This document compares the performance of three spectrum sensing techniques for cognitive radio systems: energy detection, matched filter detection, and cyclostationary feature detection. Energy detection simply analyzes signal energy without any prior knowledge, but performs poorly at low SNR. Matched filter detection requires knowledge of the primary signal but performs better than energy detection. Cyclostationary feature detection exploits periodic features of primary signals and achieves the best performance, with 100% detection probability down to -8dB SNR, but has a higher computational complexity. Simulation results show cyclostationary detection outperforms the other techniques in terms of detection probability and false alarm rate across all SNR values.
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
Spectrum Sensing Detection Techniques for Overlay UsersIJMTST Journal
Spectrum allocated Agency (FCC) is currently working on the concept of white space users “borrowing” spectrum from free license holders temporarily to improve the spectrum utilization, i.e known as dynamic spectrum access (DSA). CRN systems can utilize dispersed spectrum, and thus such approach is known as dispersed spectrum cognitive radio systems. This project provides a tradeoff between a false alarm probability (Pf) and the signal to noise ratio (SNR) value of any spectrum detector to have a certain performance. Moreover, the performance of the cyclostationary detector (CD) and the matched filter detector (MF) is better than the energy detector(ED) especially at low signal to noise ratio values. Unfortunately, the cyclostationary spectrum sensing method, performance is not satisfying when the wireless fading channels are employed. In this project we provide the best trade off for spectrum usage for over lay users.
Spectrum Sensing Detection with Sequential Forward Search in Comparison to Kn...IJMTST Journal
FCC is currently working on the concept of white space users “borrowing” spectrum from free license
holders temporarily to improve the spectrum utilization.
This project provides a relation between a Pf and the SNR value of any spectrum detector to have a
certain performance. Previous spectrum sensing detection techniques are only suitable for Low SNR and
are based on signal information values. But these methods are purely narrow band spectrum applications
In order to overcome the above said drawbacks we propose a novel method of spectrum sensing method
and is suitable for low and high SNR values, the sensed spectrum applicable for wide band applications.
Our proposed method does not require signal information at the receiver and channel information, because
this flexibility sensing rate is very high compared to previous techniques.
Single User Eigenvalue Based Detection For Spectrum Sensing In Cognitive Rad...IJMER
Scarcity of spectrum is the issue that wireless communication technology has to deal with.
Primary user is the licensed user of the spectrum. When primary user is idle or not using the spectrum
secondary user can utilize the spectrum. This sharing of spectrum can be enabled by cognitive radio
(CR) technology. The heart of enabling this technology is spectrum sensing. Spectrum sensing involves
detection of primary signal at very low SNR (in the range of -20 dB), under noise and interference
uncertainty. This requirement makes spectrum sensing, a hard nut to crack. Another major issue in
detection is hidden node problem wherein the node in vicinity of primary transmitter also indicates
absence of the primary signal since it is hidden behind the large object. There are various algorithms
for detection viz. energy detection, matched filter detection, feature detection (cyclostationary
detection, eigen-value based detection etc.) These algorithms have limitations of complexity,
requirement of signal knowledge and detection performance. In this paper the performance of
eigenvalue based detection (EBD) method in presence of noise and low SNR of the received signal has
been evaluated for a single user.
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.
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.
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
Spectrum Sensing Detection Techniques for Overlay UsersIJMTST Journal
Spectrum allocated Agency (FCC) is currently working on the concept of white space users “borrowing” spectrum from free license holders temporarily to improve the spectrum utilization, i.e known as dynamic spectrum access (DSA). CRN systems can utilize dispersed spectrum, and thus such approach is known as dispersed spectrum cognitive radio systems. This project provides a tradeoff between a false alarm probability (Pf) and the signal to noise ratio (SNR) value of any spectrum detector to have a certain performance. Moreover, the performance of the cyclostationary detector (CD) and the matched filter detector (MF) is better than the energy detector(ED) especially at low signal to noise ratio values. Unfortunately, the cyclostationary spectrum sensing method, performance is not satisfying when the wireless fading channels are employed. In this project we provide the best trade off for spectrum usage for over lay users.
Spectrum Sensing Detection with Sequential Forward Search in Comparison to Kn...IJMTST Journal
FCC is currently working on the concept of white space users “borrowing” spectrum from free license
holders temporarily to improve the spectrum utilization.
This project provides a relation between a Pf and the SNR value of any spectrum detector to have a
certain performance. Previous spectrum sensing detection techniques are only suitable for Low SNR and
are based on signal information values. But these methods are purely narrow band spectrum applications
In order to overcome the above said drawbacks we propose a novel method of spectrum sensing method
and is suitable for low and high SNR values, the sensed spectrum applicable for wide band applications.
Our proposed method does not require signal information at the receiver and channel information, because
this flexibility sensing rate is very high compared to previous techniques.
Single User Eigenvalue Based Detection For Spectrum Sensing In Cognitive Rad...IJMER
Scarcity of spectrum is the issue that wireless communication technology has to deal with.
Primary user is the licensed user of the spectrum. When primary user is idle or not using the spectrum
secondary user can utilize the spectrum. This sharing of spectrum can be enabled by cognitive radio
(CR) technology. The heart of enabling this technology is spectrum sensing. Spectrum sensing involves
detection of primary signal at very low SNR (in the range of -20 dB), under noise and interference
uncertainty. This requirement makes spectrum sensing, a hard nut to crack. Another major issue in
detection is hidden node problem wherein the node in vicinity of primary transmitter also indicates
absence of the primary signal since it is hidden behind the large object. There are various algorithms
for detection viz. energy detection, matched filter detection, feature detection (cyclostationary
detection, eigen-value based detection etc.) These algorithms have limitations of complexity,
requirement of signal knowledge and detection performance. In this paper the performance of
eigenvalue based detection (EBD) method in presence of noise and low SNR of the received signal has
been evaluated for a single user.
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.
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.
A SURVEY ON OPTIMIZATION BASED SPECTRUM SENSING TECHNIQUES TO REDUCE ISI AND ...IJNSA Journal
Cognitive radio is emerging technologies in OFDM based wireless systems which are very important for spectrum sensing. By using cognitive radio (CR) high data can be transferred with low bit error rate. The key idea of OFDM is to split the total transmission bandwidth into the subcarriers which further reduce the intersymbol interference (ISI) and peak to average power ratio(PAPR) in the signal. There are many optimization based spectrum sensing techniques are existing for efficient sensing purpose but each has its own advantages and disadvantages. This leads to start the comprehensive study for reducing PAPR and ISI(Intersymbol interference) in terms of FPGA based partial configuration. In the first part of review OFDM characteristics of the signal has compared with several optimizations based ISI reduction techniques. The second part is to compare the various spectrum sensing techniques in cognitive radio engine and its application in FPGA.
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.
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.
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.
Analysis and Comparison of Different Spectrum Sensing Technique for WLANijtsrd
This Paper explores basic two systems of spectrum sensing Cooperative System and Non Cooperative System. Non Cooperative System includes Energy detector, Match Filter and cyclostationary with a performance analysis of transmitter based detection. It also includes analysis of Match Filter and Cyclostationary under low and high SNR, validating the result and applied the technique for Wireless local Area Network WLAN . To identify the no. of detected signal, chi square equation has been solved and finds the threshold. It has been observed during analysis that energy rises at high SNR under AWGN and under high SNR no. of detected signal decreases gradually when the no. of sample increases. When no. of sample increases then the no. of detected signal increases. The results of the detection techniques are reliable in comparison. Energy detection provides good result under high SNR values. All of the simulation work is done in MATLAB software and finalized the best detection technique for spectrum sensing. Abrar Ahmed | Rashmi Raj "Analysis and Comparison of Different Spectrum Sensing Technique for WLAN" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-6 , October 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29174.pdf Paper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/29174/analysis-and-comparison-of-different-spectrum-sensing-technique-for-wlan/abrar-ahmed
Receive Antenna Diversity and Subset Selection in MIMO Communication SystemsIDES Editor
The performance of Multiple-input Multiple-output
(MIMO) systems can be improved by employing a larger
number of antennas than actually used or selected subset of
antennas. Most of the existing antenna selection algorithms
assume perfect channel knowledge and optimize criteria such
as Shannon’s capacity on bit error rates. The proposed work
examines Antenna diversity and optimal/ sub optimal receive
strategy in antenna selection. The numerical results for BER,
Information capacity with SNR are obtained using mat lab
Performance Analysis of Noise Uncertainty in Energy Detection Spectrum Sensin...Onyebuchi nosiri
Abstract—The Performance of Energy Detection (ED) spectrum sensing technique depends on threshold selected for deciding the presence or absence of Primary User. In practice, noise density is uncertain and can affect the performance of ED in that sometimes presence of signals is confused for their absence (noise) and vice versa. The traditional energy detection algorithm was based on fixed threshold and has been observed to be inefficient under noise uncertainty. The technique requires optimizing the threshold to be more flexible to check the noise uncertainty effects. The paper therefore proposed an algorithm relative to a unique environment which in effect considered the dynamism relatively and dependent on the environment. The results obtained demonstrated significant improvement compared to the traditional energy detection system
Narrowband Spectrum Sensing for Different Fading Channels for Cognitive Radio...IJMERJOURNAL
Abstract: Nowadays the demand of applications of wireless communication has increased rapidly which causes the scarcity of radio spectrum. To empower future wireless communication services, the radio spectrum management is a very important factor. Cognitiveradio is a promising technology which provides an innovative way to improve utilization efficiency of available electromagnetic spectrum by sensing spectrum and shares it without harmful interference to other users. Narrowband spectrum sensing is the technique where the bandwidth of active primary transmitter in the vicinity of cognitive radio is less than the coherence bandwidth of channel. Fading is one of the greatest impairment of narrowband spectrum sensing. It is deflection of the attenuation. It influences a signal over certain propagation media.A communication channel that experiences fading isknown as fading channel. The effects of fading can be reduced by several fading models. In this paper, performanceanalysis of several realistic fading models on narrowband channel using energy detection method is employed. Finally, performance comparison of various fading models is guaranteed through simulation.
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.
Performance Evaluation of Computationally Efficient Energy Detection Based Sp...IJRST Journal
The rapid growth of bandwidth demanding wireless technologies has led to the problem of spectrum scarcity. However, studies show that licensed spectrum is underutilized. Cognitive radio technology promises a solution to the problem by allowing unlicensed users, access to the licensed bands opportunistically. A prime component of the cognitive radio technology is spectrum sensing. Many spectrum sensing techniques have been developed to sense the presence or not of a licensed user. This paper evaluates the performance of the energy detection based spectrum sensing technique in noisy, fading, jamming, interference environments. Both single user detection and cooperative detection situations were investigated. Closed form solutions for the probabilities of detection and false alarm were derived. The analytical results were varied by numerical computations using Monte Carlo method with MATLAB. The performance of the computationally efficient energy detection (CE-ED) techniques were evaluated by use of Receiver Operating Characteristics (ROC) curves over additive white Gaussian noise (AWGN) and fading (Rayleigh & Nakagami-m) channels. Results show that for single user detection, the energy detection technique performs better in AWGN channel than in the fading channel models. The performance of cooperative detection is better than single user detection in fading environments.
Design Analysis and Simulation of 25 TAP FIR Raised Cosine Filter IJEEE
Pulse shaping filter plays an important in multirate signal processing for Software Defined Radio based wireless and mobile applications. In this paper Raised Cosine filter has been presented for pulse shaping using Kaiser and Gaussian window techniques. The raised cosine filter introduces group delay that causes ISI in wireless communication. The ISI due to group delay can be removed by delaying the input signal to the filter. The ISI can also be rejected by reduced roll off factor α which results in narrow transition width. The proposed filter has been designed and simulated using Matlab. The simulated results show that the performance of both window techniques are almost same but Gaussian window based pulse shaping filter provides improved stop band attenuation is better as compared to Kaiser window technique.
Finger Vein Detection using Gabor Filter, Segmentation and Matched FilterEditor IJCATR
This paper propose a method of personal identification based on finger-vein patterns. An image of a finger captured by the web camera under the IR light transmission contains not only the vein pattern itself; but also shade produced by various thickness of the finger muscles; bones; and tissue networks surrounding the vein. In this paper; we intro-duce preliminary process to enhance the image quality worsened by light effect and noise produced by the web camera; then segment the vein pattern by using adaptive threshold method and matched them using improved template matching. The main purposes of this paper are to investigate finger-vein technology; the applicable fields and whether finger-vein detection can solve the problems fingerprint detection imposes in certain industries
A SURVEY ON OPTIMIZATION BASED SPECTRUM SENSING TECHNIQUES TO REDUCE ISI AND ...IJNSA Journal
Cognitive radio is emerging technologies in OFDM based wireless systems which are very important for spectrum sensing. By using cognitive radio (CR) high data can be transferred with low bit error rate. The key idea of OFDM is to split the total transmission bandwidth into the subcarriers which further reduce the intersymbol interference (ISI) and peak to average power ratio(PAPR) in the signal. There are many optimization based spectrum sensing techniques are existing for efficient sensing purpose but each has its own advantages and disadvantages. This leads to start the comprehensive study for reducing PAPR and ISI(Intersymbol interference) in terms of FPGA based partial configuration. In the first part of review OFDM characteristics of the signal has compared with several optimizations based ISI reduction techniques. The second part is to compare the various spectrum sensing techniques in cognitive radio engine and its application in FPGA.
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.
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.
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.
Analysis and Comparison of Different Spectrum Sensing Technique for WLANijtsrd
This Paper explores basic two systems of spectrum sensing Cooperative System and Non Cooperative System. Non Cooperative System includes Energy detector, Match Filter and cyclostationary with a performance analysis of transmitter based detection. It also includes analysis of Match Filter and Cyclostationary under low and high SNR, validating the result and applied the technique for Wireless local Area Network WLAN . To identify the no. of detected signal, chi square equation has been solved and finds the threshold. It has been observed during analysis that energy rises at high SNR under AWGN and under high SNR no. of detected signal decreases gradually when the no. of sample increases. When no. of sample increases then the no. of detected signal increases. The results of the detection techniques are reliable in comparison. Energy detection provides good result under high SNR values. All of the simulation work is done in MATLAB software and finalized the best detection technique for spectrum sensing. Abrar Ahmed | Rashmi Raj "Analysis and Comparison of Different Spectrum Sensing Technique for WLAN" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-6 , October 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29174.pdf Paper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/29174/analysis-and-comparison-of-different-spectrum-sensing-technique-for-wlan/abrar-ahmed
Receive Antenna Diversity and Subset Selection in MIMO Communication SystemsIDES Editor
The performance of Multiple-input Multiple-output
(MIMO) systems can be improved by employing a larger
number of antennas than actually used or selected subset of
antennas. Most of the existing antenna selection algorithms
assume perfect channel knowledge and optimize criteria such
as Shannon’s capacity on bit error rates. The proposed work
examines Antenna diversity and optimal/ sub optimal receive
strategy in antenna selection. The numerical results for BER,
Information capacity with SNR are obtained using mat lab
Performance Analysis of Noise Uncertainty in Energy Detection Spectrum Sensin...Onyebuchi nosiri
Abstract—The Performance of Energy Detection (ED) spectrum sensing technique depends on threshold selected for deciding the presence or absence of Primary User. In practice, noise density is uncertain and can affect the performance of ED in that sometimes presence of signals is confused for their absence (noise) and vice versa. The traditional energy detection algorithm was based on fixed threshold and has been observed to be inefficient under noise uncertainty. The technique requires optimizing the threshold to be more flexible to check the noise uncertainty effects. The paper therefore proposed an algorithm relative to a unique environment which in effect considered the dynamism relatively and dependent on the environment. The results obtained demonstrated significant improvement compared to the traditional energy detection system
Narrowband Spectrum Sensing for Different Fading Channels for Cognitive Radio...IJMERJOURNAL
Abstract: Nowadays the demand of applications of wireless communication has increased rapidly which causes the scarcity of radio spectrum. To empower future wireless communication services, the radio spectrum management is a very important factor. Cognitiveradio is a promising technology which provides an innovative way to improve utilization efficiency of available electromagnetic spectrum by sensing spectrum and shares it without harmful interference to other users. Narrowband spectrum sensing is the technique where the bandwidth of active primary transmitter in the vicinity of cognitive radio is less than the coherence bandwidth of channel. Fading is one of the greatest impairment of narrowband spectrum sensing. It is deflection of the attenuation. It influences a signal over certain propagation media.A communication channel that experiences fading isknown as fading channel. The effects of fading can be reduced by several fading models. In this paper, performanceanalysis of several realistic fading models on narrowband channel using energy detection method is employed. Finally, performance comparison of various fading models is guaranteed through simulation.
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.
Performance Evaluation of Computationally Efficient Energy Detection Based Sp...IJRST Journal
The rapid growth of bandwidth demanding wireless technologies has led to the problem of spectrum scarcity. However, studies show that licensed spectrum is underutilized. Cognitive radio technology promises a solution to the problem by allowing unlicensed users, access to the licensed bands opportunistically. A prime component of the cognitive radio technology is spectrum sensing. Many spectrum sensing techniques have been developed to sense the presence or not of a licensed user. This paper evaluates the performance of the energy detection based spectrum sensing technique in noisy, fading, jamming, interference environments. Both single user detection and cooperative detection situations were investigated. Closed form solutions for the probabilities of detection and false alarm were derived. The analytical results were varied by numerical computations using Monte Carlo method with MATLAB. The performance of the computationally efficient energy detection (CE-ED) techniques were evaluated by use of Receiver Operating Characteristics (ROC) curves over additive white Gaussian noise (AWGN) and fading (Rayleigh & Nakagami-m) channels. Results show that for single user detection, the energy detection technique performs better in AWGN channel than in the fading channel models. The performance of cooperative detection is better than single user detection in fading environments.
Design Analysis and Simulation of 25 TAP FIR Raised Cosine Filter IJEEE
Pulse shaping filter plays an important in multirate signal processing for Software Defined Radio based wireless and mobile applications. In this paper Raised Cosine filter has been presented for pulse shaping using Kaiser and Gaussian window techniques. The raised cosine filter introduces group delay that causes ISI in wireless communication. The ISI due to group delay can be removed by delaying the input signal to the filter. The ISI can also be rejected by reduced roll off factor α which results in narrow transition width. The proposed filter has been designed and simulated using Matlab. The simulated results show that the performance of both window techniques are almost same but Gaussian window based pulse shaping filter provides improved stop band attenuation is better as compared to Kaiser window technique.
Finger Vein Detection using Gabor Filter, Segmentation and Matched FilterEditor IJCATR
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Performance Analysis and Comparative Study of Cognitive Radio Spectrum Sensin...IOSR Journals
Abstract : 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. Keywords - Cognitive radio, cooperative spectrum sensing, energy detector, spectrum sensing, hard combination
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.
An Approach to Spectrum Sensing in Cognitive RadioIOSR Journals
Abstract: 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. Keywords— Include at least 5 keywords or phrases
Performance Comparison of Energy Detection Based Spectrum Sensing for Cogniti...irjes
With the rapid deployment of new wireless devices and applications, the last decade has witnessed a growing
demand for wireless radio spectrum. However, the policy of fixed spectrum assignment produces a bottleneck for more
efficient spectrum utilization, such that a great portion of the licensed spectrum is severely under-utilized. So the concept of
cognitive radio was introduced to address this issue.The inefficient usage of the limited spectrum necessitates the
development of dynamic spectrum access techniques, where users who have no spectrum licenses, also known as secondary
users, are allowed to use the temporarily unused licensed spectrum. For this purpose we have to know the presence or
absence of primary users for spectrum usage. So spectrums sensing is one of the major requirements of cognitive radio.Many
spectrum sensing techniques have been developed to sense the presence or absence of a licensed user. This paper evaluates
the performance of the energy detection based spectrum sensing technique in noisy and fading environments.The
performance of the energy detection technique will be evaluated by use of Receiver Operating Characteristics (ROC) curves
over additive white Gaussian noise (AWGN) and fading channels.
IMPLEMENTATION OF A BPSK MODULATION BASED COGNITIVE RADIO SYSTEM USING THE EN...cscpconf
We present in this work an energy detection algorithm, based on spectral power estimation, in
the context of cognitive radio. The algorithm is based on the Neyman-Pearson test where the
robustness of the appropriate spectral bands identification, is based, at one hand, on the
‘judicious’ choice of the probability of detection (PD) and false alarm probability (PF). First, we
accomplish a comparative study between two techniques for estimation of PSD (Power Spectral
Density): the periodogram and Welch methods. Also, the interest is focused on the choice of the
optimal duration of observation where we can state that this latter one should be inversely
proportional to the level of the SNR of the transmitted signal to be sensed. The developed
algorithm is applied in the context of cognitive radio. The algorithm aims to identify the free
spectral bands representing, reserved for the primary user, of the signal carrying information,
issued from an ASCII encoding alphanumeric message and utilizing the BPSK modulation,
transmitted through an AWGN (Added White Gaussian Noise) channel. The algorithm succeeds
in identifying the free spectral bands even for low SNR lev
Implementation of a bpsk modulation based cognitive radio system using the en...csandit
We present in this work an energy detection algorit
hm, based on spectral power estimation, in
the context of cognitive radio. The algorithm is ba
sed on the Neyman-Pearson test where the
robustness of the appropriate spectral bands identi
fication, is based, at one hand, on the
‘judicious’ choice of the probability of detection
(P
D
) and false alarm probability (P
F
). First, we
accomplish a comparative study between two techniqu
es for estimation of PSD (Power Spectral
Density): the periodogram and Welch methods. Also,
the interest is focused on the choice of the
optimal duration of observation where we can state
that this latter one should be inversely
proportional to the level of the SNR of the transmi
tted signal to be sensed. The developed
algorithm is applied in the context of cognitive ra
dio. The algorithm aims to identify the free
spectral bands representing, reserved for the prima
ry user, of the signal carrying information,
issued from an ASCII encoding alphanumeric message
and utilizing the BPSK modulation,
transmitted through an AWGN (Added White Gaussian N
oise) channel. The algorithm succeeds
in identifying the free spectral bands even for low
SNR levels (e.g. to -2 dB) and allocate them
to the informative signal representing the secondar
y user.
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.
Performance Evaluation of Energy Detector Based Spectrum Sensing for Cognitiv...IJECEIAES
This paper presents the performance evaluation of the Energy Detector technique, which is one of the most popular Spectrum Sensing (SS) technique for Cognitive Radio (CR). SS is the ability to detect the presence of a Primary User (PU) (i.e. licensed user) in order to allow a Secondary User (SU) (i.e unlicensed user) to access PU’s frequency band using CR, so that the available frequency bands can be used efficiently. We used for implementation an Universal Software Radio Peripheral (USRP), which is the most used Software Defined Radio (SDR) device for research in wireless communications. Experimental measurements show that the Energy Detector can obtain good performances in low Signal to Noise Ratio (SNR) values. Furthermore, computer simulations using MATLAB are closer to those of USRP measurements.
An Optimized Energy Detection Scheme For Spectrum Sensing In Cognitive RadioIJERD Editor
With rapid growth of wireless devices, the Scarcity of Spectrum resources arises ,due to the improper and inefficient usage of available spectrum band. This problem can be alleviated by Cognitive radio . The major function of the cognitive radio rely on efficient sensing of available spectrum and Spectrum sensing techniques have been used to enhance the detection performance. Among these techniques, Energy detection is considered to be the implemented in practice because of less complexity. In this paper we propose an Adaptive threshold scheme which improves the detection performance under low SNR region. In this paper, noise uncertainty factor is considered wherein the Probability of error is minimized in various SNR regions.
Comparison of Energy Detection Based Spectrum Sensing Methods over Fading Cha...CSCJournals
With the advance of wireless communications, the problem of bandwidth scarcity has become more prominent. Cognitive radio technology has come out as a way to solve this problem by allowing the unlicensed users to use the licensed bands opportunistically. To sense the existence of licensed users, many spectrum sensing techniques have been devised. This paper presents the energy detection based spectrum sensing technique. In the present work, the comparison of ROC curves has been done for various wireless fading channels using squaring and cubing operation. The improvement has gone as high as up to 0.6 times for AWGN channel and 0.4 times for Rayleigh channel as we go from squaring to cubing operation in an energy detector
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
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IJCER (www.ijceronline.com) International Journal of computational Engineering research
1. International Journal Of Computational Engineering Research (ijceronline.com) Vol. 2 Issue. 5
Performance analysis of Energy detection, Matched filter detection &
Cyclostationary feature detection Spectrum Sensing Techniques
Mr. Pradeep Kumar Verma1, Mr. Sachin Taluja2, Prof. Rajeshwar Lal Dua3
1
M.Tech Scholar, Department of Electronics & Communication Engineering, Jaipur National University, Jaipur, India
2
M.Tech Scholar, Department of Electronics & Communication Engineering, Jaipur National University, Jaipur, India
3
HOD, Electronics & Communication Engineering, Jaipur National University, Jaipur, India.
Abstract- The growing demand of wireless applications has put a lot of constraints on the usage of available radio
spectrum which is limited and precious resource. However, a fixed spectrum assignment has lead to under utilization of
spectrum as a great portion of licensed spectrum is not effectively utilized. Cognitive radio is a promising technology
which provides a novel way to improve utilization efficiency of available electromagnetic spectrum. Spectrum sensing
helps to detect the spectrum holes (underutilized bands of the spectrum) providing h i g h s p e c t r a l r e s o l u t i o n
capability. T h i s i s a r e v i e w p a p e r that compares the performance of three main spectrum s e n s i n g techniques.
Keywords- Cognitive Radio (CR), Energy Detection (ED), Matched Filter Detection (MFD), Cyclostationary feature
Detection.
I. Introduction
The available radio spectrum is limited and it is getting crowded day by day as there is increase in the number of wireless
devices and applications. In the studies it has been found that the allocated radio spectrum is underutilized because it has
been statistically allocated not dynamically (allocated when needed). Also the approach of radio spectrum management is
not flexible, since, each wireless operator is assigned a license to operate in a certain frequency band. In the present
scenario, it has been found out that these allocated radio spectrums are free 15% to 85% most of the time i.e. they are
inefficiently used depending upon the geographical area. Since most of the useful radio spectrum already allocated, it is
difficult to find vacant frequency bands to either deploy new services or to enhance the existing ones. In order to overcome
this situation, we need to come up with a means for improved utilization of the spectrum creating opportunities for dynamic
spectrum access. [1]-[3].
The issue of spectrum underutilization in wireless communication can be solved in a better way using Cognitive Radio.
Cognitive Radio is characterized by the fact that it can adapt according to the environment by changing its
transmitting parameters, such as modulation, frequency, frame format, etc. T he main challenges with cognitive
radios are that it should not interfere with the licensed users and should vacate the band when required. For this
it should sense the signals faster. This work focuses on the spectrum sensing techniques that are based on primary
transmitter detection. In this category, three major spectrum sensing techniques “energy detection”, “matched filter
detection”, and “cyclostationary feature detection” are addressed. This paper involves the comparative analysis of these
spectrum sensing techniques for efficient working of cognitive radios.
II. Cognitive Radio
The concept behind the Cognitive users is that they have the ability to continuously sense the licensed
spectrum to search the unused locations, once the hollow locations are identified; Cognitive radio users utilize
those locations for transmission without interrupting the primary users. [4].The primary aim of a cognitive radio
system is to get hold of a best available channel by using the cognitive capability and re-configurability. Cognitive
capability is defined as the capacity of the radio system to gather information from the surroundings [5]. It
requires very complex or sophisticated techniques in order to observe the sudden variations and changes in the
radio environment without interfering with the existing users. Cognitive capability plays a major role to identify
the unused or white spaces in the frequency spectrum at a particular time so as to select a suitable spectrum
along with the suitable operating parameters. These unused channels are called spectrum holes or white spaces
[5]. The cognitive radio enables the use of white spaces in the spectrum that become available temporarily. As soon
as the primary user returns to its band, the cognitive user switches to a different spectrum hole or may stay in
the same band but alters the power level and modulation method for avoiding interference to the existing
licensed users in that band.
III. Spectrum Sensing
A major challenge in cognitive radio is that the secondary users need to detect the presence of primary users in a
licensed spectrum and quit the frequency band as quickly as possible if the corresponding primary radio emerges in order
to avoid interference to primary users. This technique is called spectrum sensing. Spectrum sensing and estimation is the
first step to implement Cognitive Radio system [6].
Issn 2250-3005(online) September| 2012 Page 1296
2. International Journal Of Computational Engineering Research (ijceronline.com) Vol. 2 Issue. 5
Energy detection Spectrum Sensing
It is a non coherent detection method that detects the primary signal based on the sensed energy [1]. Due to its
simplicity and no requirement of a priori knowledge of primary user signal, energy detection (ED) is the most popular
sensing technique in cooperative sensing [7][8][9].
The block diagram for the energy detection technique is shown in the Figure 1. In this method, signal is passed
through band pass filter of the bandwidth W and is integrated over time interval. The output from the integrator block
is then compared to a predefined threshold. This comparison is used to discover the existence of absence of the primary
user. The threshold value can set to be fixed or variable based on the channel conditions.
The ED is said to be the Blind signal detector because it ignores the structure of the signal. It estimates the presence
of the signal by comparing the energy received with a known threshold ν derived from the statistics of the noise.
Analytically, signal detection can be reduced to a simple identification problem, formalized as a hypothesis test,
y(k ) = n(k )........................H 0
y(k ) = h ∗ s(k ) + n(k ).........H 1 (1)
Where y(k) is the sample to be analyzed at each instant k and n (k) is the noise of variance σ2 . Let y(k) be a sequence
of received samples k Є {1, 2….N} at the signal detector, then a decision rule can be stated as,
H 0 ....if ε < v
H 1 ....if ε > v (2)
2
Where ε=|E y(k)|
The estimated energy of the received signal and v is chosen to be the noise variance σ2 [10].
Fig. 1: Block diagram of Energy detection [1].
The “probability of primary user detection” and the “probability of false detection” for the energy detection
method can be calculated by the given equations [10]:
(3)
Where λ= SNR,
n= TW (Time bandwidth product)
⎡(.)= complete gamma function,
⎡(.,.)= incomplete gamma function,
Qm= Generalized Marcum function [11].
Matched Filter Spectrum Detection
A matched filter (MF) is a linear filter designed to maximize the output signal to noise ratio for a given input signal.
When secondary user has a priori knowledge of primary user signal, matched filter detection is applied. Matched filter
operation is equivalent to correlation in which the unknown signal is convolved with the filter whose impulse response is
the mirror and time shifted version of a reference signal. The operation of matched filter detection is expressed as:
∞
Y[n] =∑h[n − k]x[k ] (3)
k=-∞
Issn 2250-3005(online) September| 2012 Page 1297
3. International Journal Of Computational Engineering Research (ijceronline.com) Vol. 2 Issue. 5
Where ‘x’ is the unknown signal (vector) and is convolved with the ‘h’, the impulse response of matched filter that is
matched to the reference signal for maximizing the SNR. Detection by using matched filter is useful only in cases where
the information from the primary users is known to the cognitive users [10].
Fig. 2: Block diagram of matched Filter detection [1].
Cyclostationary feature Spectrum Detection
It exploits the periodicity in the received primary signal to identify the presence of primary users (PU). The periodicity
is commonly embedded in sinusoidal carriers, pulse trains, spreading code, hopping sequences or cyclic prefixes of the
primary signals. Due to the periodicity, these cyclostationary signals exhibit the features of periodic statistics and
spectral correlation, which is not found in stationary noise and interference [ 11].
Thus, cyclostationary feature detection is robust to noise uncertainties and performs better than energy detection in low
SNR regions. Although it requires a priori knowledge of the signal characteristics, cyclostationary feature detection is
capable of distinguishing the CR transmissions from various types of PU signals. This eliminates the synchronization
requirement of energy detection in cooperative sensing. Moreover, CR users may not be required to keep silent during
cooperative sensing and thus improving the overall CR throughput. This method has its own shortcomings owing to its
high computational complexity and long sensing time. Due to these issues, this detection method is less common than
energy detection in cooperative sensing [12].
Fig. 3: Block diagram of Cyclostationary feature detection [1].
Process flow diagrams
Fig. 4: Process flow diagram of Energy Detection. Fig. 5: Process flow diagram of Matched filter Detection.
Issn 2250-3005(online) September| 2012 Page 1298
4. International Journal Of Computational Engineering Research (ijceronline.com) Vol. 2 Issue. 5
Fig. 6: Flow diagram of Cyclostationary feature Detection.
IV. Results And Analysis
An extensive set of simulations have been conducted using the system model as described in the previous
section. T he emphasis is to analyze the comparative performance of three spectrum sensing techniques. The
performance metrics used for comparison include the “probability of primary user detection” and “probability
of false detection”. The number of channels and the number primary users considered in this analysis is
twenty five and respectively. The SNR of the channels is considered to be precisely same and the channel
model is A W G N with zero mean. The results are shown in Figure-7 and Figure-8.
Probability of Primary Detection
Figure-7 depicts the “probability of primary user detection” as a function of SN R for the three cases: (i) energy
detection, (ii) matched filter detection and (iii) cyclo-stationary feature detection.
It is observed that for energy detection and matched filter detection, much higher SNR is required to obtain a
performance comparable to cyclostationary feature detection. For energy detection, about 16 dB s higher SNR is
needed to achieve 100% probability of detection whereas for matched filter detection, about 24 dB s higher
SNR is required. For cyclostationary feature detection, 100% probability of detection is attained at -8 dB s.
Cyclostationary feature detection performs well for very low SNR, however the major disadvantage is that it
requires large observation time for occupancy detection. Matched filter detection performs well as compared to
energy detection but restriction lies in prior knowledge of user signaling. Further, cyclostationary feature
detection algorithm is complex as compared to other detection techniques.
Probability of False Detection
Figure-8 illustrates the “probability of false detection” for three transmitter detection based spectrum sensing
techniques versus SNR.
It is observed that “probability of false detection” of cyclostationary feature detection is much smaller as
compared to other two techniques. In fact, it is zero for the range of SNR considered in this study i.e., -30 dB
to + 30 dB s. It is further seen that the “probability of false detection” for energy detection technique is inversely
proportional to the SNR. At low SNR we have higher probability of false detection and at high SNR we have
lower probability o f false detection, because energy detection cannot isolate between signal and noise. T he
probability of false detection for energy detection and matched filter detection approaches zero at about +14
dB s and +8 dB s respectively.
Issn 2250-3005(online) September| 2012 Page 1299
5. International Journal Of Computational Engineering Research (ijceronline.com) Vol. 2 Issue. 5
Fig. 7: Probability of Primary Detection.
Figure 8: Probability of False Detection.
I. Conclusion
To efficiently utilize the wireless spectrum cognitive radios were introduced which opportunistically utilize the holes
present in the spectrum. The most essential aspect of a cognitive radio system is spectrum sensing and various sensing
techniques which it uses to sense the spectrum. In this paper the main focus was on Energy Detection, Matched Filter
Detection and Cyclostationary feature Detection spectrum sensing techniques. The advantage of Energy detection is
that, it does not require any prior knowledge about primary users. It does not perform well at low SNR values, it
requires a minimum SNR for its working. The result in the paper shows that Energy detection starts working at -7 dB
s of SNR. Matched filter detection is better than energy detection as it starts working at low SNR of -30 dB s.
Cyclostationary feature detection is better than both the previous detection techniques since it produces better results
at lowest SNR, i.e. for values below -30 dB s. the results shows that the performance of energy detection gets better
with increasing SNR as the “probability of primary detection” increases from zero at -14 dB s to 100% at +8 dB s and
correspondingly the “probability of false detection” improves from 100% to zero. Similar type of performance is
achieved using matched filter detection as “probability of primary detection” and the “probability of false detection”
shows improvement in SNR as it varies from -30 dB s to +8 dB s. the cyclostationary feature detection outclasses the
other two sensing techniques as 100% “probability of primary detection” and zero “probability of false detection” is
achieved at -8 dB s, but the processing time of cyclostationary feature detection is greater than the energy dete ction
and matched filter detection techniques.
References
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Authors
Pradeep Kumar Verma- Student of M. Tech (Communication and signal processing) final semester at Jaipur
National University, Jaipur. Completed B. Tech from Northern India Engineering College, Lucknow from Uttar
Pradesh Technical University in Electronics and Communications Engineering in 2009. Worked as Site Engineer
for 9 months in Telecom Industry. I have keen interest in subjects like signal and systems, digital communications,
information theory and coding and wireless communications.
Sachin Taluja M.Tech Scholar at Jaipur National University, Jaipur. He received B.E. from M.D.University Rohtak,
Haryana in Electronics and Communication . He has over 5 years of Industrial experience in the Field of Computers. His
Area of interest includes Network Security, Artificial intelligence, Communication system, Computer architecture, Wireless
Communications, Digital Communications, fiber optics, Nano Technology. He has attended various workshops on different
domains of computers.
Professor Rajeshwar Lal Dua – He is a fellow life member of IETE and also a life member of I.V.S & I.P.A, former -
scientist F of the Central Electronics Engineering Research Institute (CEERI), Pilani. Has been one of the most w ell
known scientists in India in the field of Vaccum Electronics Devices for over the and half decades. His professional
achievements span a wide area of vaccum microwave devices ranging from crossed -field and linear-beam devices to
present-day gyrotrons. He was awarded a degree of M. Sc (Physics) and M. Sc Tech (Electronics) from BITS Pilani. He
started his professional carrier in 1966 at Central Electronics Engineering Research Institute (CEERI), Pilani. During
this period he designed and developed a specific high power Magnetron for defense and batch produced about 100 tubes
for their use. Trained the Engineers of Industries with know how transfer for further production of the same.
In 1979 he visited department of Electrical and Electronics Engineering at the University of Sheffield (UK) in the capacity
of independent research worker and Engineering Department of Cambridge University Cambridge (UK) as a visiting
scientist. He has an experience of about 38 years in area of research and development in Microwave field with several
papers and a patent to his credit. In 2003 retired as scientist from CEERI, PILANI & shifted to Jaipur and joined the
profession of teaching. From last eight years he is working as professor and head of electronics department in various
engineering colleges. At present he is working as head and Professor in the department of Electronics and communication
engineering at JNU, Jaipur. He has guided several thesis of M.tech .of many Universities.
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