. Topics Signal
Process., vol. 2, no. 1, pp. 2840, Feb. 2008.
[7] E. C. Y. Peh, Y.-C. Liang and Y. L. Guan, “Optimization of cooperative
sensing in cognitive radio networks: A sensing-throughput tradeoff
view,” in Proc. IEEE International Conf. Commun., pp. 3521–3525,
2009.
[8] Y. Wei, H. Leung, C. Wenqing and C. Siyue, “Optimizing voting rule
for cooperative spectrum sensing through learning automata,” IEEE
Transactions on Vehicular Technology, vol.60, no.7, pp. 3253–3264,
2011.
[9] Z. Wei, R. Mallik and K. Letaief, “Optimization of cooperative spectrum
sensing with energy detection in cognitive radio networks,” IEEE
Transactions on Wireless Communications, vol.8, no.12, pp. 5761–5766,
2009.
[10] K. Seung-Jun, and G. B. Giannakis, “Sequential and cooperative sens-
ing for multi-channel cognitive radios,” IEEE Transactions on Signal
Processing, vol. 58, no. 8, pp. 4239–4253, 2010.
[11] J. Park, P. Pawelczak and D. Cabric, “Performance of joint spectrum
sensing and mac algorithms for multichannel opportunistic spectrum
access ad hoc networks,” IEEE Transactions on Mobile Computing,
vol.10, no.7, pp. 1011-1027, 2011.
[12] Y.R. Kondareddy, and P. Agrawal, “Synchronized MAC protocol for
multi-hop cognitive radio networks,” in Proc. IEEE ICC’2008.
[13] G. Bianchi, “Performance analysis of the IEEE 802.11 distributed
coordination function,” IEEE J. Sel. Areas Commun., vol. 18, no. 3,
pp. 535–547, Mar. 2000.
[14] H.W. Kuhn, “The Hungarian method for the assignment problem,” Naval
Research Logistic Quarterly, 2 (1955), pp. 83–97, 1955.
1702