The massively increasing number of wireless communication devices has led to considerable growths in
radio traffic density, resulting in a predictable shortage of the available spectrum. To address this potential
shortage, the Cognitive Radio (CR) technology offers promising solutions that aim to improve the spectrum
utilization. The operation of CR relies on detecting the so-called spectrum holes, i.e., the frequency bands
when they are unoccupied by their licensed operators. The unlicensed users are then allowed to
communicate using these spectrum holes. Consequently, the performance of CR is highly dependent on the
employed spectrum sensing methods. Several sensing methods are already available or literarily proposed.
However, no individual method can accommodate all possible CR operation scenarios. Hence, it is fair to
ascertain that the performance of a CR device can be improved if it is capable of supporting several
sensing methods. Then it should be able to effectively select the most suitable method. In this paper, several
spectrum sensing methods are compared and analyzed, aiming to identify their advantages and
shortcomings in different CR operating conditions. Furthermore, it identifies the factors that need to be
considered while selecting a proper sensing method from the catalog of available methods.
IRJET- Cooperative Spectrum Sensing based on Adaptive Threshold for Cognitive...IRJET Journal
This document discusses cooperative spectrum sensing based on an adaptive threshold for cognitive radio. It begins with an introduction to cognitive radio and spectrum sensing. It then discusses energy detection, the most common spectrum sensing method due to its low complexity. However, energy detection may not perform well in low signal-to-noise ratio environments. To address this, an adaptive threshold is proposed that varies based on the received primary user signal's SNR. The document also discusses cooperative spectrum sensing, where multiple cognitive radios sense the spectrum individually and share their decisions with a fusion center. The fusion center combines the decisions to make an overall determination with better performance than non-cooperative sensing. Simulation results showed that an adaptive threshold combined with cooperative spectrum sensing provides better detection
A comprehensive study of signal detection techniques for spectrum sensing in ...IAEME Publication
This document summarizes several signal detection techniques for spectrum sensing in cognitive radio systems. It begins with an introduction to cognitive radio and spectrum sensing. It then describes and compares three main non-cooperative (transmitter-based) detection techniques: matched filter detection, energy detection, and cyclostationary feature detection. Matched filter detection provides optimal detection but requires prior knowledge of the primary user's signal. Energy detection has lower complexity but cannot differentiate signals from noise. Cyclostationary feature detection can detect periodic signals but has higher complexity than energy detection.
Comparative Study of Different Non-Cooperative Techniques in Cognitive RadioRSIS International
Wireless technology is expanding its domain and with it
is growing the need for more frequencies for communication.
Cognitive radio offers a solution to this problem by using the
concept of Dynamic spectrum access instead of fixed spectrum
allocation. Such radios are capable of sensing the RF spectrum
for identifying idle frequency bands. It then transmits
opportunistically so as to avoid interference with primary user
over same band. In cognitive radio, intelligent spectrum sensing
forms the major and most important part. Out of the various
sensing techniques, we will give an overview of some of the
prominent non-cooperative techniques. The paper deals with
comparative study of these methods.
Heterogeneous Spectrum Sensing in Cognitive Radio Network using Traditional E...IJEACS
The accurate spectrum sensing is a predominant
aspect of any competent CR system. Efficient spectrum sensing
enables a CR terminal to detect the spectrum holes (underutilized
spectral bands) by providing high spectral resolution, thereby
accrediting opportunistic transmission in the licensed band to the
CR. In order to facilitate a good spectrum management and its
efficient use a hybrid method for the detection of the spectrum
with the purpose of detecting the presence of bands of
unoccupied frequencies is proposed. The method used are
traditional energy detection and matched filter with changing
number of secondary users using each technique and finally a
centralized cooperative spectrum sensing network which employs
hard combination at the fusion centre.
Spectrum Sensing in Cognitive Radio Networks : QoS Considerations csandit
This document discusses spectrum sensing methods in cognitive radio networks and their impact on quality of service (QoS). It analyzes several spectrum sensing methods including energy detection, covariance-based detection, cyclostationarity feature detection, correlation detection, radio identification based sensing, and matched filtering. These methods are categorized as requiring no prior information, requiring prior information, or being based on cooperation between secondary users. The document notes that imperfect spectrum sensing can degrade QoS for both primary and secondary users. It also discusses how increasing sensing time and frequency improves detection of primary users but reduces data transmission time and degrades QoS for secondary users.
A SURVEY ON DYNAMIC SPECTRUM ACCESS TECHNIQUES FOR COGNITIVE RADIOijngnjournal
Cognitive radio (CR) is a new paradigm that utilizes the available spectrum band. The key characteristic of CR system is to sense the electromagnetic environment to adapt their operation and dynamically vary its radio operating parameters. The technique of dynamically accessing the unused spectrum band is known as Dynamic Spectrum Access (DSA). The dynamic spectrum access technology helps to minimize unused spectrum bands. In this paper, main functions of Cognitive Radio (CR) i.e. spectrum sensing, spectrum management, spectrum mobility and spectrum sharing are discussed. Then DSA models are discussed along with different methods of DSA such as Command and Control, Exclusive-Use, Shared Use of Primary Licensed User and Commons method. Game-theoretic approach using Bertrand game model, Markovian Queuing Model for spectrum allocation in centralized architecture and Fuzzy logic based method are also discussed and result are shown.
IRJET- Dynamic Spectrum Sensing using Matched Filter Method and MATLAB Simula...IRJET Journal
The document discusses spectrum sensing techniques for cognitive radio networks, focusing on the matched filter method. It explains that the matched filter is the optimal detection method when the primary user's signal is known, as it maximizes the signal-to-noise ratio. The paper also presents the process of implementing matched filter detection to identify spectrum holes and determine whether a primary user is present or absent based on comparing the matched filter output to a predetermined threshold.
An Approach to Spectrum Sensing in Cognitive Radio IOSR Journals
Recent research shows that more than 70% of the available spectrum is not utilized
efficiently. The bandwidth becomes expensive due to a shortage of frequencies. Therefore for efficient
utilization of spectrum, we need to sniff the spectrum to determine whether it is being used by primary user or
not. The term cognitive radio refers to the adoption of radio parameters using the sensed information
of the spectrum. There are various spectrum sensing techniques proposed in the literature but still there is
room for researchers in this field to explore more sophisticated approaches. There are three major
categories of spectrum sensing techniques; transmitter detection, receiver detection and interference
temperature detection. This thesis presents a survey of techniques suggested in the literature for
spectrum sensing with a performance analysis of transmitter-based detection techniques.
IRJET- Cooperative Spectrum Sensing based on Adaptive Threshold for Cognitive...IRJET Journal
This document discusses cooperative spectrum sensing based on an adaptive threshold for cognitive radio. It begins with an introduction to cognitive radio and spectrum sensing. It then discusses energy detection, the most common spectrum sensing method due to its low complexity. However, energy detection may not perform well in low signal-to-noise ratio environments. To address this, an adaptive threshold is proposed that varies based on the received primary user signal's SNR. The document also discusses cooperative spectrum sensing, where multiple cognitive radios sense the spectrum individually and share their decisions with a fusion center. The fusion center combines the decisions to make an overall determination with better performance than non-cooperative sensing. Simulation results showed that an adaptive threshold combined with cooperative spectrum sensing provides better detection
A comprehensive study of signal detection techniques for spectrum sensing in ...IAEME Publication
This document summarizes several signal detection techniques for spectrum sensing in cognitive radio systems. It begins with an introduction to cognitive radio and spectrum sensing. It then describes and compares three main non-cooperative (transmitter-based) detection techniques: matched filter detection, energy detection, and cyclostationary feature detection. Matched filter detection provides optimal detection but requires prior knowledge of the primary user's signal. Energy detection has lower complexity but cannot differentiate signals from noise. Cyclostationary feature detection can detect periodic signals but has higher complexity than energy detection.
Comparative Study of Different Non-Cooperative Techniques in Cognitive RadioRSIS International
Wireless technology is expanding its domain and with it
is growing the need for more frequencies for communication.
Cognitive radio offers a solution to this problem by using the
concept of Dynamic spectrum access instead of fixed spectrum
allocation. Such radios are capable of sensing the RF spectrum
for identifying idle frequency bands. It then transmits
opportunistically so as to avoid interference with primary user
over same band. In cognitive radio, intelligent spectrum sensing
forms the major and most important part. Out of the various
sensing techniques, we will give an overview of some of the
prominent non-cooperative techniques. The paper deals with
comparative study of these methods.
Heterogeneous Spectrum Sensing in Cognitive Radio Network using Traditional E...IJEACS
The accurate spectrum sensing is a predominant
aspect of any competent CR system. Efficient spectrum sensing
enables a CR terminal to detect the spectrum holes (underutilized
spectral bands) by providing high spectral resolution, thereby
accrediting opportunistic transmission in the licensed band to the
CR. In order to facilitate a good spectrum management and its
efficient use a hybrid method for the detection of the spectrum
with the purpose of detecting the presence of bands of
unoccupied frequencies is proposed. The method used are
traditional energy detection and matched filter with changing
number of secondary users using each technique and finally a
centralized cooperative spectrum sensing network which employs
hard combination at the fusion centre.
Spectrum Sensing in Cognitive Radio Networks : QoS Considerations csandit
This document discusses spectrum sensing methods in cognitive radio networks and their impact on quality of service (QoS). It analyzes several spectrum sensing methods including energy detection, covariance-based detection, cyclostationarity feature detection, correlation detection, radio identification based sensing, and matched filtering. These methods are categorized as requiring no prior information, requiring prior information, or being based on cooperation between secondary users. The document notes that imperfect spectrum sensing can degrade QoS for both primary and secondary users. It also discusses how increasing sensing time and frequency improves detection of primary users but reduces data transmission time and degrades QoS for secondary users.
A SURVEY ON DYNAMIC SPECTRUM ACCESS TECHNIQUES FOR COGNITIVE RADIOijngnjournal
Cognitive radio (CR) is a new paradigm that utilizes the available spectrum band. The key characteristic of CR system is to sense the electromagnetic environment to adapt their operation and dynamically vary its radio operating parameters. The technique of dynamically accessing the unused spectrum band is known as Dynamic Spectrum Access (DSA). The dynamic spectrum access technology helps to minimize unused spectrum bands. In this paper, main functions of Cognitive Radio (CR) i.e. spectrum sensing, spectrum management, spectrum mobility and spectrum sharing are discussed. Then DSA models are discussed along with different methods of DSA such as Command and Control, Exclusive-Use, Shared Use of Primary Licensed User and Commons method. Game-theoretic approach using Bertrand game model, Markovian Queuing Model for spectrum allocation in centralized architecture and Fuzzy logic based method are also discussed and result are shown.
IRJET- Dynamic Spectrum Sensing using Matched Filter Method and MATLAB Simula...IRJET Journal
The document discusses spectrum sensing techniques for cognitive radio networks, focusing on the matched filter method. It explains that the matched filter is the optimal detection method when the primary user's signal is known, as it maximizes the signal-to-noise ratio. The paper also presents the process of implementing matched filter detection to identify spectrum holes and determine whether a primary user is present or absent based on comparing the matched filter output to a predetermined threshold.
An Approach to Spectrum Sensing in Cognitive Radio IOSR Journals
Recent research shows that more than 70% of the available spectrum is not utilized
efficiently. The bandwidth becomes expensive due to a shortage of frequencies. Therefore for efficient
utilization of spectrum, we need to sniff the spectrum to determine whether it is being used by primary user or
not. The term cognitive radio refers to the adoption of radio parameters using the sensed information
of the spectrum. There are various spectrum sensing techniques proposed in the literature but still there is
room for researchers in this field to explore more sophisticated approaches. There are three major
categories of spectrum sensing techniques; transmitter detection, receiver detection and interference
temperature detection. This thesis presents a survey of techniques suggested in the literature for
spectrum sensing with a performance analysis of transmitter-based detection techniques.
This document discusses cooperative spectrum sensing in cognitive radio networks to improve energy efficiency and throughput. It proposes deriving the optimal number of cooperating cognitive radios under two scenarios: 1) minimizing radios needed for a given detection performance to maximize energy efficiency, and 2) maximizing throughput by optimizing the reporting time given a detection constraint. Computer simulations show that an OR fusion rule outperforms AND in both scenarios using fewer radios.
SPECTRUM SENSING STRATEGY TO ENHANCE THE QOS IN WHITE-FI NETWORKSIJCNC Journal
The rapidly growing number of wireless devices running applications that require high bandwidths, has
resulted in increasing demands for the unlicensed frequency spectrum. Given the scarcity of allocated
unlicensed frequencies, meeting such demands can become a serious concern. Cognitive Radio (CR)
technology opens the door for the opportunistic use of the licensed spectrum to partially address the issues
relevant to the limited availability of unlicensed frequencies. Combining CR and Wi-Fi to form the socalled
White-Fi networks, has been proposed for achieving higher spectrum utilization. This article
discusses the spectrum sensing in White-Fi networks and the impacts that it has on the QoS of typical
applications. It also reports the analysis of such impacts through various simulation studies. Our results
demonstrate the advantages of an adaptive sensing strategy that is capable of changing the related
parameters based on QoS requirements. We also propose such a sensing strategy that can adapt to the
IEEE 802.11e requirements. The goal of the proposed strategy is the enhancement of the overall QoS of the
applications while maintaining efficient sensing of the spectrum. Simulation results of the scenarios that
implement the proposed mechanisms demonstrate noticeable QoS improvements compared to cases where
common sensing methods are utilized in IEEE802.11 networks.
Simulation and analysis of cognitive radioijngnjournal
The increasing demand of wireless applications has put a lot of limitations on the use of available
radio spectrum is limited and precious resource. Many survey of spectrum utilization shows that entire
spectrum is not used at all the times, so many of the radio spectrum is underutilized. Some of the frequency
bands in the spectrum are unoccupied, some of the frequency bands less occupied and few bands are over
utilized. Cognitive radio system is a technique which overcomes that spectrum underutilization. Cognitive
radio is a technique where secondary user looks for a free band to use when primary user is not in use of
its licensed band. A function of cognitive radio is called Spectrum sensing which enables to search for the
free bands and it helps to detect the spectrum hole (frequency band which is free enough to be used) which
can be utilized by secondary user with high spectral resolution capability. The idea of simulation and
analysis of Cognitive Radio System to reuse unused spectrum to increase the total system capacity was
brought in this paper and this work digs into the practical implementation of a Cognitive radio system.
MATLAB R2007b (version7.5) has been used to test the performance of Cognitive radio dynamically.
Collaborative cyclostationary spectrum sensing for cognitive radio systemskareenavolt
This article proposes an energy efficient collaborative cyclostationary spectrum sensing approach for cognitive radio systems. It extends an existing statistical hypothesis test for cyclostationarity to multiple cyclic frequencies and establishes its asymptotic distributions. It proposes collaborative test statistics to fuse local test statistics from secondary users, and a censoring technique where only informative test statistics are transmitted to reduce energy use. It also proposes a method to numerically approximate the asymptotic distribution of the censored test statistic. Simulations show the benefits of the proposed cyclostationary approach over energy detection, the importance of collaboration for overcoming fading, and the reliable performance even in very low SNR regimes under communication constraints.
A novel scheme to improve the spectrum sensing performanceIJCNCJournal
Due to limited availability of spectrum for license
d users only, the need for secondary access by unli
censed
users is increasing. Cognitive radio turns out to b
e helping this situation because all that is needed
is a
technique that could efficiently detect the empty s
paces and provide them to the secondary devices wit
hout
causing any interference to the primary (licensed)
users. Spectrum sensing is the foremost function of
the
cognitive radio which senses the environment for wh
ite spaces. Energy detection is one of the various
spectrum sensing techniques that are under research
. Earlier it was shown that energy detection works
better under AWGN channel as compared to Rayleigh c
hannel, however the conventional spectrum sensing
techniques have a high probability of false alarm a
nd also show a better probability of detection for
higher
values of SNR. There is a need for a new technique
that shows a reduced probability of false alarm as
well
as an increase in the probability of detection for
lower values of SNR. In the present work the conven
tional
energy detection technique has been enhanced to get
better results.
This presentation discusses cooperative sensing in cognitive radios. It defines cognitive radio and explains that cognitive radios use techniques like spectrum sensing and learning to access licensed spectrum when it is not in use. The document discusses different types of spectrum including licensed and unlicensed bands. It then covers the key aspects of cooperative sensing including centralized, distributed, and relay-assisted sensing approaches as well as issues like probability of detection, false alarms, and accurate detection. The elements and benefits of cognitive radio are also summarized.
Spectrum sensing performance of cognitive radio under awgn and fading channel...eSAT Journals
Abstract Accurate sensing of the spectrum occupancy is essential for successful implementation of cognitive radio networks. However, due to higher levels of noise and multipath propagation effects of the channel, the sensing information of cognitive radio may not be accurate all the times. In this context, Receiver Operating Characteristics (ROC) of the system gives a measure of this information. It is a curve of probability of true detection with respect to probability of false detection. This paper presents the ROC of cognitive radio system for AWGN, Rayleigh and Rician channels. Keywords: Cognitive Radio, Spectrum Sensing, Primary User Detection, AWGN Channel, Rayleigh and Rician Channels
A Mathematical Approach for Hidden Node Problem in Cognitive Radio NetworksTELKOMNIKA JOURNAL
Cognitive radio (CR) technology has emerged as a realistic solution to the spectrum scarcity
problem in present day wireless networks. A major challenge in CR radio networks is the hidden node
problem, which is the inability of the CR nodes to detect the primary user. This paper proposes energy
detector-based distributed sequential cooperative spectrum sensing over Nakagami-m fading, as a tool to
solve the hidden node problem. The derivation of energy detection performance over Nakagami-m fading
channel is presented. Since the observation represents a random variable, likelihood ratio test (LRT) is
known to be optimal in this type of detection problem. The LRT is implemented using the Neyman-Pearson
Criterion (maximizing the probability of detection but at a constraint of false alarm probability). The
performance of the proposed method has been evaluated both by numerical analysis and simulations. The
effect of cooperation among a group of CR nodes and system parameters such as SNR, detection
threshold and number of samples per CR nodes is investigated. Results show improved detection
performance by implementing the proposed model.
A SURVEY ON DYNAMIC SPECTRUM ACCESS TECHNIQUES IN COGNITIVE RADIOijngnjournal
Wireless networks are characterized by fixed spectrum policy. With increasing demands for wireless communication efficiently using the spectrum resources has become an essential issue. Cognitive radio is a form of wireless communication which is used to sense the spectrum and find the free spectrum. It is used by unlicensed users without causing interference to the licensed user. Cognitive radio with the dynamic spectrum access is key technology which provides the best solution by allowing a group of Secondary users to share the radio spectrum originally allocated to the primary users. Dynamically accessing the unused spectrum is known as dynamic spectrum access (DSA) which becomes a promising approach to increase
the efficiency of spectrum usage. In this paper, DSA models are discussed along with different methods such as game theory based method, a measurement-based model, network coded cognitive control channel, Markovian Queuing model, the Delay performance of threshold policies, fuzzy logic based method and spatio-temporal spectrum management model.
Spectrum Sensing using Cooperative Energy Detection Method for Cognitive RadioSaroj Dhakal
This document summarizes cooperative spectrum sensing using energy detection in cognitive radio networks. It discusses how cooperative sensing can improve detection performance by exploiting spatial diversity among cognitive radio users. The key points are:
1. Cooperative sensing allows cognitive radio users to share sensing information to make a combined decision that is more accurate than individual decisions. This mitigates issues like multipath fading and shadowing.
2. Energy detection is commonly used for cooperative sensing due to its simplicity. However, its performance depends on noise power uncertainty. Cooperative sensing addresses this by fusing observations from multiple spatially distributed users.
3. The document also discusses challenges in spectrum sensing like hardware requirements, hidden primary users, and detecting spread spectrum
Performance Analysis of Bayesian Methods to for the Spectrum Utilization in C...ijtsrd
1) The document proposes using Bayesian detection methods to improve spectrum utilization in cognitive radio systems without prior knowledge of primary user signals.
2) It describes developing an optimal Bayesian detector for digitally modulated primary users and approximating suboptimal detectors for low and high SNR regimes.
3) Simulation results show the Bayesian detector and its approximation in high SNR achieve higher detection probability and lower false alarm probability than energy detection, improving secondary user throughput and spectrum utilization, especially at high SNR where energy detection is suboptimal.
Performance Analysis and Comparative Study of Cognitive Radio Spectrum Sensin...IOSR Journals
In cognitive radio, spectrum sensing is an emergent technology to find available and unused
spectrum for increasing spectrum utilization and to overcome spectrum scarcity problem without harmful
interference to licensed users. Cooperative spectrum sensing is used to give reliable performance in terms of
detection probability and false alarm probability as well as in order to reduce fading, noise and shadowing
effects on cognitive radio users. In this paper according to detection performance and complexity various
cooperative spectrum sensing schemes have been discussed. We have analyzed spectrum sensing with different fusion rules and their comparative behavior has also been studied. Furthermore, we introduced AND-OR fusion rules in 2-bit and 3-bit hard combination schemes
Cooperative tv spectrum sensing in cognitive radio BY DEEPAK PORIYADeepak Poriya
This document discusses cooperative spectrum sensing in cognitive radio networks for Wi-Fi. It describes the system model of a Wi-Fi zone with primary and secondary users. It analyzes single user and cooperative spectrum sensing using energy detection algorithms. Cooperative sensing can use OR, AND or K-out-of-N rules at a fusion center to determine primary user presence. The document derives the optimal number of secondary users for the K-out-of-N rule and numerically calculates the optimal sensing time to minimize detection error probability and maximize throughput.
Reactive Power Compensation in Single Phase Distribution System using SVC, ST...IRJET Journal
This document discusses and compares two spectrum sensing techniques for cognitive radio networks: energy detection and matched filter detection. It analyzes the performance of these techniques based on probability of detection and probability of false alarm under different signal-to-noise ratio levels and fading channel models (AWGN, flat fading, Rayleigh fading). The key findings are that matched filter detection has better performance than energy detection, but requires prior knowledge of the primary signal. Energy detection has lower complexity but performs poorly in low SNR scenarios. Overall, matched filter detection results in lower probability of false alarms compared to energy detection.
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OPTIMIZATION OF THE RECURSIVE ONE-SIDED HYPOTHESIS TESTING TECHNIQUE FOR AUTO...ijwmn
In this paper, an optimized Recursive One-Sided Hypothesis Testing (ROHT) threshold estimation algorithm for energy detection based on Cognitive Radio (CR) application is presented. The ROHT algorithm is well known to compute and correct threshold values based on the choice of the parameter
values; namely the coefficient of standard deviation (z-value) and the stopping criteria (). A fixed computational process has been employed in most cases to estimate these parameter values, thus rendering them non-adaptive under different sensing conditions. Also, this fixed (manual tuning) process requires prior knowledge of some noise level to enable pre-configuration of a predefined target false alarm rate.
This renders the parameter estimation process cumbrous and unworkable for real-time purposes, particularly for autonomous CR applications. Furthermore, using wrong parameter values may lead to either too high or too low false alarms or detection rates of the algorithm. Sequel to aforementioned mentioned constraints, we propose a new mechanism for instantaneous parameter optimization of the ROHT algorithm using Particle Swarm Optimization (PSO) algorithm. Our PSO-ROHT model design was extensively tested under different conditions and results were compared to the non-optimized ROHT. The
results obtained show that the proposed design effectively adapts the parameter values of the Recursive One-Sided Hypothesis Testing algorithm in accordance with the input dataset under consideration. Also, that the proposed optimized model outperforms its non-optimized counterpart following the estimated detection probability and false alarm probability of both schemes, particularly in detecting Orthogonal Frequency-Division Multiplexing signals. In detecting the Orthogonal Frequency-Division Multiplexing signals at signal-to-noise ratio of 3dB and above, the proposed model achieved a higher detection rate of 96.23% while maintaining a low false alarm rate below 10%, which complies with the IEEE 802.22standard for Cognitive Radio application. Our PSO-ROHT algorithm is shown to be highly effective for autonomous and full blind signal detection in CR, with strong potentials for application in other areas requiring automatic threshold estimation.
A COGNITIVE RADIO SCHEME FOR DYNAMIC RESOURCE ALLOCATION BASED ON QOEijwmn
This paper introduces a cognitive radio scheme based on quality of experience (QoE). QoE involves the
mobile end user’s preferences. Considering QoE can lead to an improved cognitive radio resource
management strategy. The cognitive radio scheme aims to manage the traffic flow in dynamic systems; it is
a new way of thinking about dynamic resource management in cellular systems. The Use of the cognitive
radio techniques in cellular systems will improve the resource assignment in wireless communication. The
cognitive radio is a self-aware communication system that aims to use the resource assignment in an
efficient way. The proposed algorithm is very successful at handling the call-blocking rate based on QoS
and QoE.
ROUTING PROTOCOLS FOR DELAY TOLERANT NETWORKS: SURVEY AND PERFORMANCE EVALUATIONijwmn
Delay Tolerant Networking (DTN) is a promising technology that aims to provide efficient communication
between devices in a network with no guaranteed continuous connectivity. Most existing routing schemes
for DTNs exploit the advantage of message replication to achieve high message delivery rate. However,
these schemes commonly suffer from large communication overhead due to the lack of efficient mechanisms
to control message replication. In this paper we give a brief survey on routing protocols designed for
DTNs, and evaluate the performance of several representative routing protocols including Epidemic, Spray
and Wait, PRoPHET, and 3R through extensive trace-driven simulations. Another objective of this work is
to evaluate the security strength of different routing schemes under common DTN attacks such as the black
hole attack. The results and analysis presented in this paper can provide useful guidance on the design and
selection of routing protocols for given delay-tolerant applications.
A novel energy efficient routing algorithm for wireless sensor networks using...ijwmn
There are numerous applications for wireless sensor networks which are inevitable now a day in our daily
life. Majority of such applications which use wireless sensor networks will be in areas where the direct
human intervention is impossible. So the limited energy available in such sensors is a threat for prolonging
the life of the entire network. The need of energy efficiency in wireless sensor networks is a hot research
topic in which lot of new strategies for improvement in energy efficiency has been sought after. As
communication process consumes more energy, an energy efficient routing strategy can probably reduce
the energy consumption to a great extend. This paper gives an overview of the different routing techniques
in which mobile sinks are used to facilitate the routing process which can effectively reduce the energy use.
A new routing strategy with mobile sinks and a static sink is proposed and is compared based on the
matrices life time and average energy of the nodes with the existing Shortest Hop path (SH) algorithm. The
simulation results shows the proposed algorithm is more energy efficient than the existing one.
This document summarizes the design and performance evaluation of a two-unit Yagi-Uda antenna array for UHF satellite communication. Simulations were conducted using 4NEC2 software to optimize the design for a gain of 18.6 dBi at 437.025 MHz. Field tests validated the antenna array achieved high gain and front-to-back ratio while maintaining low standing wave ratio across the UHF band. The two-unit circularly polarized crossed Yagi array design successfully improved communication link margins for small cube satellites operating with stringent power budgets.
DISCRETE COSINETRANSFORM-II FOR REDUCTION IN PEAK TO AVERAGE POWER RATIO OF O...ijwmn
Orthogonal frequency Division multiplexing (OFDM) is the most familiar word in telecommunication
and wireless communication systems as it provides enhanced spectral efficiency than Frequency division
multiplexing (FDM).Although it is sustaining an orthogonal relation betweencarriers but high peak to
average power ratio (PAPR) is one of the main disadvantages of OFDM system.Various PAPR reduction
techniques have been used, including techniques based on companding. Incompanding, -Law
companding has potential to reduce the PAPR of OFDMsignals. -Law Companding technique
preserves the dynamic range of samples at low amplitudes.A new method named as precoding which is
having less complexity compared to the other power reduction techniques is proposed to reduce PAPR.
This paper put forward combination of two existing techniques namely -Law Companding Transform
and Discrete Cosine Transform-II precoding technique. The simulation results show that, the proposed
combinedscheme gives better result for PAPR Reduction and results in no distortion.
EFFECTS OF FILTERS ON THE PERFORMANCE OF DVB-T RECEIVERijwmn
Digital Video Broadcasting-Terrestrial (DVB-T) is an international standard for digital television
services. Orthogonal Frequency Division Multiplexing (OFDM) is the core of this technology. OFDM
based system like DVB-T can handle multipath fading and hence it can minimize Inter Symbol
Interference (ISI). DVB-T has some limitations too namely large dynamic range of the signals and
sensitivity to frequency error. In order to overcome these limitations DVB-T receivers should be optimally
designed. In this paper we address the issues related to optimal DVB-T receiver design. There of several
signal processing units in a DVB-T receiver. A low-pass filter is one of them. In this paper, we consider
some classic filters namely Butterworth, Chebyshev, and elliptic in the DVB-T receiver. The effects of
different filters on the performances of DVB-T receiver have been investigated and compared in this
paper under AWGN channel condition
This document discusses cooperative spectrum sensing in cognitive radio networks to improve energy efficiency and throughput. It proposes deriving the optimal number of cooperating cognitive radios under two scenarios: 1) minimizing radios needed for a given detection performance to maximize energy efficiency, and 2) maximizing throughput by optimizing the reporting time given a detection constraint. Computer simulations show that an OR fusion rule outperforms AND in both scenarios using fewer radios.
SPECTRUM SENSING STRATEGY TO ENHANCE THE QOS IN WHITE-FI NETWORKSIJCNC Journal
The rapidly growing number of wireless devices running applications that require high bandwidths, has
resulted in increasing demands for the unlicensed frequency spectrum. Given the scarcity of allocated
unlicensed frequencies, meeting such demands can become a serious concern. Cognitive Radio (CR)
technology opens the door for the opportunistic use of the licensed spectrum to partially address the issues
relevant to the limited availability of unlicensed frequencies. Combining CR and Wi-Fi to form the socalled
White-Fi networks, has been proposed for achieving higher spectrum utilization. This article
discusses the spectrum sensing in White-Fi networks and the impacts that it has on the QoS of typical
applications. It also reports the analysis of such impacts through various simulation studies. Our results
demonstrate the advantages of an adaptive sensing strategy that is capable of changing the related
parameters based on QoS requirements. We also propose such a sensing strategy that can adapt to the
IEEE 802.11e requirements. The goal of the proposed strategy is the enhancement of the overall QoS of the
applications while maintaining efficient sensing of the spectrum. Simulation results of the scenarios that
implement the proposed mechanisms demonstrate noticeable QoS improvements compared to cases where
common sensing methods are utilized in IEEE802.11 networks.
Simulation and analysis of cognitive radioijngnjournal
The increasing demand of wireless applications has put a lot of limitations on the use of available
radio spectrum is limited and precious resource. Many survey of spectrum utilization shows that entire
spectrum is not used at all the times, so many of the radio spectrum is underutilized. Some of the frequency
bands in the spectrum are unoccupied, some of the frequency bands less occupied and few bands are over
utilized. Cognitive radio system is a technique which overcomes that spectrum underutilization. Cognitive
radio is a technique where secondary user looks for a free band to use when primary user is not in use of
its licensed band. A function of cognitive radio is called Spectrum sensing which enables to search for the
free bands and it helps to detect the spectrum hole (frequency band which is free enough to be used) which
can be utilized by secondary user with high spectral resolution capability. The idea of simulation and
analysis of Cognitive Radio System to reuse unused spectrum to increase the total system capacity was
brought in this paper and this work digs into the practical implementation of a Cognitive radio system.
MATLAB R2007b (version7.5) has been used to test the performance of Cognitive radio dynamically.
Collaborative cyclostationary spectrum sensing for cognitive radio systemskareenavolt
This article proposes an energy efficient collaborative cyclostationary spectrum sensing approach for cognitive radio systems. It extends an existing statistical hypothesis test for cyclostationarity to multiple cyclic frequencies and establishes its asymptotic distributions. It proposes collaborative test statistics to fuse local test statistics from secondary users, and a censoring technique where only informative test statistics are transmitted to reduce energy use. It also proposes a method to numerically approximate the asymptotic distribution of the censored test statistic. Simulations show the benefits of the proposed cyclostationary approach over energy detection, the importance of collaboration for overcoming fading, and the reliable performance even in very low SNR regimes under communication constraints.
A novel scheme to improve the spectrum sensing performanceIJCNCJournal
Due to limited availability of spectrum for license
d users only, the need for secondary access by unli
censed
users is increasing. Cognitive radio turns out to b
e helping this situation because all that is needed
is a
technique that could efficiently detect the empty s
paces and provide them to the secondary devices wit
hout
causing any interference to the primary (licensed)
users. Spectrum sensing is the foremost function of
the
cognitive radio which senses the environment for wh
ite spaces. Energy detection is one of the various
spectrum sensing techniques that are under research
. Earlier it was shown that energy detection works
better under AWGN channel as compared to Rayleigh c
hannel, however the conventional spectrum sensing
techniques have a high probability of false alarm a
nd also show a better probability of detection for
higher
values of SNR. There is a need for a new technique
that shows a reduced probability of false alarm as
well
as an increase in the probability of detection for
lower values of SNR. In the present work the conven
tional
energy detection technique has been enhanced to get
better results.
This presentation discusses cooperative sensing in cognitive radios. It defines cognitive radio and explains that cognitive radios use techniques like spectrum sensing and learning to access licensed spectrum when it is not in use. The document discusses different types of spectrum including licensed and unlicensed bands. It then covers the key aspects of cooperative sensing including centralized, distributed, and relay-assisted sensing approaches as well as issues like probability of detection, false alarms, and accurate detection. The elements and benefits of cognitive radio are also summarized.
Spectrum sensing performance of cognitive radio under awgn and fading channel...eSAT Journals
Abstract Accurate sensing of the spectrum occupancy is essential for successful implementation of cognitive radio networks. However, due to higher levels of noise and multipath propagation effects of the channel, the sensing information of cognitive radio may not be accurate all the times. In this context, Receiver Operating Characteristics (ROC) of the system gives a measure of this information. It is a curve of probability of true detection with respect to probability of false detection. This paper presents the ROC of cognitive radio system for AWGN, Rayleigh and Rician channels. Keywords: Cognitive Radio, Spectrum Sensing, Primary User Detection, AWGN Channel, Rayleigh and Rician Channels
A Mathematical Approach for Hidden Node Problem in Cognitive Radio NetworksTELKOMNIKA JOURNAL
Cognitive radio (CR) technology has emerged as a realistic solution to the spectrum scarcity
problem in present day wireless networks. A major challenge in CR radio networks is the hidden node
problem, which is the inability of the CR nodes to detect the primary user. This paper proposes energy
detector-based distributed sequential cooperative spectrum sensing over Nakagami-m fading, as a tool to
solve the hidden node problem. The derivation of energy detection performance over Nakagami-m fading
channel is presented. Since the observation represents a random variable, likelihood ratio test (LRT) is
known to be optimal in this type of detection problem. The LRT is implemented using the Neyman-Pearson
Criterion (maximizing the probability of detection but at a constraint of false alarm probability). The
performance of the proposed method has been evaluated both by numerical analysis and simulations. The
effect of cooperation among a group of CR nodes and system parameters such as SNR, detection
threshold and number of samples per CR nodes is investigated. Results show improved detection
performance by implementing the proposed model.
A SURVEY ON DYNAMIC SPECTRUM ACCESS TECHNIQUES IN COGNITIVE RADIOijngnjournal
Wireless networks are characterized by fixed spectrum policy. With increasing demands for wireless communication efficiently using the spectrum resources has become an essential issue. Cognitive radio is a form of wireless communication which is used to sense the spectrum and find the free spectrum. It is used by unlicensed users without causing interference to the licensed user. Cognitive radio with the dynamic spectrum access is key technology which provides the best solution by allowing a group of Secondary users to share the radio spectrum originally allocated to the primary users. Dynamically accessing the unused spectrum is known as dynamic spectrum access (DSA) which becomes a promising approach to increase
the efficiency of spectrum usage. In this paper, DSA models are discussed along with different methods such as game theory based method, a measurement-based model, network coded cognitive control channel, Markovian Queuing model, the Delay performance of threshold policies, fuzzy logic based method and spatio-temporal spectrum management model.
Spectrum Sensing using Cooperative Energy Detection Method for Cognitive RadioSaroj Dhakal
This document summarizes cooperative spectrum sensing using energy detection in cognitive radio networks. It discusses how cooperative sensing can improve detection performance by exploiting spatial diversity among cognitive radio users. The key points are:
1. Cooperative sensing allows cognitive radio users to share sensing information to make a combined decision that is more accurate than individual decisions. This mitigates issues like multipath fading and shadowing.
2. Energy detection is commonly used for cooperative sensing due to its simplicity. However, its performance depends on noise power uncertainty. Cooperative sensing addresses this by fusing observations from multiple spatially distributed users.
3. The document also discusses challenges in spectrum sensing like hardware requirements, hidden primary users, and detecting spread spectrum
Performance Analysis of Bayesian Methods to for the Spectrum Utilization in C...ijtsrd
1) The document proposes using Bayesian detection methods to improve spectrum utilization in cognitive radio systems without prior knowledge of primary user signals.
2) It describes developing an optimal Bayesian detector for digitally modulated primary users and approximating suboptimal detectors for low and high SNR regimes.
3) Simulation results show the Bayesian detector and its approximation in high SNR achieve higher detection probability and lower false alarm probability than energy detection, improving secondary user throughput and spectrum utilization, especially at high SNR where energy detection is suboptimal.
Performance Analysis and Comparative Study of Cognitive Radio Spectrum Sensin...IOSR Journals
In cognitive radio, spectrum sensing is an emergent technology to find available and unused
spectrum for increasing spectrum utilization and to overcome spectrum scarcity problem without harmful
interference to licensed users. Cooperative spectrum sensing is used to give reliable performance in terms of
detection probability and false alarm probability as well as in order to reduce fading, noise and shadowing
effects on cognitive radio users. In this paper according to detection performance and complexity various
cooperative spectrum sensing schemes have been discussed. We have analyzed spectrum sensing with different fusion rules and their comparative behavior has also been studied. Furthermore, we introduced AND-OR fusion rules in 2-bit and 3-bit hard combination schemes
Cooperative tv spectrum sensing in cognitive radio BY DEEPAK PORIYADeepak Poriya
This document discusses cooperative spectrum sensing in cognitive radio networks for Wi-Fi. It describes the system model of a Wi-Fi zone with primary and secondary users. It analyzes single user and cooperative spectrum sensing using energy detection algorithms. Cooperative sensing can use OR, AND or K-out-of-N rules at a fusion center to determine primary user presence. The document derives the optimal number of secondary users for the K-out-of-N rule and numerically calculates the optimal sensing time to minimize detection error probability and maximize throughput.
Reactive Power Compensation in Single Phase Distribution System using SVC, ST...IRJET Journal
This document discusses and compares two spectrum sensing techniques for cognitive radio networks: energy detection and matched filter detection. It analyzes the performance of these techniques based on probability of detection and probability of false alarm under different signal-to-noise ratio levels and fading channel models (AWGN, flat fading, Rayleigh fading). The key findings are that matched filter detection has better performance than energy detection, but requires prior knowledge of the primary signal. Energy detection has lower complexity but performs poorly in low SNR scenarios. Overall, matched filter detection results in lower probability of false alarms compared to energy detection.
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OPTIMIZATION OF THE RECURSIVE ONE-SIDED HYPOTHESIS TESTING TECHNIQUE FOR AUTO...ijwmn
In this paper, an optimized Recursive One-Sided Hypothesis Testing (ROHT) threshold estimation algorithm for energy detection based on Cognitive Radio (CR) application is presented. The ROHT algorithm is well known to compute and correct threshold values based on the choice of the parameter
values; namely the coefficient of standard deviation (z-value) and the stopping criteria (). A fixed computational process has been employed in most cases to estimate these parameter values, thus rendering them non-adaptive under different sensing conditions. Also, this fixed (manual tuning) process requires prior knowledge of some noise level to enable pre-configuration of a predefined target false alarm rate.
This renders the parameter estimation process cumbrous and unworkable for real-time purposes, particularly for autonomous CR applications. Furthermore, using wrong parameter values may lead to either too high or too low false alarms or detection rates of the algorithm. Sequel to aforementioned mentioned constraints, we propose a new mechanism for instantaneous parameter optimization of the ROHT algorithm using Particle Swarm Optimization (PSO) algorithm. Our PSO-ROHT model design was extensively tested under different conditions and results were compared to the non-optimized ROHT. The
results obtained show that the proposed design effectively adapts the parameter values of the Recursive One-Sided Hypothesis Testing algorithm in accordance with the input dataset under consideration. Also, that the proposed optimized model outperforms its non-optimized counterpart following the estimated detection probability and false alarm probability of both schemes, particularly in detecting Orthogonal Frequency-Division Multiplexing signals. In detecting the Orthogonal Frequency-Division Multiplexing signals at signal-to-noise ratio of 3dB and above, the proposed model achieved a higher detection rate of 96.23% while maintaining a low false alarm rate below 10%, which complies with the IEEE 802.22standard for Cognitive Radio application. Our PSO-ROHT algorithm is shown to be highly effective for autonomous and full blind signal detection in CR, with strong potentials for application in other areas requiring automatic threshold estimation.
A COGNITIVE RADIO SCHEME FOR DYNAMIC RESOURCE ALLOCATION BASED ON QOEijwmn
This paper introduces a cognitive radio scheme based on quality of experience (QoE). QoE involves the
mobile end user’s preferences. Considering QoE can lead to an improved cognitive radio resource
management strategy. The cognitive radio scheme aims to manage the traffic flow in dynamic systems; it is
a new way of thinking about dynamic resource management in cellular systems. The Use of the cognitive
radio techniques in cellular systems will improve the resource assignment in wireless communication. The
cognitive radio is a self-aware communication system that aims to use the resource assignment in an
efficient way. The proposed algorithm is very successful at handling the call-blocking rate based on QoS
and QoE.
ROUTING PROTOCOLS FOR DELAY TOLERANT NETWORKS: SURVEY AND PERFORMANCE EVALUATIONijwmn
Delay Tolerant Networking (DTN) is a promising technology that aims to provide efficient communication
between devices in a network with no guaranteed continuous connectivity. Most existing routing schemes
for DTNs exploit the advantage of message replication to achieve high message delivery rate. However,
these schemes commonly suffer from large communication overhead due to the lack of efficient mechanisms
to control message replication. In this paper we give a brief survey on routing protocols designed for
DTNs, and evaluate the performance of several representative routing protocols including Epidemic, Spray
and Wait, PRoPHET, and 3R through extensive trace-driven simulations. Another objective of this work is
to evaluate the security strength of different routing schemes under common DTN attacks such as the black
hole attack. The results and analysis presented in this paper can provide useful guidance on the design and
selection of routing protocols for given delay-tolerant applications.
A novel energy efficient routing algorithm for wireless sensor networks using...ijwmn
There are numerous applications for wireless sensor networks which are inevitable now a day in our daily
life. Majority of such applications which use wireless sensor networks will be in areas where the direct
human intervention is impossible. So the limited energy available in such sensors is a threat for prolonging
the life of the entire network. The need of energy efficiency in wireless sensor networks is a hot research
topic in which lot of new strategies for improvement in energy efficiency has been sought after. As
communication process consumes more energy, an energy efficient routing strategy can probably reduce
the energy consumption to a great extend. This paper gives an overview of the different routing techniques
in which mobile sinks are used to facilitate the routing process which can effectively reduce the energy use.
A new routing strategy with mobile sinks and a static sink is proposed and is compared based on the
matrices life time and average energy of the nodes with the existing Shortest Hop path (SH) algorithm. The
simulation results shows the proposed algorithm is more energy efficient than the existing one.
This document summarizes the design and performance evaluation of a two-unit Yagi-Uda antenna array for UHF satellite communication. Simulations were conducted using 4NEC2 software to optimize the design for a gain of 18.6 dBi at 437.025 MHz. Field tests validated the antenna array achieved high gain and front-to-back ratio while maintaining low standing wave ratio across the UHF band. The two-unit circularly polarized crossed Yagi array design successfully improved communication link margins for small cube satellites operating with stringent power budgets.
DISCRETE COSINETRANSFORM-II FOR REDUCTION IN PEAK TO AVERAGE POWER RATIO OF O...ijwmn
Orthogonal frequency Division multiplexing (OFDM) is the most familiar word in telecommunication
and wireless communication systems as it provides enhanced spectral efficiency than Frequency division
multiplexing (FDM).Although it is sustaining an orthogonal relation betweencarriers but high peak to
average power ratio (PAPR) is one of the main disadvantages of OFDM system.Various PAPR reduction
techniques have been used, including techniques based on companding. Incompanding, -Law
companding has potential to reduce the PAPR of OFDMsignals. -Law Companding technique
preserves the dynamic range of samples at low amplitudes.A new method named as precoding which is
having less complexity compared to the other power reduction techniques is proposed to reduce PAPR.
This paper put forward combination of two existing techniques namely -Law Companding Transform
and Discrete Cosine Transform-II precoding technique. The simulation results show that, the proposed
combinedscheme gives better result for PAPR Reduction and results in no distortion.
EFFECTS OF FILTERS ON THE PERFORMANCE OF DVB-T RECEIVERijwmn
Digital Video Broadcasting-Terrestrial (DVB-T) is an international standard for digital television
services. Orthogonal Frequency Division Multiplexing (OFDM) is the core of this technology. OFDM
based system like DVB-T can handle multipath fading and hence it can minimize Inter Symbol
Interference (ISI). DVB-T has some limitations too namely large dynamic range of the signals and
sensitivity to frequency error. In order to overcome these limitations DVB-T receivers should be optimally
designed. In this paper we address the issues related to optimal DVB-T receiver design. There of several
signal processing units in a DVB-T receiver. A low-pass filter is one of them. In this paper, we consider
some classic filters namely Butterworth, Chebyshev, and elliptic in the DVB-T receiver. The effects of
different filters on the performances of DVB-T receiver have been investigated and compared in this
paper under AWGN channel condition
DYNAMIC OPTIMIZATION OF OVERLAP-AND-ADD LENGTH OVER MIMO MBOFDM SYSTEM BASED ...ijwmn
An important role performed by Zero Padding (ZP) in multi-band OFDM (MB-OFDM) System. This role
show for low-complexity in résistance against multipath interference by reducing inter-carrier interference
(ICI) and eliminating the inter-symbol interference (ISI) Also, zero-padded suffix can be used to eliminate
ripples in the power spectral density in order to conform to FCC requirements. At the receiver of MB-OFDM system needs to use of a technique called as overlap-and-add (OLA). Which maintain the circular convolution property and take the multipath energy of the channel.In this paper, we proposed a method of performing overlap-and-add length for zero padded suffixes. Then,we studied the effect of this method, dynamic optimization of overlap-and-add (OLA) equalization, on the performance of MIMO MBOFDM system on Bit Error Rate (BER) with AWGN channel and SalehValenzuela (S-V) Multipath channel Model.In the dynamic optimization OLA, the Length of ZP depends on length of channel impulse response (CIR).
These measures, based on SNR, insert the ZP according to the measurement.Dynamic optimization of length of ZP improves the Performance of MIMO MBOFDM system. In fact wedeveloped a technique to select the length of ZP as function of SNR and CIR estimate. In our simulation
this technique improve to 0.6 dB at BER=10-2 with a multipath channels CM4
Design and analysis of high gain diode predistortionijwmn
This paper presents the design and analysis of a high gain, broadband Schottky and PIN diode based RF
pre-distortion linearizer for TWTA. The circuit is using ABCD matrix approach. The simulation is
performed using Agilent ADS software. We have proposed a new linearizer circuit which can achieve a
high gain compared to existing linearizer designs.
PERFORMANCE IMPROVEMENT OF PAPR REDUCTION FOR OFDM SIGNAL IN LTE SYSTEMijwmn
This document discusses performance improvement of peak-to-average power ratio (PAPR) reduction for orthogonal frequency division multiplexing (OFDM) signals in long-term evolution (LTE) systems. It proposes an improved amplitude clipping and filtering method for PAPR reduction that shows significant improvement over existing methods, with a slight increase in bit error rate. The document provides background on OFDM, PAPR issues in OFDM, and motivations for reducing PAPR such as improving power amplifier efficiency.
Long term evolution (LTE) is replacing the 3G services slowly but steadily and become a preferred choice
for data for human to human (H2H) services and now it is becoming preferred choice for voice also. In
some developed countries the traditional 2G services gradually decommissioned from the service and
getting replaced with LTE for all H2H services. LTE provided high downlink and uplink bandwidth
capacity and is one of the technology like mobile ad hoc network (MANET) and vehicular ad hoc network
(VANET) being used as the backbone communication infrastructure for vehicle networking applications.
When Compared to VANET and MANET, LTE provides wide area of coverage and excellent infrastructure
facilities for vehicle networking. This helps in transmitting the vehicle information to the operator and
downloading certain information into the vehicle nodes (VNs) from the operators server. As per the ETSI
publications the number of machine to machine communication (MTC) devices are expected to touch 50
billion by 2020 and this will surpass H2H communication. With growing congestion in the LTE network,
accessing the network for any request from VN especially during peak hour is a big challenge because of
the congestion in random access channel (RACH). In this paper we will analyse this RACH congestion
problem with the data from the live network. Lot of algorithms are proposed for resolving the RACH
congestion on the basis of simulation results so we would like to present some practical data from the live
network to this issue to understand the extent RACH congestion issue in the real time scenario.
Performance of the IEEE 802.15.4a UWB System using Two Pulse Shaping Techniqu...ijwmn
In Cognitive radio (CR) applications Ultra-wideband (UWB) impulse radio (IR) signals can be designed
such as they can co-exist with licensed primary users. The pulse shape should be adjusted such that the
power spectral characteristics not only meet the Federal Communications Commission (FCC) constrains,
but also mitigate multiple narrow-band interference at the locations of existing primary users. In this
paper, the Parks-McClellan (PM) Algorithm and the Eigen Value Decomposition (EVD) approach for
UWB impulse radio waveform shaping are considered. The power spectral density (PSD) and the bit-errorrate
(BER) performance of the two methods are compared in the presence of single and double narrowband
interference (NBI). The interference rejection capabilities of the two methods are evaluated and
compared for different interference and additive noise levels. In particular, the simulations consider the
coexistence of practical IEEE 802.15.4a UWB systems with both IEEE 802.11 wireless LAN systems
operating at 5.2 GHz and radio location services operating at 8.5 GHz.
The delivering of both good quality of service (QoS) and Grade of Service (GoS) in any competitive mobile
communication environment is a major factor to reducing subscribers’ churn rate. Therefore, it is
important for wireless mobile network operators to ensure stability and efficiency by delivering a
consistent, reliable and high-quality end user (subscriber) satisfaction. This can only be achieve by
conducting a regular network performance monitoring and optimisation as it directly impacts the quality of
the offered services and hence user satisfaction. In this paper, we present the results of network
performance evaluation and optimisation of a GSM network on cell cluster-basis, in Asaba region, South
East Nigeria. We employ a combination of essential key performance indicators such as dropped call rate,
call setup success rate and outage call rate to examine overall QoS and GoS performance of the GSM
network. Our results after network optimisation showed significant performance improvement in terms of
call drop rate, call set up success rate, and call block rate across. Specifically, the end user satisfaction
rate has increased from 94.45%, 87.74%, and 92.85% to 99.05%, 95.38% and 99.03% respectively across
the three GSM cell clusters. The GoS is reduced from 3.33%, 6.60% and 2.38% to 0.00%, 3.70% and
0.00% respectively. Furthermore, ESA, which correspond end points service availability, has improved
from 94.44%, 93.40% and 97.62% to 100%, 96.30% and 100% respectively. In addition, the average
throughput has improved from 73.74kbits/s, 85.06kbits/s and 87.54kbits/s to 77.07kbits/s, 92.38kbits/s and
102kbits/s respectively across the three GSM cell clusters.
S URVEY OF L TE D OWNLINK S CHEDULERS A LGORITHMS IN O PEN A CCESS S IM...ijwmn
he LTE/LTE-A has become a catchphrase for research
and lot of research are being conducted and
carried out in LTE in various issues by various peo
ple. New tools are developed and introduced in the
market to interpret the results of the new algorith
ms proposed by various people. Some tools are open
access which are free to use but some tools are pro
duced by the companies which are not open access. I
n
this paper some of the open access simulation tools
like LTE-Sim and NS-3 are analyzed and LTE downlin
k
scheduler algorithms are simulated using those tool
s. In LTE systems, the downlink scheduler is an
important component for radio resource management;
hence in the context of LTE simulation, a study
between the downlink scheduler models between the s
imulators are performed.
Performance analysis and implementation for nonbinary quasi cyclic ldpc decod...ijwmn
Non-binary low-density parity check (NB-LDPC) codes are an extension of binary LDPC codes with
significantly better performance. Although various kinds of low-complexity iterative decoding algorithms
have been proposed, there is a big challenge for VLSI implementation of NBLDPC decoders due to its high
complexity and long latency. In this brief, highly efficient check node processing scheme, which the
processing delay greatly reduced, including Min-Max decoding algorithm and check node unit are
proposed. Compare with previous works, less than 52% could be reduced for the latency of check node
unit. In addition, the efficiency of the presented techniques is design to demonstrate for the (620, 310) NBQC-
LDPC decoder.
Wireless sensor nodes are usually deployed in not easily accessible places to provide solution to a wide
range of application such as environmental, medical and structural monitoring. They are spatially
distributed and as a result are usually powered from batteries. Due to the limitation in providing power
with batteries, which must be manually replaced when they are depleted, and location constraints in
wireless sensor network causes a major setback on performance and lifetime of WSNs. This difficulty in
battery replacement and cost led to a growing interest in energy harvesting. The current practice in energy
harvesting for sensor networks is based on practical and simulation approach. The evaluation and
validation of the WSN systems is mostly done using simulation and practical implementation. Simulation is
widely used especially for its great advantage in evaluating network systems. Its disadvantages such as the
long time taken to simulate and not being economical as it implements data without proper analysis of all
that is involved ,wasting useful resources cannot be ignored. In most times, the energy scavenged is directly
wired to the sensor nodes. We, therefore, argue that simulation – based and practical implementation of
WSN energy harvesting system should be further strengthened through mathematical analysis and design
procedures. In this work, we designed and modeled the energy harvesting system for wireless sensor nodes
based on the input and output parameters of the energy sources and sensor nodes. We also introduced the
use of supercapacitor as buffer and intermittent source for the sensor node. The model was further tested in
a Matlab environment, and found to yield a very good approach for system design.
An efficient model for reducing soft blocking probability in wireless cellula...ijwmn
One of the research challenges in cellular networks is the design of an efficient model that can reduce call
blocking probability and improve the quality of service (QoS) provided to mobile users. Blocking occurs
when a new call cannot be admitted into the network due to channel unavailability caused by limited
capacity or when an ongoing call cannot be continued as it moves from one base station to another due to
mobility of the user. The proposed model computes the steady state probability and resource occupancy
distribution, traffic distribution, intra-cell and inter-cell interferences from mobile users. Previously
proposed models are reviewed through which the present model is built for use in emerging wireless
networks so as to obtain improved QoS performance. The developed model is validated through simulations
in MATLAB and its equations implemented using Java Programming Language. The results obtained
indicate reduced call blocking probability below threshold.
Performance evaluation of different spectrum sensing techniques for realistic...ijwmn
In this paper, the performance assessment of five different detection techniques from spectrum sensing
perspective in cognitive radio networks is proposed and implemented using the realistic implementation
oriented model (R-model) with signal processing operations. The performance assessment of the different
sensing techniques in the existence of unknown or imprecisely known impulsive noise levels is done by
considering the signal detection in cognitive radio networks under a non-parametric multisensory detection
scenario. The examination focuses on performance comparison of basic spectrum sensing mechanisms as,
energy detection (ED) and cyclostationary feature detection (CSFD) along with the eigenvalue-based
detection methods namely, Maximum-minimum eigenvalue detection (MMED), Roy’s largest Root Test
(RLRT) which requires knowledge of the noise variance and Generalized Likelihood Ratio Test (GLRT)
which can be implemented as a test of the largest eigenvalues vs. Maximum-likelihood estimates a noise
variance. From simulation results it is observed that the detection performance of the GLRT method is
better than the other techniques in realistic implementation oriented model.
A Grouped System Architecture for Smart Grids Based AMI Communications Over LTE ijwmn
- The document proposes a grouped hierarchical architecture and scheduling technique for smart meter communications over LTE networks. Smart meters are divided into groups, with each group connected to a data concentrator.
- The data concentrator collects smart meter readings and sends a total consumption message to the LTE network on a scheduled basis. It also sends individual smart meter readings.
- This grouped approach reduces the number of LTE modules needed and ensures real-time monitoring while avoiding overloading the LTE network, making LTE a promising solution for smart grid communications.
EFFICIENT MIXED MODE SUMMARY FOR MOBILE NETWORKSijwmn
This document proposes a new lossless compression scheme called Mixed Mode Summary-based Lossless Compression for Mobile Networks log files (MMSLC). MMSLC uses the Apriori algorithm to mine frequent patterns from log files. It then assigns unique codes to frequent patterns based on their compression gain. MMSLC exploits correlations between consecutive log files by using a mixed online and offline compression approach. It applies frequent patterns mined from previous files during online compression of current files, while also mining patterns from current files for future compression. The method achieves high compression ratios and provides summaries of frequent patterns to aid in network monitoring.
SPECTRUM SENSING IN COGNITIVE RADIO NETWORKS: QOS CONSIDERATIONS cscpconf
The rapidly growing number of wireless communication devices has led to massive increases in radio traffic density, resulting in a noticeable shortage of available spectrum. To address this shortage, the Cognitive Radio (CR) technology offers promising solutions that aim to improve the spectrum utilization. The operation of CR relies on detecting the so-called spectrum holes, the frequency bands that remain unoccupied by their licensed operators. The unlicensed users are then allowed to communicate using these spectrum holes. As such, the performance of CR is highly dependent on the employed spectrum sensing methods. Several sensing methods are already available. However, no individual method can accommodate all potential CR operation scenarios. Hence, it is fair to ascertain that the performance of a CR device can be improved if it is capable of supporting several sensing methods. It should obviously also be able to select the most suitable method. In this paper, several spectrum sensing methods are compared and analyzed, aiming to identify their advantages and shortcomings in different CR operating conditions. Furthermore, it identifies the features that need to be considered while selecting a suitable sensing method from the catalog of available methods.
Spectrum Sensing using Cooperative Energy Detection Method for Cognitive RadioSaroj Dhakal
This document summarizes cooperative spectrum sensing using energy detection in cognitive radio networks. It discusses how cooperative sensing can improve detection performance by exploiting spatial diversity among cognitive radio users. The key points are:
1. Cooperative sensing allows cognitive radio users to share sensing information to make a combined decision that is more accurate than individual decisions. This mitigates issues like multipath fading and shadowing.
2. Energy detection is commonly used for cooperative spectrum sensing due to its simplicity. However, its performance depends on noise power uncertainty.
3. Cooperative sensing involves local sensing by each cognitive radio, reporting results to a fusion center, and data fusion to make a combined decision. Centralized, distributed, and relay-
Sensing Time Improvement Using Two Stage Detectors for Cognitive Radio SystemIJCNCJournal
Cognitive radio (CR) is a promising technology for both present and future telecommunications to satisfy the demand of the next generation due to inefficient use of the allocated spectrum. Due to its ability to utilize the available bandwidth of other wireless communication networks and so enhance its occupancy. Spectrum sensing (SS) is the key characteristic of the CR system that helps it identify the empty spectrum. SS has gained a lot of interest recently and it is an active research area since it offers additional opportunities to secondary users. A broad variety of analytical methods to identify the Primary User's (PUs) presence have emerged as a result of SS techniques for CRs. Although each approach has its own benefits, the drawbacks attached to them make an individual implementation of the technique impractical for usage. To mitigate the drawbacks and maximize the benefits offered by the individual methods, a two stage detector can be employed for SS. However, the stages method lengthens the time needed to sense the spectrum and produce a definitive result. In this paper, we propose a two-stage sensing approach, where the first stage is an Interval Dependent Denoising detector (IDD) and followed by a second stage is Energy Detection (ED) which provides a large decrease in the mean sensing time compared to different related two-stage SS approaches The ED method is simple and has a short sensing time, but it performs poorly when the Signal to Noise Ratio (SNR) is low, Hence it is thought that separating PU activity from noise is essential for accurate SS. Therefore, we use IDD as a noise reduction technique in the first stage before the ED stage. The simulation results have been utilized to demonstrate that this technique leads to a large savings in sensing time as compared to an existing two-stage detection approaches
Sensing Time Improvement using Two Stage Detectors for Cognitive Radio SystemIJCNCJournal
Cognitive radio (CR) is a promising technology for both present and future telecommunications to satisfy the demand of the next generation due to inefficient use of the allocated spectrum. Due to its ability to utilize the available bandwidth of other wireless communication networks and so enhance its occupancy. Spectrum sensing (SS) is the key characteristic of the CR system that helps it identify the empty spectrum. SS has gained a lot of interest recently and it is an active research area since it offers additional opportunities to secondary users. A broad variety of analytical methods to identify the Primary User's (PUs) presence have emerged as a result of SS techniques for CRs. Although each approach has its own benefits, the drawbacks attached to them make an individual implementation of the technique impractical for usage. To mitigate the drawbacks and maximize the benefits offered by the individual methods, a two stage detector can be employed for SS. However, the stages method lengthens the time needed to sense the spectrum and produce a definitive result. In this paper, we propose a two-stage sensing approach, where the first stage is an Interval Dependent Denoising detector (IDD) and followed by a second stage is Energy Detection (ED) which provides a large decrease in the mean sensing time compared to different related two-stage SS approaches The ED method is simple and has a short sensing time, but it performs poorly when the Signal to Noise Ratio (SNR) is low, Hence it is thought that separating PU activity from noise is essential for accurate SS. Therefore, we use IDD as a noise reduction technique in the first stage before the ED stage. The simulation results have been utilized to demonstrate that this technique leads to a large savings in sensing time as compared to an existing two-stage detection approaches.
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.
SPECTRUM SENSING STRATEGY TO ENHANCE THE QOS IN WHITE-FI NETWORKSIJCNCJournal
The rapidly growing number of wireless devices running applications that require high bandwidths, has resulted in increasing demands for the unlicensed frequency spectrum. Given the scarcity of allocated unlicensed frequencies, meeting such demands can become a serious concern. Cognitive Radio (CR) technology opens the door for the opportunistic use of the licensed spectrum to partially address the issues relevant to the limited availability of unlicensed frequencies. Combining CR and Wi-Fi to form the socalled White-Fi networks, has been proposed for achieving higher spectrum utilization. This article discusses the spectrum sensing in White-Fi networks and the impacts that it has on the QoS of typical applications. It also reports the analysis of such impacts through various simulation studies. Our results demonstrate the advantages of an adaptive sensing strategy that is capable of changing the related parameters based on QoS requirements. We also propose such a sensing strategy that can adapt to the IEEE 802.11e requirements. The goal of the proposed strategy is the enhancement of the overall QoS of the applications while maintaining efficient sensing of the spectrum. Simulation results of the scenarios that implement the proposed mechanisms demonstrate noticeable QoS improvements compared to cases where common sensing methods are utilized in IEEE802.11 networks.
A Cognitive Radio And Dynamic Spectrum Access – A Studyjosephjonse
A basic problem facing the future in wireless systems is where to find suitable spectrum bands to fulfill the demand of future services. While all of the radio spectrum is allocated to different services, applications and users, observation show that usage of the spectrum is actually quite low. To overcome this problem and improve the spectrum utilization, cognitive radio concept has been evolved. Wireless communication, in which a transmitter and receiver can detect intelligently communication channels that are in use and those which are not in use are known as Cognitive Radio, and it can move to unused channels. This makes possible the use of available radio frequency spectrum while minimizing interference with other users. CRs must have the capability to learn and adapt their wireless transmission according to the surrounding radio environment. The application of Artificial Intelligence approaches in the Cognitive Radio is very promising since they have a great importance for the implementation of Cognitive Radio networks architecture. Dynamic spectrum access is a promising approach to make less severe the spectrum scarcity that wireless communications face now. It aims at reusing sparsely occupied frequency bands and does not interfere to the actual licensees. This paper is a review and comparison of different DSA models and methods.
A cognitive radio and dynamic spectrum access – a studyijngnjournal
A basic problem facing the future in wireless systems is where to find suitable spectrum bands to fulfill the
demand of future services. While all of the radio spectrum is allocated to different services, applications
and users, observation show that usage of the spectrum is actually quite low. To overcome this problem
and improve the spectrum utilization, cognitive radio concept has been evolved. Wireless communication,
in which a transmitter and receiver can detect intelligently communication channels that are in use and
those which are not in use are known as Cognitive Radio, and it can move to unused channels. This makes
possible the use of available radio frequency spectrum while minimizing interference with other users. CRs
must have the capability to learn and adapt their wireless transmission according to the surrounding radio
environment. The application of Artificial Intelligence approaches in the Cognitive Radio is very promising
since they have a great importance for the implementation of Cognitive Radio networks architecture.
Dynamic spectrum access is a promising approach to make less severe the spectrum scarcity that wireless
communications face now. It aims at reusing sparsely occupied frequency bands and does not interfere to
the actual licensees. This paper is a review and comparison of different DSA models and methods.
A review paper based on spectrum sensing techniques in cognitive radio networksAlexander Decker
This document summarizes different spectrum sensing techniques for cognitive radio networks. It discusses cooperative detection techniques which involve multiple cognitive radios sharing sensing information, and non-cooperative detection where radios act independently. Specific techniques covered include centralized, distributed, and relay-assisted cooperative sensing as well as blind sensing, energy detection, and eigenvalue-based sensing. The document concludes that cooperative sensing performs better than non-cooperative sensing, especially for low signal-to-noise ratio primary user signals.
This document proposes and analyzes several algorithms for blind spectrum sensing of OFDM signals in cognitive radio systems. It first shows that the existing cyclic prefix correlation coefficient (CPCC)-based detection algorithm is a special case of the constrained generalized likelihood ratio test (GLRT) in the absence of multipath. It then develops a new multipath-based constrained GLRT (MP-based C-GLRT) algorithm that exploits multipath correlation and outperforms CPCC-based detection in multipath environments. Combining CPCC- and MP-based C-GLRT algorithms provides further performance improvement. The document also develops a GLRT-based detection algorithm for unsynchronized OFDM signals that achieves near-synchron
An Approach to Spectrum Sensing in Cognitive RadioIOSR Journals
This document presents an approach to spectrum sensing in cognitive radio. It discusses three main categories of spectrum sensing techniques: transmitter detection, receiver detection, and interference temperature detection. It analyzes transmitter-based detection techniques like energy detection, matched filtering, and cyclostationary feature detection. It also discusses cooperative versus non-cooperative sensing and provides methodology used to implement a primary transmitter and the different detection techniques. Results are presented showing the output of the detectors at different SNR levels. Future work includes implementing the techniques on hardware for real-time processing and decision making in cognitive radio networks.
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.
OPTIMIZATION OF THE RECURSIVE ONE-SIDED HYPOTHESIS TESTING TECHNIQUE FOR AUTO...ijwmn
In this paper, an optimized Recursive One-Sided Hypothesis Testing (ROHT) threshold estimation algorithm for energy detection based on Cognitive Radio (CR) application is presented. The ROHT algorithm is well known to compute and correct threshold values based on the choice of the parameter
values; namely the coefficient of standard deviation (z-value) and the stopping criteria (). A fixed computational process has been employed in most cases to estimate these parameter values, thus rendering them non-adaptive under different sensing conditions. Also, this fixed (manual tuning) process requires prior knowledge of some noise level to enable pre-configuration of a predefined target false alarm rate. This renders the parameter estimation process cumbrous and unworkable for real-time purposes, particularly for autonomous CR applications. Furthermore, using wrong parameter values may lead to either too high or too low false alarms or detection rates of the algorithm. Sequel to aforementioned mentioned constraints, we propose a new mechanism for instantaneous parameter optimization of the ROHT algorithm using Particle Swarm Optimization (PSO) algorithm. Our PSO-ROHT model design was extensively tested under different conditions and results were compared to the non-optimized ROHT. The
results obtained show that the proposed design effectively adapts the parameter values of the Recursive One-Sided Hypothesis Testing algorithm in accordance with the input dataset under consideration. Also, that the proposed optimized model outperforms its non-optimized counterpart following the estimated detection probability and false alarm probability of both schemes, particularly in detecting Orthogonal Frequency-Division Multiplexing signals. In detecting the Orthogonal Frequency-Division Multiplexingsignals at signal-to-noise ratio of 3dB and above, the proposed model achieved a higher detection rate of 96.23% while maintaining a low false alarm rate below 10%, which complies with the IEEE 802.22
standard for Cognitive Radio application. Our PSO-ROHT algorithm is shown to be highly effective for autonomous and full blind signal detection in CR, with strong potentials for application in other areas requiring automatic threshold estimation.
A STUDY ON QUANTITATIVE PARAMETERS OF SPECTRUM HANDOFF IN COGNITIVE RADIO NET...ijwmn
The innovation of wireless technologies requires dynamic allocation of spectrum band in an efficient
manner. This has been achieved by Cognitive Radio (CR) networks which allow unlicensed users to make
use of free licensed spectrum, when the licensed users are kept away from that spectrum. The cognitive
radio makes decision, switching from primary user to secondary user and vice-versa, based on its built-in
interference engine. It allows secondary users to makes use of a channel based on its availability i.e. on the
absence of the primary user and they should vacate the channel once the primary user re-enters and
continue their communication on another available channel and this process in the cognitive radio is
known as spectrum mobility. The main objective of spectrum mobility is that, there is no interruption
caused due to the channel occupied by secondary users and maintains a good quality of service. In order to
achieve better spectrum mobility, it is mandatory to choose an effective spectrum handoff strategy with the
capability of predicting spectrum mobility. The handoff strategy with its parameters and its impact is an
important concept in spectrum mobility but fairly explored. In this paper an empirical study on quantitative
parameters involved in spectrum mobility prediction are discussed in detail. These parameters are studied
extensively because they play a vital role in the spectrum handoff process moreover the impact of these
parameters in various handoff methods can be used to predict the effectiveness of the system.
A STUDY ON QUANTITATIVE PARAMETERS OF SPECTRUM HANDOFF IN COGNITIVE RADIO NET...ijwmn
The innovation of wireless technologies requires dynamic allocation of spectrum band in an efficient
manner. This has been achieved by Cognitive Radio (CR) networks which allow unlicensed users to make
use of free licensed spectrum, when the licensed users are kept away from that spectrum. The cognitive
radio makes decision, switching from primary user to secondary user and vice-versa, based on its built-in
interference engine. It allows secondary users to makes use of a channel based on its availability i.e. on the
absence of the primary user and they should vacate the channel once the primary user re-enters and
continue their communication on another available channel and this process in the cognitive radio is
known as spectrum mobility. The main objective of spectrum mobility is that, there is no interruption
caused due to the channel occupied by secondary users and maintains a good quality of service. In order to
achieve better spectrum mobility, it is mandatory to choose an effective spectrum handoff strategy with the
capability of predicting spectrum mobility. The handoff strategy with its parameters and its impact is an
important concept in spectrum mobility but fairly explored. In this paper an empirical study on quantitative
parameters involved in spectrum mobility prediction are discussed in detail. These parameters are studied
extensively because they play a vital role in the spectrum handoff process moreover the impact of these
parameters in various handoff methods can be used to predict the effectiveness of the system.
ENERGY EFFICIENT COOPERATIVE SPECTRUM SENSING IN COGNITIVE RADIOIJCNCJournal
Sensing in cognitive radio (CR) protects the primary user (PU) from bad interference. Therefore, it is
assumed to be a requirement. However, sensing has two main challenges; first the CR is required to sense
the PU under very low signal to noise ratios which will take longer sensing time, and second, some CR
nodes may suffer from deep fading and shadowing effects. Cooperative spectrum sensing (CSS) is supposed
to solve these challenges. However, CSS adds extra energy consumption due to CRs send the sensing result
to the fusion center and receive the final decision from the fusion center. This is in addition to the sensing
energy itself. Therefore, CSS may consume considerable energy out of the battery of the CR node.
Therefore in this paper, we try to find jointly the sensing time required from each CR node and the number
of CR nodes who should perform sensing such that the energy and energy efficiency (i.e., ratio of
throughput to energy consumed) are optimized. Simulation results show that the joint optimization achieves
better in terms of energy efficiency than other approaches that perform separate optimization.
IRJET- Research on Dynamic Spectrum AllocationIRJET Journal
This document summarizes research on dynamic spectrum allocation using cognitive radio. It first provides background on the increasing interference in wireless networks due to the growing number of devices operating in unlicensed bands like the ISM band. It then introduces cognitive radio as a potential solution, which can detect available channels and adapt transmission accordingly to allow more concurrent devices. It discusses the main challenges for cognitive radios in not interfering with licensed users. The document reviews several papers on related topics like online spectrum allocation algorithms and surveys of spectrum management techniques. It also describes common spectrum sensing methods used by cognitive radios to detect spectrum holes like matched filtering, cyclostationary detection, and energy detection. Results are presented on performance metrics like end-to-end delay
With cloud computing, users can remotely store their data into the cloud and use on-demand high-quality applications. Data outsourcing: users are relieved from the burden of data storage and maintenance When users put their data (of large size) on the cloud, the data integrity protection is challenging enabling public audit for cloud data storage security is important Users can ask an external audit party to check the integrity of their outsourced data. Purpose of developing data security for data possession at un-trusted cloud storage servers we are often limited by the resources at the cloud server as well as at the client. Given that the data sizes are large and are stored at remote servers, accessing the entire file can be expensive in input output costs to the storage server. Also transmitting the file across the network to the client can consume heavy bandwidths. Since growth in storage capacity has far outpaced the growth in data access as well as network bandwidth, accessing and transmitting the entire archive even occasionally greatly limits the scalability of the network resources. Furthermore, the input output to establish the data proof interferes with the on-demand bandwidth of the server used for normal storage and retrieving purpose. The Third Party Auditor is a respective person to manage the remote data in a global manner.
Transmitter Detection Methods of Spectrum Sensing For Cognitive Radio Network...IRJET Journal
This document discusses and compares two spectrum sensing techniques for cognitive radio networks: energy detection and matched filter detection. It analyzes the performance of these techniques based on probability of detection and probability of false alarm under different signal-to-noise ratio levels and fading channel models (AWGN, flat fading, Rayleigh fading). The key findings are that matched filter detection has better performance than energy detection, but requires prior knowledge of the primary signal. Energy detection has lower complexity but performs poorly in low SNR scenarios. Overall, matched filter detection results in lower probability of false alarms compared to energy detection.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
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SELECTION OF SPECTRUM SENSING METHOD TO ENHANCE QOS IN COGNITIVE RADIO NETWORKS
1. International Journal of Wireless & Mobile Networks (IJWMN) Vol. 8, No. 1, February 2016
DOI : 10.5121/ijwmn.2016.8104 39
SELECTION OF SPECTRUM SENSING METHOD TO
ENHANCE QOS IN COGNITIVE RADIO NETWORKS
Nabil Giweli, Seyed Shahrestani and Hon Cheung
School of Computing, Engineering and Mathematics, Western Sydney University,
Sydney, Australia
ABSTRACT
The massively increasing number of wireless communication devices has led to considerable growths in
radio traffic density, resulting in a predictable shortage of the available spectrum. To address this potential
shortage, the Cognitive Radio (CR) technology offers promising solutions that aim to improve the spectrum
utilization. The operation of CR relies on detecting the so-called spectrum holes, i.e., the frequency bands
when they are unoccupied by their licensed operators. The unlicensed users are then allowed to
communicate using these spectrum holes. Consequently, the performance of CR is highly dependent on the
employed spectrum sensing methods. Several sensing methods are already available or literarily proposed.
However, no individual method can accommodate all possible CR operation scenarios. Hence, it is fair to
ascertain that the performance of a CR device can be improved if it is capable of supporting several
sensing methods. Then it should be able to effectively select the most suitable method. In this paper, several
spectrum sensing methods are compared and analyzed, aiming to identify their advantages and
shortcomings in different CR operating conditions. Furthermore, it identifies the factors that need to be
considered while selecting a proper sensing method from the catalog of available methods.
KEYWORDS
Cognitive Radio; Spectrum Sensing; QoS
1. INTRODUCTION
Conventionally, the Radio Frequency Spectrum (RFS) is statically regulated into licensed and
unlicensed bands. While the use of the former is restricted to authorized operators, the unlicensed
bands are available for use by the public subject to transmission constraints [1]. Under such
regulation, the unlicensed bands may get heavily congested. On the other hand, several studies
and measurements conducted around the world have indicated that the licensed RFS bands can be
underutilized [2].
From a technical perspective, the Cognitive Radio (CR) concept is a promising technology to
achieve an efficient utilization of RFS. The concept for CR model was introduced in 1999 by
Joseph Mitola [3]. In these models, the operators licensed to use some particular frequency bands
are considered as the Primary Users (PUs), whereas, the unlicensed participants are referred to as
the Secondary Users (SUs). The CR model is based on the realization that a PU may not fully
utilize its licensed bands, leaving parts of its spectrum unoccupied. These unoccupied white
spaces, or holes, relate to use, or more correctly the lack of use, in terms of frequency, time, or
space and location. An SU can utilize these holes in addition to the unlicensed bands that it may
typically use.
2. International Journal of Wireless & Mobile Networks (IJWMN) Vol. 8, No. 1, February 2016
40
To achieve their objectives to maximize the utilization of the available frequency spectrum, CR
systems are dependent on the execution of a sequence of several functions, the so-called CR
cycle. A typical CR cycle was proposed by Mitola [3]. This is illustrated in Figure 1.
The main functions of the CR cycle are spectrum sensing, spectrum decision, spectrum sharing,
and spectrum mobility. More specifically, an SU should be able to perform the following [4]:
• Spectrum sensing: sense the surrounding RFS to determine spectrum holes and to detect
the presence of the relevant PU.
• Spectrum decision: analyze and decide which spectrum hole is the most suitable for
satisfying the application requirements.
• Spectrum sharing: share the available spectrum holes with other SUs as fairly as possible.
• Spectrum mobility: seamlessly switch to another suitable spectrum hole to avoid
interference with a detected PU that may wish to start using its licensed spectrum. The
decision of which spectrum hole is a suitable for handoff to is to be requested from
spectrum decision function.
Detecting the presence of a PU, or more precisely finding out whether the PU is using its
allocated spectrum or not, is an essential task for a CR device. On one hand, this fundamental task
requires improving sensing accuracy by avoiding false positive results while detecting the
presence of a PU. On the other, the employed sensing technique should achieve a high detecting
probability of the available spectrum holes. The nature of the electromagnetic signals makes
accurate sensing a complicated process. More specifically, the Signal to Noise Ratio (SNR), the
multipath fading of the PU signals, and the changing levels of noise can significantly affect the
sensing accuracy [5, 6]. Moreover, imperfect spectrum sensing can result in increased
transmission error rates, for both the PU and the SUs [7]. Such errors may contribute to the
degradation of the quality of services (QoSs) provided by a PU and SUs. Noticeably, any QoS
degradation that can be attributed to the CR technology can potentially harm the progress of the
CR-based solutions. In this paper, the main features and limitations of the prevalent spectrum
sensing methods are examined. Furthermore, the key aspects that should be involved in selecting
the appropriate sensing method are highlighted and discussed.
The remainder of this paper is organized as follows. Section II presents the background and
motivation for this work. The effects of the sensing operation on the QoS of the applications
running over CR networks are described in Section III. Several sensing approaches are studied
and discussed in Section IV. Factors that may help in selecting the proper sensing techniques are
outlined in Section V. The last section gives the conclusions and points to the potential future
expansion of the reported work.
Figure 1. Basic CR cycle
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2. MOTIVATIONS
Most of the previous reviews of spectrum sensing techniques are mainly focused on the operation,
accuracies, complexities, and implementation issues [8-11]. For instance, the relation between the
sensing accuracy and the sensing time or frequency is the primary focus of the authors in [8].
They suggested that the focus should be on finding an optimal spectrum sensing technique with
the capability of flexible tuning between time and frequency resolutions. For such optimization
possibility, they nominate a wavelet-based spectrum estimation method. However, they find that
the available state-of-art sensing technologies do not offer a possible trade-off between the
complexity of the sensing method and its accuracy. In contrast, other reviewers consider the
characteristics of the PU signal as the main factor for selecting a proper sensing method [9].
Nevertheless, other factors should be considered for more adaptive sensing and improved
performance.
In general, the common approach is about how to find an optimal sensing method for all possible
CR operation requirements. However, all the aforementioned references agree that none of the
proposed sensing methods is suitable for all possible sensing situations, conditions and
technologies of CR systems. This study shifts the focus to a new approach where a CR device
supports a range of various sensing methods. Thus, the proper sensing technique can be selected
based on the real-time requirements. This approach implies the need for a real-time mechanism
to select the most suitable sensing method based on a number of factors or criteria. In this paper,
various sensing methods are studied toward finding the relevant selection criteria that should be
considered when designing such as real-time selection mechanism.
3. SENSING OPERATION IMPACT ON APPLICATIONS’ QOS IN CR
NETWORKS
As shown in Figure 2, the sensing operation of a CR consists of repeated cycles of the sensing
period T. The sensing period effectively represents the time interval where sensing is repeated
together with data transmission. It also represents the communication frame in CR, referred to as
a CR frame. During the sensing time t in a sensing period, a CR device obtains frequency
spectrum information, called RFS Stimuli in Figure 1, from its environment of surrounding radio
frequency spectrum. After the sensing time, the CR device can decide to transmit data on the
same channel or in a new vacant channel, i.e., a spectrum hole, based on the outcome from the
spectrum decision component.
The decision taken by the CR device is based on the sensing outcome, i.e., the presence or
absence of suitable spectrum holes as well as that of the PU. The data transmission starts after the
sensing time until the next sensing period, also called the CR communication frame. The data
transmission time (T-t) depends on the sensing time t and the CR frame time T and hence the data
transmission is based on how frequent and long the sensing is conducted. Thus, sensing frequency
is 1/T. The sensing time t and the CR frame time T can be designed to be fixed for all frames or
could be designed to vary based on the design goals [12]. Typically, sensing should be as short
and less frequent as possible without affecting the sensing accuracy [13].
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Figure 2. Simple structure of CR frames based on sensing operation
Increasing the sensing time t and conducting sensing more frequently, i.e. decreasing T, lead to an
increase in the probability of correct detection of the PU’s presence. In turn, this leads to more
protection to the PU from interference by other CR users and more utilization of the spectrum. On
the other hand, it leads to less data transmission rate and hence to QoS degradation for SUs. The
degradation can be measured by several parameters such as throughput, delay and MAC layer
process overhead [14]. Therefore, designing the sensing time and frequency of sensing should
take into account the trade-off between protecting the PU’s QoS and improving the QoS of SUs.
4. SENSING METHODS
The main challenge facing the sensing methods is how to improve the spectrum sensing
performance by mainly increasing the positive detection probability and decreasing the false
detection probability. A sensing technique with a higher positive detection probability provides
more protection to PU. A CR device with a lower probability of false detection of the presence of
the PU has more chance to use the available spectrum holes. Therefore, the CR device has more
chance of achieving a higher throughput on the CR network. The design of a sensing technique is
constrained by an acceptable level of false detection [15]. Additionally, improving sensing
performance is challenged by a range of trade-offs and various constraints such as application
requirements, hardware capability, complexity and required infrastructure [16].
In general, a sensing method that uses surrounding RFS information collected by the CR device
only is called a local sensing method. If the SUs do not exchange their surrounding RFS
information gathered by local sensing, then the sensing method is referred to as a non-cooperative
sensing method. In this paper, the sensing methods are also classified into three categories:
methods with no prior sensing information required, methods based on prior sensing information
and methods based on sharing of sensing information amongst SUs.
4.1. Blind Sensing
In blind sensing, no prior information about the PUs’ signal is necessary for the sensing methods
under this category. However, prior information about the noise power of the targeted spectrum
may be required for better performance. Otherwise, a reasonable estimation of the noise power is
used instead. Two well-known blind sensing methods are based on energy detection and
covariance-based detection.
4.1.1. Energy Detection
The energy detection, also known as radiometry or periodogram, is the most common method for
spectrum sensing because of its low implementation complexity and computational overhead [5].
In this method, an energy detector is used to monitor the energy level of the communication
channel with a narrowband frequency spectrum and then the observed signal energy level is
compared with a predefined threshold. The channel is occupied by the PU if the signal’s energy is
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over the threshold; otherwise, it is considered unoccupied and therefore a spectrum hole exists in
the channel. Because of this simplicity, this technique requires the shortest sensing time t per CR
frame compared to other common sensing technologies [17].
Generalizing the use of this method faces several challenges as a consequence of its simplicity.
Firstly, selection of the threshold used for detection becomes an issue when the channel noise
level is unknown or uncertain over time [18]. Secondly, under a low SNR, it is hard to
differentiate between modulated signals, including signals of other SUs, noise, and interference,
resulting in poor detection performance [5]. Lastly, an energy detector is ineffective in detecting
spread spectrum signals [19].
4.1.2. Covariance-based Detection
This method is based on comparing the covariance of the observed signal and the covariance of
the noise where statistical covariance matrices of signal and noise are usually different [20]. The
main improvement of this method is to overcome the energy detection shortcomings. In
particular, it can distinguish between signal and noise in a low SNR, and without any prior
information about the PU’s signal and channel noise. This improvement is achieved at the
expense of adding a computational overhead in computing the covariance matrix of the observed
signal samples [11]. In addition to an increase in complexity, other drawbacks of the energy
detection are still present in the covariance-based detection.
The covariance-based detection method works with no prior information about the PU signals.
They have a limited performance particularly when the PU uses spread spectrum signals for its
transmission techniques. Moreover, the blind sensing methods could not effectively distinguish
between PU and other SUs that are sharing the same spectrum holes. Research is ongoing to
improve the blind sensing approach in terms of performance and required sensing time, such as in
[21, 22].
4.2. Prior Information Required
Methods belonging to this category rely on partial or full information about the PU’s transmission
signal to be able to differentiate it from other signals and noise. In this category, the sensing
method takes several samples of the surrounding spectrum of a certain channel and extracts any
possible features of the collected samples. Then it compares these characteristics with the prior
known features of the PU signal. The algorithms used to derive and compare these features differ
from sensing method to another. Also, the amount and type of the required prior information are
based on the used method. In this section, several of the sensing methods belong to this category
are described.
4.2.1. Cyclostationarity Feature Detection
This method is based on distinguishing the PU signal from noise, interference, and other signals
by identifying its cyclostationarity features [23, 24]. These cyclostationarity features are
associated with the signal modulation type, carrier frequency, and data rate. Hence, the CR device
needs sufficient prior information about these unique characteristics of the PU signal. Based on
this information, it can perform a cyclostationarity analysis on the signal to identify matched
features [9]. For this method to perform better than the energy detection method, an adequate
number of real-time sample sets in the frequency domain need to be collected. As a consequence,
better performance accrues more complexity and sensing time at the expense of the available
throughput [9].
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4.2.2. Correlation Detection
Sensing based on correlation is also known as waveform-based sensing or coherent sensing. In
this method, the expected correlation or coherence between the observed signal samples is
identified to detect the PU signal based on previous knowledge about its waveform patterns [9].
The accuracy of the sensing increases when the length of the known signal pattern of the PU is
increased [25]. The main drawback of this method is related to the large amount of information
required for signal patterns of the PUs to achieve a high performance that is not practical for
several CR systems.
4.2.3. Radio Identification Based Sensing
This method is based on having a priori information about the transmission technologies used by
the PU. In the radio identification stage of the method, several extracted features of the received
signal are exploited and then classified to determine if the signal demonstrates the PU signal
technology [26]. Fundamentally, the feature extraction and classification techniques are used in
the context of the European Transparent Ubiquitous Terminal (TRUST) project [27]. For
collecting and extracting the signal features, the radio identification method may use one of the
known sensing techniques, such as the energy detection method [9]. The radio identification
improves the accuracy of the energy detection to some extent with complexity implication. The
achieved precision is dependent on the signal feature extraction and classification techniques used
to identify the presence of the PU.
4.2.4. Matched Filtering
The matched filtering method achieves a higher detection probability in a shorter detection time,
compared to other methods that are similarly based on prior information [28, 29]. This method is
considered as the best sensing method in this classification. The collected signal is passed through
a filter that will amplify the possible PU signal and attenuate any noise signal. The filter makes
the detection of the presence of the PU signal more accurate [29]. The filter, which is known as a
matched filter, has to be tuned based on some features of the PU signal. These features include
the required bandwidth, operating frequency, the modulation used and frame format [9]. One of
the disadvantages of this method is in implementation where different PUs signal types require
different dedicated hardware receivers. This requirement makes the method difficult to be
practically implemented and also leads to higher power consumption during operation if the
method is implemented based on current hardware technologies.
Figure 3 shows an estimated comparison between non-cooperative sensing methods, based on
accuracy and complexity of the reviewed sensing methods in this study. Table 1 shows more
comparison aspects between local sensing methods. The comparison clearly shows that a higher
accuracy is achieved in the cost of complexity. Moreover, sensing methods with higher
performance and more robustness against noise require more sensing time and sufficient prior
information about the PU signal.
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Table 1. Comparison between local sensing methods
4.3. Based on SU Cooperation
The main principle of this approach is that SUs share their locally sensed information of the
spectrum with each other. The use of sensed information from other SUs can produce a more
accurate sensing outcome than relying solely on local sensing. The hidden transmitter problem is
an example of the issues that may prohibit a CR from detecting the presence of a PU, when the
CR relies only on locally sensed information. The cause of this problem is the fading and
shadowing of the signals emitted from a PU, although it is within the transmission range of the
CR [9]. However, when cooperated SUs are spatially distributed, it helps to overcome the hidden
PU problem and other limitations of local sensing [30]. Sensing cooperation can also reduce the
local sensing cost, e.g., sensing time and energy consumption while maintaining sensing quality
by scheduling the sensing operation among cooperative SUs [31]. The sensing method used by an
individual SU can be based on one of the sensing methods for local sensing, such as energy
detection and cyclostationarity feature detection [10].
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In some environments, cooperative sensing may lose its advantages as far as an individual SU is
concerned. For instance, increasing the local sensing frequency in an individual SU of high
mobility is more efficient, in terms of sensing accuracy and overhead, than to cooperate with
other SUs [19]. In cooperative sensing, the improvement of sensing is more noticeable when the
number of cooperative SUs is increased. However, involvement of more SUs will increase the
cooperation overhead in terms of the amount of data exchange and the time required for the
exchange [32].
A cooperative approach can only be used when SUs are able and willing to collaborate. Also, a
SU may not always find other cooperative SUs within its transmission range. Therefore, the CR
devices should not solely rely on cooperative sensing approaches. They should be able to use a
suitable local sensing method and resort to cooperative sensing, only when an enhanced
performance is possible.
5. FACTORS FOR SELECTING SUITABLE SENSING METHOD
Selecting the suitable sensing method for a particular CR operation condition depends on several
factors. These factors may change during the CR operation. Thus, the proper sensing method for
the new conditions might be a different method. Based on the discussions in previous sections,
notable factors are described in the following sub-sections.
5.1. Applications QoS Requirements
The QoS requirements differ based on the applications running on a CR device. The sensing
delay and transmission throughput vary from one sensing method to another within the same
operating conditions. As a result, the sensing operation used on a CR device has a direct impact
on the QoS of an application running on the device, mainly in terms of the throughput, delay and
jitter. As sensing is a repetitive operation, a CR device should be able to select a proper sensing
method with the least impact on the QoS of the running application. As shown in Table 1, the
required sensing time and the accuracy level vary depending on the sensing method used. Using a
sensing method having a higher sensing accuracy leads to greater utilization of the spectrum.
However, achieving a higher sensing accuracy requires more sensing time that causes more delay
to the running application. For example, the sensing time for energy detection is usually less than
1 ms while cyclostationarity feature detection requires 24 ms or more [17]. For an optimal
sensing accuracy, the sensing time needs to be in the range of 2 seconds as has been found in
[33]. Such a long sensing time is not suitable for delay sensitive applications, such as VoIP.
Hence, the sensing methods that require long sensing times should be avoided when a CR device
is running an application sensitive to delay. Similarly, other operational requirements must also
be taken into account.
5.2. Availability of Prior Information
The amount of information available about the characteristics of the PUs and the communications
media is an important factor influencing the selection of a proper sensing method. For instance,
insufficient information about the PU signals excludes the use of the methods utilizing matched
filters. To achieve an optimal sensing accuracy, a CR device should be able to change the sensing
method based on the information that becomes available about the PU signal or the SNR of the
targeted spectrum. The energy detection method performs more effectively when the SNR is high
so it could be the preferred sensing method in this situation and this method has a minimal
overhead in terms of sensing time and power consumption. In contrast, in low or uncertain SNR,
the energy detection method performs very poorly and thus should be avoided. Under the absence
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of any prior information about the PU, the selection of the sensing method is limited to the blind
sensing methods. The range of the sensing methods based on prior information that can be used is
depended on the type of the available information about the PU. For example, the transmission
technology used by a PU is enough for sensing methods based on radio identification, but it is not
adequate for those based on the use of matched filters, as they requires more detailed information.
Obtaining very specific information about a PU, including the modulation used and frequency
operation, is not possible in some cases. The operation of a CR device usually involves switching
amongst different frequency bands licenced to different PUs. Therefore, the CR device has to
change the sensing method based on the information available about the new frequency band.
5.3. Level of Protection Required for PU
The selection of the sensing method must be considered with regard to the degree of protection
necessary for the PU. They may vary depending on available frequency bands and types of
services. For instance, analog TV service is more robust against interference than digital TV
service [16]. Hence, a sensing method that provides less protection, i.e., lower PU detection
probability, should only be used when the PU is more tolerant of interference such as in analog
TV services. The PU application sensitivity should also be considered on the protection level
required. For example, PU signals used for military and security purposes require a high level of
protection. High accuracy sensing may be enforced in frequency bands where the PU signals used
for critical missions. This factor poses the need of classifying different protection levels for PUs
based on the transmission technology being used by the PUs and their application sensitivity.
These protection levels can be assigned to each licensed band and announced. Currently, the
IEEE standardization effort, for CR, specifies only one general protection level, i.e., the minimum
accepted level of detection probability is 90% [34]. The wide adoption of the CR technology is
based on how extent this technology success in guaranteeing an adequate level of protection to
the PUs.
5.4. CR Device Capability
A CR device designed with limited hardware resources and power capacities will not be able to
support a wider range of sensing methods. Some methods require sophisticated hardware
components and higher power consumptions, e.g. the matched filter method, compared to simple
ones such as the energy detection method. An ideal CR device should be able to be reconfigured
on-the-fly to support a broad range of sensing methods. In practice, a CR device’s actual
capability will limit the range of sensing methods that can be supported. For mobile CR devices,
which is capable of supporting a wide range of sensing methods, the remaining battery power or
the economic power consumption theme can be considered in the selection of a sensing method
requiring lower power consumption.
5.5. The CR Network Mode and Capability
The network mode and capability are important factors to CR systems to make a decision
between cooperative and non-cooperative sensing approaches. In CR networks with infrastructure
and centralized topology, a method based on cooperative sensing is more suitable than that based
on local sensing only. Hence, the capability of such a CR network depends on how much
management ability can provide for white space determination to its CR devices. Furthermore, the
capacity of a CR network relies on how much information the network can gather and provide to
its CR users about the PU signals and the ambient spectrum.
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In addition, the Medium Access Control (MAC) techniques used by a CR device should be considered
in selecting a local sensing method. In general, the MAC techniques can be classified into three approaches:
random access, time slotted and hybrid protocols [35, 36]. The Carrier Sense Multiple Access with
Collision Avoidance (CSMA/CA) mechanism is widely used in random access and hybrid based
protocols. The well-known IEEE 802.11stadnrads are based on CSMA/CA where the random
access or hybrid based protocols are adopted. When a CR device uses the CSMA/CA to content
on the same spectrum holes, the sensing operation will be conducted more often. Hence, the
selection of the sensing method should be considered under two stages. The first stage of sensing
is conducted to avoid interference with the PU user. While the second stage is performed within
the contention window to avoid interference with other CR users. In the first stage, as the PU
protection is the main concern, a high accuracy method should be used. In the second stage, the
energy detection method is usually used because it requires a small sensing time. In the time
slotted approach, the CR users share the spectrum based on Time-Division Multiple Access
(TDMA) which avoids interference between CR users [37]. Hence, the sensing operation is only
needed to protect the PU. Therefore, TDMA networks require sensing less frequent than random
access networks. The hybrid protocols are used to achieve a compromisation between random
access and time slotted approaches. This compromisation should be also reflected on
compromising switching between complex and simple sensing methods.
6. CONCLUSIONS
The work reported in this paper indicates that none of the available spectrum sensing techniques
can achieve perfect detection of spectrum holes or the presence of the PU for all potential CR
operating conditions. The spectrum sensing operation has an essential impact on the QoS of the
running applications and overall performance in CR. This impact varies based on the sensing
method used. Therefore, to improve the performance of CR systems, the relevant devices must be
capable of utilizing a range of sensing methods. The selection of the most suitable method from
the available sensing methods is based on a number of factors that have also been identified and
discussed in this paper. The two most important factors among them are the QoS requirements
and the required protection level for PU signals. This study poses the need of a real-time selection
mechanism of the proper sensing method with the consideration of the stated factors. Our future
works will focus on more exhaustive evaluations of these factors and how their fine-tunings can
contribute to an improved CR performance. Furthermore, a real-time mechanism for selecting the
proper sensing method based on these factors is our future aim.
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AUTHORS
Nabil Giweli received the B.Sc. degree in Communication Engineering from Tripoli
University, Libya, in 1997, the Master degree in Information and Communication
Technology (with the dean medal award) from the Western Sydney University in 2011,
and another M.Sc. form the same university in Cloud Security in 2013. Currently, he is a
Ph.D. candidate and a casual teacher at the School of Computing, Engineering and
Mathematics, Western Sydney University, Australia. His current research area is in
Cognitive Radio Technologies.
Dr. Seyed Shahrestani completed his PhD degree in Electrical and Information Engineering
at the University of Sydney. He joined Western Sydney University (Western) in 1999,
where he is currently a Senior Lecturer. He is also the head of the Networking, Security
and Cloud Research (NSCR) group at Western. His main teaching and research interests
include: computer networking, management and security of networked systems, analysis,
control and management of complex systems, artificial intelligence applications, and health
ICT. He is also highly active in higher degree research training supervision, with
successful results.
Dr. Hon Cheung graduated from The University of Western Australia in 1984 with First
Class Honours in Electrical Engineering. He received his PhD degree from the same
university in 1988. He was a lecturer in the Department of Electronic Engineering, Hong
Kong Polytechnic from 1988 to 1990. From 1990 to 1999, he was a lecturer in Computer
Engineering at Edith Cowan University, Western Australia. He has been a senior lecturer in
Computing at Western Sydney University since 2000. Dr Cheung has research experience
in a number of areas, including conventional methods in artificial intelligence, fuzzy sets,
artificial neural networks, digital signal processing, image processing, network security and forensics, and
communications and networking. In the area of teaching, Dr Cheung has experience in development and
delivery of a relative large number of subjects in computer science, electrical and electronic engineering,
computer engineering and networking.