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
DATA FALSIFICATION LENIENT SECURE SPECTRUM SENSING BY COGNITIVE USER RELIABIL...IAEME Publication
Cognitive radio network’s primary challenge is sensing of primary user signal and efficiently handling the spectrum availability. Spectrum sensing is the way ahead and vital for Dynamic Spectrum Access, where malicious users deploy Spectrum Sensing Data Falsification (SSDF) attacks. This paper discusses the technique to calculate the importance of using nodes for primary as well as secondary users. It prevents spectrum problems to primary users from Spectrum Sensing Data Falsification by secondary us ers and also shields secondary users from unauthorized primary users. Simulation runs of the novel approach using usual network conditions and SSDF attacks greatly bought down the error rate of spectrum decision and at the same time improved the detection rate of malicious cognitive nodes.
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
Performance evaluation of various cooperative spectrum sensing algorithms for...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Welcome to International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
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.
Spectrum Sensing in Cognitive Radio Networks : QoS Considerations csandit
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.
DATA FALSIFICATION LENIENT SECURE SPECTRUM SENSING BY COGNITIVE USER RELIABIL...IAEME Publication
Cognitive radio network’s primary challenge is sensing of primary user signal and efficiently handling the spectrum availability. Spectrum sensing is the way ahead and vital for Dynamic Spectrum Access, where malicious users deploy Spectrum Sensing Data Falsification (SSDF) attacks. This paper discusses the technique to calculate the importance of using nodes for primary as well as secondary users. It prevents spectrum problems to primary users from Spectrum Sensing Data Falsification by secondary us ers and also shields secondary users from unauthorized primary users. Simulation runs of the novel approach using usual network conditions and SSDF attacks greatly bought down the error rate of spectrum decision and at the same time improved the detection rate of malicious cognitive nodes.
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
Performance evaluation of various cooperative spectrum sensing algorithms for...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Welcome to International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
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.
Spectrum Sensing in Cognitive Radio Networks : QoS Considerations csandit
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.
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.
Transferring quantum information through theijngnjournal
Transmission of information in the form of qubits much faster than the speed of light is the important
aspects of quantum information theory. Quantum information processing exploits the quantum nature of
information that needs to be stored, encoded, transmit, receive and decode the information in the form of
qubits. Bosonic channels appear to be very attractive for the physical implementation of quantum
communication. This paper does the study of quantum channels and how best it can be implemented with
the existing infrastructure that is the classical communication. Multiple access to the quantum network is
the requirement where multiple users want to transmit their quantum information simultaneously without
interfering with each others.
Hybrid Spectrum Sensing Method for Cognitive Radio IJECEIAES
With exponential rise in the internet applications and wireless communications, higher and efficient data transfer rates are required. Hence proper and effective spectrum is the need of the hour, As spectrum demand increases there are limited number of bands available to send and receive the data. Optimizing the use of these bands efficiently is one of the tedious tasks. Various techniques are used to send the data at same time, but for that we have to know which bands are free before sending the data. For this purpose various spectrum sensing approaches came with variety of solutions. In this paper the sensing problem is tackled with the use of hybrid spectrum sensing method, This new networking paradox uses the Centralized concept of spectrum sensing and creates one of the most trusted spectrums sensing mechanism. This proposed technique is simulated using MATLAB software.This paper also provides comparative study of various spectrum sensing methodologies.
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 small vessel detection using a co-located multi-frequency FMCW MIMO radar IJECEIAES
Small vessels detection is a known issue due to its low radar cross section (RCS). An existing shore-based vessel tracking radar is for long-distance commercial vessels detection. Meanwhile, a vessel-mounted radar system known for its reliability has a limitation due to its single radar coverage. The paper presented a co-located frequency modulated continuous waveform (FMCW) maritime radar for small vessel detection utilising a multiple-input multiple-output (MIMO) configuration. The radar behaviour is numerically simulated for detecting a Swerling 1 target which resembles small maritime’s vessels. The simulated MIMO configuration comprised two transmitting and receiving nodes. The proposal is to utilize a multi-frequency FMCW MIMO configuration in a maritime environment by applying the spectrum averaging (SA) to fuse MIMO received signals for range and velocity estimation. The analysis was summarised and displayed in terms of estimation error performance, probability of error and average error. The simulation outcomes an improvement of 2.2 dB for a static target, and 0.1 dB for a moving target, in resulting the 20% probability of range error with the MIMO setup. A moving vessel's effect was observed to degrade the range error estimation performance between 0.6 to 2.7 dB. Meanwhile, the proposed method was proven to improve the 20% probability of velocity error by 1.75 dB. The impact of multi-frequency MIMO was also observed to produce better average error performance.
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.
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 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.
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
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.
SELECTION OF SPECTRUM SENSING METHOD TO ENHANCE QOS IN COGNITIVE RADIO NETWORKSijwmn
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.
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 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.
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.
Transferring quantum information through theijngnjournal
Transmission of information in the form of qubits much faster than the speed of light is the important
aspects of quantum information theory. Quantum information processing exploits the quantum nature of
information that needs to be stored, encoded, transmit, receive and decode the information in the form of
qubits. Bosonic channels appear to be very attractive for the physical implementation of quantum
communication. This paper does the study of quantum channels and how best it can be implemented with
the existing infrastructure that is the classical communication. Multiple access to the quantum network is
the requirement where multiple users want to transmit their quantum information simultaneously without
interfering with each others.
Hybrid Spectrum Sensing Method for Cognitive Radio IJECEIAES
With exponential rise in the internet applications and wireless communications, higher and efficient data transfer rates are required. Hence proper and effective spectrum is the need of the hour, As spectrum demand increases there are limited number of bands available to send and receive the data. Optimizing the use of these bands efficiently is one of the tedious tasks. Various techniques are used to send the data at same time, but for that we have to know which bands are free before sending the data. For this purpose various spectrum sensing approaches came with variety of solutions. In this paper the sensing problem is tackled with the use of hybrid spectrum sensing method, This new networking paradox uses the Centralized concept of spectrum sensing and creates one of the most trusted spectrums sensing mechanism. This proposed technique is simulated using MATLAB software.This paper also provides comparative study of various spectrum sensing methodologies.
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 small vessel detection using a co-located multi-frequency FMCW MIMO radar IJECEIAES
Small vessels detection is a known issue due to its low radar cross section (RCS). An existing shore-based vessel tracking radar is for long-distance commercial vessels detection. Meanwhile, a vessel-mounted radar system known for its reliability has a limitation due to its single radar coverage. The paper presented a co-located frequency modulated continuous waveform (FMCW) maritime radar for small vessel detection utilising a multiple-input multiple-output (MIMO) configuration. The radar behaviour is numerically simulated for detecting a Swerling 1 target which resembles small maritime’s vessels. The simulated MIMO configuration comprised two transmitting and receiving nodes. The proposal is to utilize a multi-frequency FMCW MIMO configuration in a maritime environment by applying the spectrum averaging (SA) to fuse MIMO received signals for range and velocity estimation. The analysis was summarised and displayed in terms of estimation error performance, probability of error and average error. The simulation outcomes an improvement of 2.2 dB for a static target, and 0.1 dB for a moving target, in resulting the 20% probability of range error with the MIMO setup. A moving vessel's effect was observed to degrade the range error estimation performance between 0.6 to 2.7 dB. Meanwhile, the proposed method was proven to improve the 20% probability of velocity error by 1.75 dB. The impact of multi-frequency MIMO was also observed to produce better average error performance.
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.
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 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.
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
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.
SELECTION OF SPECTRUM SENSING METHOD TO ENHANCE QOS IN COGNITIVE RADIO NETWORKSijwmn
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.
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 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.
Signal classification of second order cyclostationarity signals using bt scld...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
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.
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.
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.
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.
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.
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.
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Runway Orientation Based on the Wind Rose Diagram.pptx
Spectrum Sensing using Cooperative Energy Detection Method for Cognitive Radio
1. Proceedings of IOE Graduate Conference, Vol. 1, Nov 2013 91
Spectrum Sensing using Cooperative Energy Detection
Method for Cognitive Radio
Saroj Dhakal, Sharad Kumar Ghimire
Department of Electronics and Computer Engineering, IOE, Central Campus, Pulchowk, Tribhuvan University, Nepal
saroj_dhakal@live.com
Abstract: In order to utilize the spectrum efficiently, the role of spectrum sensing is essential in cognitive
radio networks. The transmitter detection based techniques, energy detection, cyclostationary feature
detection, and matched filter detections are most commonly used for the spectrum sensing. However,
detection performance in practice is often compromised with multipath fading, shadowing and receiver
uncertainty issues. To mitigate the impact of these issues, cooperative spectrum sensing has been shown to
be an effective method to improve the detection performance by exploiting spatial diversity. The main idea
of cooperative sensing is to enhance the sensing performance by exploiting the spatial diversity in the
observations of spatially located CR users. By cooperation, CR users could share their sensing information
for making a combined decision more accurate than the individual decisions. Thus the Cooperative sensing
can formulate excellent use of network assets and make the network smooth.
Keywords: Cognitive radio, radio spectrum, spectrum sensing, cooperative sensing, detection probability.
1. INTRODUCTION
In CR network, each CR user in the primitive sense is to
detect licensed (primary) users if they are present and
also identify if they are absent. This is achieved by a
process called spectrum sensing. The objective of
spectrum sensing are twofold i.e., CR users should not
cause interference to PUs and CR users should efficiently
identify and exploit spectrum holes for required
throughputs and quality of services. Thus the detection
performance can be primarily determined on the basis of
two metrics i.e., probability of false alarm, which denotes
the probability of a CR user declaring that a PU is present
when the spectrum is actually free, and probability of
detection, which denotes the probability of a CR user
declaring that a PU is present when the spectrum is
indeed occupied by the PU. Since a miss in the detection
will cause the interference with the PU and a false alarm
will reduce the spectral efficiency, it is usually required
for optimal detection performance that the probability of
detection is maximized subject to the constraint of the
probability of false alarm. In practice, several factors
such as multipath fading, shadowing and, consequently,
the hidden terminal problem may affect the detector’s
performance. These factors could be, however, mitigated
if the CR users shared their sensing results with the other
CRs. This mechanism is called cooperative spectrum
sensing [1]. This scenario can be illustrated as below
figure.
Due to this multipath fading and shadowing the signal to
noise ratio (SNR) of the received primary signal can be
quite small and detection task may very difficult. Since
the receiver sensitivity indicates that the capability of
detecting weak signal.
Figure 1: Receiver uncertainty and multipath fading
2. SPECTRUM SENSING CHALLENGES
Before the detail discussion of the spectrum sensing
techniques, some of the challenges associated with
spectrum sensing are mentioned.
Hardware requirements
In cognitive radio networks [2] analogue to digital
converter with high speed processors, high resolution and
with dynamic range are required for spectrum sensing.
Therefore, terminals are essential for processing
transmission for any opportunity over a much wide band.
Hence in order to identify and spectrum opportunity the
CR should be in a position to capture and analysed a
larger band. Radio frequency (RF) components are
imposed on additional requirements by larger operating
bandwidth such as antennas and power amplifiers.
Hidden primary user problem
This hidden primary user problem is like the hidden node
dilemma in Carrier Sense Multiple Accessing (CSMA)
[3]. Many factors like shadowing or severe multipath
fading which is observed by secondary user during the
2. Proceedings of IOE Graduate Conference, Vol. 1, Nov 2013 92
transmission scanning for the primary user, create this
hidden primary user problem.
Figure 2: Hidden primary user problem in CR System [3].
Figure above illustrates the hidden node problem while
the operating ranges for the primary user (PU) and for the
cognitive radio device are shown by dashed lines.
Detecting spread spectrum primary users
A DSSS device resembles the FHSS devices but they
utilize a single band in order to spread their energy.
Primary users (PUs) which use spread spectrum
signalling are hard to identify as the power of the PUs is
dispersed over a broad frequency range, while the real
information bandwidth is much narrower [4]. A partial
solution of this problem is that if I know the hopping
pattern and method of perfect synchronization, but it is
possible but not easy to develop such an algorithm
through which estimation in code dimension is possible.
Sensing duration and frequency
As the CR operates in the bands of primary users, these
bands can be claimed by primary users at any time so in
order to avoid interference to and for PU, the CR should
be so sensible that it could identify the presence of the
PU and leave the band immediately. Hence within certain
duration, the CR should identify the presence of the PU.
Although these conditions put some complexity and
challenge for the design of CR, the sensing frequency is a
key parameter which should be chosen carefully. Sensing
frequency requirements can be relaxed if the status of the
PU is going to change slowly. For example in the case of
TV channel detection, in a geographical area presence of
a TV channel does not change frequency unless an
existing channel goes off or a new channel starts
broadcasting. Sensing period for IEEE 802.22 draft
standard is 30 seconds. Except sensing frequency, other
timing related parameters like channel move time and
channel detection time etc, are also defined in the
standard [5].
Decision fusion in cooperative sensing
For the case of cooperative sensing all results due to
various measurements and sharing information among
CR was a difficult task. There are two types of decisions
i.e.; soft and hard decisions, based on shared information
made by each cognitive device [6]. The results existing in
[6], illustrates that soft information made by each
outperforms hard information combining techniques in
term of the possibility of missed opportunity. While on
the other hand when cooperative users are high, hard
decisions perform as good as soft decisions. A variety of
simpler schemes for combining results are exploited in
[7].
Security
The cognitive radio air interface can be modified by a
malicious user to mimic a primary user. Hence primary
users can be misleading during the spectrum sensing
process. Such a behaviour or attack is called primary user
emulation (PUE) attack. The transmitter position is used
to identify an attacker in [8]. A challenging problem is to
develop valuable countermeasure when an attack is
identified. In order to prevent secondary users masked as
primary users, public key encryption based primary user
recognition is proposed in [9]. An encrypted value which
is generated using a private key is required to transmit
with the transmission of legitimate primary users.
3. ELEMENTS OF COOPERATIVE SPECTRUM
SENSING
The conventional cooperative sensing is generally
considered as a three-step process i.e., local sensing,
reporting, and data fusion. The overall elements used for
cooperative sensing as follows.
Fig3: Element of cooperative sensing [1]
Cooperation models
I considered the most popular parallel fusion network
models and recently developed game theoretical models.
For this paper preferred primarily fusion model only.
Sensing techniques
It used to sense the RF environment, taking observation
samples, and employing signal processing techniques for
detecting the PU signal or the available spectrum. The
3. Proceedings of IOE Graduate Conference, Vol. 1, Nov 2013 93
choice of the sensing technique has the effect on how CR
users cooperate with each other.
Hypothesis testing
It is a statistical test to determine the presence or absence
of a PU. This test can be performed individually by each
cooperating user for local decisions or performed by the
fusion centre for cooperative decision.
Control channel and reporting
It concerns about how the sensing results obtained by
cooperating CR users can be efficiently and reliably
reported to the fusion centre.
Data fusion
It is the process of combining the reported or shared
sensing results for making the cooperative decision.
User selection
It deals with how to optimally select the cooperating CR
users and determine the proper cooperation
footprint/range to maximize the cooperative gain and
minimize the cooperation overhead.
Knowledge base
It stores the information and facilitates the cooperative
sensing process to improve the detection performance.
4. CLASSIFICATION OF SPECTRUM SENSING
Figure 4: Classification of spectrum sensing
Figure above shows the detailed classification of
spectrum sensing techniques. They are broadly classified
into three main types, transmitter detection or non
cooperative sensing, cooperative sensing and interference
based sensing. Transmitter detection is further classified
into energy detection, matched filter detection and
cyclostationary feature detection.
Spectrum Sensing using Energy Detection
It is not coherent detection method that detects the
primary signal base on sensed energy. Due to the
simplicity in the circuit and needlessness of prior
knowledge of primary user signal .Energy detection (ED)
is the most popular sensing technique in cooperative
sensing [11].
Figure 5 : Energy detection block diagram.
The block diagram for the energy detection technique as
shown in the above figure 3.4.1.In this method signal is
passed through the band pass filter of a band with ‘W’
and is integrate over a time interval. The output from the
integrator is then compared to an already predefined
threshold. This comparison is used to discover the
existence or absence of primary user. The threshold value
can set to be fixed or variable based on channel
condition. The ED is said to be a blind signal detector
because it is unaware of the structure of the signal. It
estimates the presence of the signal by comparing the
energy received with a known threshold derived from the
statistics of the noise. Analytically signal detection can be
reduced to be a simple identification problem and
formalizer as a hypothesis test.
= … … … (1)
= h *s + … … … (2)
Where is the sample to be analysed at each instant k
and is the noise of variance 2
. Let be a
sequence of received samples k= {1, 2... N} at the signal
detector then a decision rule can be sated as
…..if ɛ >
…..if ɛ <
Where ɛ=E | the estimated energy of the received
signal and is chosen to be the noise variance 2
.
However ED has the following disadvantages as follows
i. The sensing time taken to achieve a given
probability of detection may be high.
ii. Detection performance is subjected to the
uncertainty of noise power.
iii. ED cannot be used to distinguish primary
signals from the CR user signals. Thus, CR users
need to be tightly synchronized and refrained
4. Proceedings of IOE Graduate Conference, Vol. 1, Nov 2013 94
from the transmissions during an interval called
quite period in cooperative sensing.
iv. ED cannot be used to detect spread spectrum
signals.
Match filter method
Figure 6: Block diagram of match filter method
A match filter (MF) is the linear filter design to maximize
the output signal to noise ratio for a given input signal.
When secondary user knows about the primary user
signal, a method called match filter detection, which 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 match filter detection is expressed as,
Y[n] (3)
Where X is the unknown signal and is convolved with ‘h’
the impulse response of matched filter, which is matched
to the reference signal for maximizing the SNR.
Detection using matched filter is useful only in the cases
where the information from the primary users is already
known to the cognitive users [12].
Advantages: Matched filter detection needs less detection
time because it requires only (1/SNR) samples to meet a
given probability of detection constraint. When the
information of the primary user signal is known to the
cognitive user, matched filter detection is optimal
detection in stationary Gaussian noise.
Disadvantages: Matched filter detection requires a prior
knowledge of every primary signal. If the information is
not accurate, MF performs poorly. Also, the major
disadvantage of MF is that a CR would need a dedicated
receiver for every type of primary user.
Cyclostationary feature detection
Figure 7: Cyclostationary feature detection method.
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, hoping 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. Thus
cyclostationary feature detection is robust to noise
uncertainties and performs better then energy detection in
low SNR levels. Although it requires a prior 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 requirements of energy
detection is cooperative sensing. Moreover, CR users
may not be required to keep silent during cooperative
sensing and thus improving the overall CR throughput.
This method is not encouraged to apply as it has its own
drawbacks owing to its high computational complexity
and long sensing time. Considering these issues, this
detection method is less common compared to energy
detection in cooperative sensing.
Interference based Detection
In this section I present interference based detection so
that the CR users would operate in spectrum underlay
(UWB like) approach.
Primary Receiver Detection
In general primary receiver emits the local oscillator (LO)
leakage power from its RF front end while receiving the
data from primary transmitter. This method is useful to
detect primary user by mounting a low cost sensor node
close to a primary user’s receiver in order to detect the
local oscillator (LO) leakage power emitted by the RF
front end of the primary user’s receiver which are within
the range of communication from CR system users. After
that the local sensor reports the sensed information to the
CR users so that they can identify the spectrum
occupancy status. This method can also be used to
identify the spectrum opportunities to operate CR users in
spectrum overlay.
Interference Temperature Management
Unlike the primary receiver detection, the basic idea
behind the interference temperature management is to
setup an upper interference limit for given frequency
band in specific geographic location such that the CR
users are not allowed to cause harmful interference while
using the specific band in specific area. Typically CR
user transmitters control their interference by regulating
based on where they are located with respect to the
primary users. This method basically concentrates on
measuring interference at the receiver. The operating
principle of this method is like an UWB technology,
where the CR users are allowed to coexist and transmit
simultaneously with primary users using low transmitting
power that is restricted by the interference temperature
level so as not to cause harmful interference to primary
users.
5. Proceedings of IOE Graduate Conference, Vol. 1, Nov 2013 95
Here, CR users do not perform spectrum sensing for
spectrum opportunities and can transmit right way with
specified preset power mask. However the CR users
cannot transmit their data with higher power even if the
licensed system is completely idle since they are not
allowed to transmit with higher than the preset power to
limit the interference at primary users. This is noted that
the CR users in this method should know the location and
corresponding upper level of allowed transmitted power
levels. Otherwise they will interfere with the primary user
transmissions.
Figure 8: Interference temperature model [10].
5. CLASSIFICATION OF COOPERATIVE SENSING
There are three different cooperative sensing categories
based on how CRs share data in the network i.e.,
centralized, distributed and relay-assisted. In the
centralized category, an entity called fusion centre (FC)
controls all the cooperative sensing process.
Fig 9: Centralized cooperative sensing [1]
Figure illustrated these functions as CR0 is the FC and
CR1–CR5 are cooperating CR users performing local
sensing and reporting the results back to CR0. For local
sensing, all CR users are tuned to the selected licensed
channel or frequency band where a physical point-to-
point link between the PU transmitter and each
cooperating CR user for observing the primary signal is
called a sensing channel. For data reporting, all CR users
are tuned to a control channel where a physical point-to-
point link between each cooperating CR user and the FC
for sending the sensing results is called a reporting
channel. Note that centralized cooperative sensing can
occur in either centralized or distributed CR networks. In
centralized CR networks, a CR base station (BS) is
naturally the FC. Alternatively, in CR ad hoc networks
(CRAHNs) where a CR BS is not present, any CR user
can act as a FC to coordinate cooperative sensing and
combine the sensing information from the cooperating
neighbours [4].
In distributed cooperative sensing does not rely on a FC
for making the cooperative decision. In this case, CR
users communicate among themselves and converge to a
unified decision on the presence or absence of PUs by
iterations. Figure below illustrates the cooperation in the
distributed manner.
Figure 10: Distributed cooperative sensing [1].
After local sensing, CR1–CR5 shares the local sensing
results with other users within their transmission range.
Based on a distributed algorithm, each CR user sends its
own sensing data to other users, combines its data with
the received sensing data, and decides whether or not the
PU is present by using a local criterion. If the criterion is
not satisfied, CR users send their combined results to
other users again and repeat this process until the
algorithm is converged and a decision is reached. In this
manner, this distributed scheme may take several
iterations to reach the unanimous cooperative decision
[4].
The third scheme is relay-assisted cooperative sensing. In
this scheme both sensing channel and report channel are
not perfect, a CR user observing a weak sensing channel
and a strong report channel and a CR user with a strong
sensing channel and a weak report channel, for example,
can complement and cooperate with each other to
improve the performance of cooperative sensing. Figure
illustrates the functioning of relay assisted cooperative
sensing.
Figure 11: Relay Assisted cooperative sensing [1].
6. Proceedings of IOE Graduate Conference, Vol. 1, Nov 2013 96
From figure, CR1, CR4, and CR5, who observe strong
PU signals, may suffer from a weak report channel. CR2
and CR3, who have a strong report channel, can serve as
relays to assist in forwarding the sensing results from
CR1, CR4, and CR5 to the FC. In this case, the report
channels from CR2 and CR3 to the FC can also be called
relay channels.
6. BENEFITS OF COOPERATION
Cognitive users who have a major role in a big deal to
sense the channels that have large benefits among which
the plummeting sensitivity requirements: channel
impairments like multipath fading, shadowing and
building penetration losses, impose high sensitivity
requirements inherently limited by cost and power
requirements. Employing cooperation between nodes can
drastically reduce the sensitivity requirements up to
-25dBm, and thus, reduction in sensitivity threshold can
be obtained by using this scheme agility improvement: all
topologies of cooperative network reduce detection time
compared to uncoordinated networks.
7. DISADVANTAGES OF COOPERATION
Sensing should be done from time to time at periodic
intervals by CR users as the sensed information is passed
at fast rate due to factors like mobility, channel
impairments etc., which increases the chances of data
overhead; large sensory data, since the spectrum, which
results to large amounts of data to be processed, being
inefficient in terms of cooperatively sensing data poses
lot of challenges, it could be carried out without incurring
much overhead because only approximate sensing
information is required eliminating the need for complex
signal processing schemes at the receiver side and
reducing the data load. Also even though a wide channel
has to be scanned, only a portion of it changes at a time
requiring update only the changed information and not all
the details of the entire scanned spectrum.
8. ED WITH COOPERATIVE METHOD
Step 1: Numbers of signal are received from two or more
users. Each received signal is sampled with certain
sampling frequency.
= h *s + where “i” is the number of users,
i=0, 1, β, γ….
Step 2: Estimated energy of each received signal is
calculated with noise variance .
ɛi = E |
Step 3: Integrated output signal of each user is compared
with already defined threshold value.
Step 4: Each user sends estimated energy to fusion centre
and compared with threshold value
…..if ɛi >
…..if ɛi <
Step5: Final decision at FC related to given band is based
on data fusion rule.
ɛi, ɛ {0, 1},
Where “0” (“1”) indicates the absence (presence) of
primary user,
ɛ i = decision of i-th CR user upon a given sub-band.
ɛ = final decision made at FC for the sub-band.
9. SIMULATION RESULTS
Cooperation communication has obtained much attention
because of its capability to obtain high diversity gain,
decreased transmitted power, increased system
throughput and combat fading. Diversity gain is achieved
by allowing the users to cooperate in cooperative
networks and even better performance can be achieved by
combing the cooperation with other techniques.
Figure 12: Energy detection simulation result
For simulation purpose, the graph is plotted in terms of
probability of false alarm ( ) and probability of
detection ( ). The detection performance can be mainly
determined on the basis of these two things, i.e.; the
probability of false alarm which denotes the probability
of CR users declaring that a PU is present when the
spectrum is actually free. And another one is probability
of detection, which denotes the probability of CR users
declaring that a primary user is present when the
spectrum is indeed occupied by primary user. Since a
miss in the detection will cause the interference with the
primary user and the false alarm will reduce the spectral
efficiency. Thus it is usually required for optimal
7. Proceedings of IOE Graduate Conference, Vol. 1, Nov 2013 97
detection performance that the probability of detection is
maximized subject to the constraint of the probability of
false alarm.
In above figure 12, versus simulation result at -
10dB SNR level was shown. From this simulation,
different value of probability of false alarm ( ) having
with different value of probability of detection ( are
shown. However ED is always accompanied by various
disadvantages like noise uncertainty problem, sensing
time take to achieve a given probability of detection may
be high, ED method cannot be used to distinguish
primary and secondary signal. Therefore ED method is
not useful in low SNR level applications.
Practically, Energy Detection method is best among,
different transmitter based detection method. Thus to
mitigate the issues arises in non cooperative techniques
like multipath fading, shadowing and hidden terminal
problem, cooperative ED is used.
Figure 13: Receicer Operating Characteristics for ED with
cooperative method
The ROC curve (figure 13) shows the simulation result in
terms of probability of false alarm versus probability of
detection. The simulation was done at -10db SNR level
and considering Gaussian channel. The simulation uses
the different number of users showing with different
Receiver Operating Characteristic (ROC) in above figure
13. The number of user (sensors) was considered 5, 8 and
10. If the number of users were higher the chance of
detection is maximized. The different numbers of
cognitive users are cooperates to each other and make a
centralized decision from fusion centre. This decision
may increase the chance of detection; from this
simulation result if the number of user is 10 the
probability of detection is maximum at a constant
probability of false alarm. Similarly in another side in
figure 14, if the numbers of users are minimums the
chance of misdetection is high. From another perspective
if the numbers of users are higher the chance of
probability of misdetection is also minimized using
cooperation. Hence the higher numbers of users the
chance of misdetection is minimized using cooperation,
which optimizes the spectrum utilization.
Figure 14: Complementry Receicer Operating Characteristics for ED
with cooperative method
To overcome the shortcomings of energy detection, the
other methods based on the eigenvalue of the covariance
matrix of the received signal is useful. But this method
may give the ratio of the maximum eigenvalue to the
minimum eigenvalue can be used to detect the presence
of the signal. Based on some latest random matrix
theories (RMT) [13], here quantify the distributions of
these ratios and find the detection thresholds for the
detection algorithms. The probability of false alarm and
probability of detection are also derived by using the
RMT. The methods overcome the noise uncertainty
problem and can even perform better than energy
detection when the signals to be detected are highly
correlated. The methods can be used for various signal
detection applications without knowledge of the signal,
the channel and noise power. Furthermore, different from
matched filtering, the methods do not require accurate
synchronization.
10. CONCLUSION
Cognitive radio is the promising technique for utilizing
the available spectrum optimally. The important aspect of
cognitive radio is spectrum sensing and from that
identifying the opportunistic spectrum for secondary user
communication. In this paper, different existing spectrum
sensing techniques were studied. Among them, the
performance of energy detection was simulated in non
cooperative and cooperative environment. The
performance of the ED method is presented in term of
Receiver Operating Characteristic (curves). Hence the
probability of presence or absent of the primary user is
decided using the ROC curves. The probability of false
alarm versus probability of detection or misdetection is
plotted. The ED method having uncertainty noise
variance at low SNR level is the major demerit. Besides
8. Proceedings of IOE Graduate Conference, Vol. 1, Nov 2013 98
this, it increases the probability of detection and
minimized the probability of miss detection by using
cooperation. Thus the higher number of cooperative users
gives the higher probability of detection even low SNR
level.
Hence the cooperative spectrum sensing technique is a
best technique for sensing spectrum which optimizes the
use of spectrum dynamically by using cooperation among
number of available cognitive users.
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