A Novel Weighted-Cooperative Spectrum Sensing Scheme Using Clustering

2012 ◽  
Vol 195-196 ◽  
pp. 277-282
Author(s):  
Hui Heng Liu ◽  
Wei Chen
Keyword(s):  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Cluster Head ◽  
Probability Of Detection ◽  
Fusion Center ◽  
Secondary Users ◽  
Probability Of Error ◽  
Radio System ◽  
Simulation Results ◽  
Observation Results

This paper proposes a novel weighted-cooperative spectrum sensing scheme using clustering for cognitive radio system. We firstly classify the secondary users into a few clusters according to several existent methods, and then use cluster-head to collect the observation results come from different secondary users in the same cluster and make a cluster-decision. Considering the different distances between the clusters and the fusion center, different weightings are used to weight the cluster-decisions before combining. The simulation results show that our proposed method improve the probability of detection and reduce the probability of error.

scholarly journals Fuzzy-based reliable and secure cooperative spectrum sensing for the smart grid

2021 ◽  
Vol 8 (2) ◽  
pp. 92-100
Author(s):  
Laila Nassef ◽  
Reemah Alhebshi ◽  
Keyword(s):  
Cognitive Radio ◽  
Smart Grid ◽  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Probability Of Detection ◽  
Fusion Center ◽  
Secondary Users ◽  
Sensing Data ◽  
Spectrum Detection ◽  
Fuzzy Fusion

Cognitive radio is a promising technology to solve the spectrum scarcity problem caused by inefficient utilization of radio spectrum bands. It allows secondary users to opportunistically access the underutilized spectrum bands assigned to licensed primary users. The local individual spectrum detection is inefficient, and cooperative spectrum sensing is employed to enhance spectrum detection accuracy. However, cooperative spectrum sensing opens up opportunities for new types of security attacks related to the cognitive cycle. One of these attacks is the spectrum sensing data falsification attack, where malicious secondary users send falsified sensing reports about spectrum availability to mislead the fusion center. This internal attack cannot be prevented using traditional cryptography mechanisms. To the best of our knowledge, none of the previous work has considered both unreliable communication environments and the spectrum sensing data falsification attack for cognitive radio based smart grid applications. This paper proposes a fuzzy inference system based on four conflicting descriptors. An attack model is formulated to determine the probability of detection for both honest and malicious secondary users. It considers four independent malicious secondary users’ attacking strategies of always yes, always no, random, and opposite attacks. The performance of the proposed fuzzy fusion system is simulated and compared with the conventional fusion rules of AND, OR, Majority, and the reliable fuzzy fusion that does not consider the secondary user’s sensing reputation. The results indicate that incorporating sensing reputation in the fusion center has enhanced the accuracy of spectrum detection and have prevented malicious secondary users from participating in the spectrum detection fusion

scholarly journals Energy-Efficient Cluster-Based Cooperative Spectrum Sensing in a Multiple Antenna Cognitive Radio Network

2021 ◽  
pp. 176-185
Author(s):  
Samson I. Ojo ◽  
◽  
Zachaeus K. Adeyemo ◽  
Damilare O. Akande ◽  
Ayobami O. Fawole
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Energy Efficient ◽  
Cooperative Spectrum Sensing ◽  
Cluster Head ◽  
Fusion Rule ◽  
Probability Of Detection ◽  
Multiple Antenna ◽  
Secondary Users ◽  
Sensing Time

Spectrum Hole Detection (SHD) is a major operation in a Cognitive Radio (CR) network to identify empty spectrum for maximum utilization. However, SHD is often affected by multipath effects resulting in interference. The existing techniques used to address these problems are faced by poor detection rate, long sensing time and bandwidth inefficiency. Hence, this paper proposes a cluster-based Energy-Efficient Multiple Antenna Cooperative Spectrum Sensing (EEMACSS) for SHD in CR networks using Energy Detector (ED) with a modified combiner. Multiple secondary users are used to carry out local sensing using ED in multiple antenna configurations. The local sensing results are combined at the cluster head using majority fusion rule to determine the sensing results at each cluster. The sensing results from individual cluster are combined to determine the global sensing result using OR fusion rule. The proposed EEMACSS is evaluated using Probability of Detection (PD), Sensing Time (ST) and Spectral Efficiency (SE) by comparing with existing techniques. The results reveal that the proposed technique shows better performance.

A SSDF-Attack-Exclusion Cooperative Spectrum Sensing Scheme in Cognitive Radio Networks

2014 ◽  
Vol 556-562 ◽  
pp. 5219-5222
Author(s):  
Wei Wu ◽  
Xiao Fei Zhang ◽  
Xiao Ming Chen
Keyword(s):  
Cognitive Radio ◽  
Utility Function ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Cooperative Spectrum Sensing ◽  
Radio Networks ◽  
Fusion Center ◽  
Sensing Data ◽  
Single User ◽  
Simulation Results

Compared with the single user spectrum sensing, cooperative spectrum sensing is a promising way to improve the detection precision. However, cooperative spectrum sensing is vulnerable to a variety of attacks, such as the spectrum sensing data falsification attack (SSDF attack). In this paper, we propose a concise cooperative spectrum sensing scheme based on a reliability threshold. We analyze the utility function of SSDF attacker in this scheme, and present the least reliability threshold for the fusion center against SSDF attack. Simulation results show that compared with the traditional cooperative spectrum sensing scheme, the SSDF attacker has a much lower utility in our proposed scheme, which drives it not to attack any more.

scholarly journals One-to-Many Relationship Based Kullback Leibler Divergence against Malicious Users in Cooperative Spectrum Sensing

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Noor Gul ◽  
Ijaz Mansoor Qureshi ◽  
Sadiq Akbar ◽  
Muhammad Kamran ◽  
Imtiaz Rasool
Keyword(s):  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Primary User ◽  
Performance Degradation ◽  
Fusion Center ◽  
Secondary Users ◽  
Malicious User ◽  
Leibler Divergence ◽  
Higher Weights ◽  
The Individual

The centralized cooperative spectrum sensing (CSS) allows unlicensed users to share their local sensing observations with the fusion center (FC) for sensing the licensed user spectrum. Although collaboration leads to better sensing, malicious user (MU) participation in CSS results in performance degradation. The proposed technique is based on Kullback Leibler Divergence (KLD) algorithm for mitigating the MUs attack in CSS. The secondary users (SUs) inform FC about the primary user (PU) spectrum availability by sending received energy statistics. Unlike the previous KLD algorithm where the individual SU sensing information is utilized for measuring the KLD, in this work MUs are identified and separated based on the individual SU decision and the average sensing statistics received from all other users. The proposed KLD assigns lower weights to the sensing information of MUs, while the normal SUs information receives higher weights. The proposed method has been tested in the presence of always yes, always no, opposite, and random opposite MUs. Simulations confirm that the proposed KLD scheme has surpassed the existing soft combination schemes in estimating the PU activity.

Selection of Cognitive Users in Cooperative Spectrum Sensing

2012 ◽  
Vol 433-440 ◽  
pp. 5218-5222
Author(s):  
Xue Qiang Zheng ◽  
Juan Chen ◽  
Xin Wang ◽  
Fan Jun Kong
Keyword(s):  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Target Function ◽  
Primary User ◽  
Optimal Number ◽  
Fusion Center ◽  
Simulation Results ◽  
Network Overhead ◽  
Selection Of ◽  
Usage Efficiency

Cooperative spectrum sensing under network overhead constraints is studied. To protect the primary user well, the detection probability must exceed the predefined threshold. Based on the protection of the primary user, the constraints on optimal number of cognitive users are defined by weighting the detection performance and the usage efficiency in a target function. The analysis of the target function is given under energy fusion strategy in the fusion center. The simulation results show the validity of the constraints.

A Study of Cognitive Radio Sensing Techniques for Optimum Spectrum Utilization

2020 ◽  
Vol 13 ◽  
Author(s):  
Darwin Nesakumar A ◽  
Inbamalar T M
Keyword(s):  
Comparative Study ◽  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Decision Fusion ◽  
Vital Role ◽  
Probability Of Detection ◽  
Ratio Method ◽  
Spectrum Utilization ◽  
Secondary Users ◽  
Fusion Centre

Background: The spectrum scarcity plays a vital role in wireless communications. We are in the situation to use it through an efficient methodology. Objective: To identify the holes in the spectrum through an efficient spectrum sensing and to allocate the bands to the unlicensed users (Secondary Users- SU). Methods: It has been proposed to make a comparative study among the existing spectrum sensing methods based on the following parameters such as Probability detection (Pd) measurement, Algorithm, Decision fusion method, Network model. Results: Comparative study has been made to find the pros and cons of the existing techniques with their limitations and the field of application. CSS (Cooperative Spectrum Sensing) technique significantly consumes less energy and reporting time to FC (Fusion Centre) since it utilizes LLR (Log Likelihood Ratio) Method to find the Probability of detection using Chair-varshney rule in local sensing with parallel report approach in the cluster based network. Conclusion: Through the study and the comparison of parameters in literature, it is found that CSS provide better detection. Therefore, this technique can be considered as an efficient technique to find the holes and to share the frequency with SU’s.

scholarly journals Efficient techniques for cooperative spectrum sensing in cognitive radio networks

2021 ◽  
Author(s):  
Lamiaa Khalid
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Cooperative Spectrum Sensing ◽  
Selection Criterion ◽  
Radio Networks ◽  
Joint Detection ◽  
Secondary Users ◽  
Simulation Results ◽  
Time Offset

In this thesis, we focus on two important design aspects of cooperative spectrum sensing (CSS) in cognitive radio networks which are the selection criterion of cooperating secondary users and the fusion technique for combining their local sensing decisions. We propose a novel adaptive user-group assignment algorithm that addresses the problem of sensing accuracy-efficiency trade-off in group-based CSS with heterogeneous cooperating secondary users. The performance of the proposed algorithm is bounded by 4.2% of the optimal solution. Through extensive simulations, we demonstrate that the proposed algorithm can effectively improve the performance of CSS in terms of the opportunistic throughput, sensing overhead and the number of sensing rounds needed to discover an available channel. Considering the different detection performance of cooperating secondary users, we propose a novel reliability-based decision fusion scheme in which a weight is assigned to each secondary user's local decision based on its reliability. Since the knowledge of the local probabilities of detection and false alarm for each secondary detector may not be known in practice, we employ a counting process to estimate those probabilities based on past global and local decisions. We then formulate the problem of minimizing the network probability of sensing error and develop a dual search algorithm, based on a non-linear Lagrangian approach, to solve the formulated problem. Our simulation results show that the dual algorithm converges to the optimal value with zero duality gap using few numbers of iterations. We also show that the probability of error is reduced by 18% and 88% compared to the OR and AND fusion rules, respectively, when the number of secondary users is eight. We then address the practical concern of secondary users reporting correlated local decisions to the fusion center. For this scenario, we formulate the problem of minimizing the network probability of sensing error optimization problem and employ the genetic algorithm to jointly find the optimal K*-out-of-M fusion rule and the optimal local threshold for a certain correlation index. Simulation results show that the network probability of sensing error degrades as the degree of correlation between cooperating secondary users increases. We also study the problem of multiband cooperative joint detection in the presence of sensing errors due to time offset. We derive the aggregate opportunistic throughput and aggregate interference to primary users for multiband cooperative joint detection in the presence of time offset. Our numerical results demonstrate the negative impact of the time offset on the aggregate opportunistic throughput of multiband cooperative joint detection.

scholarly journals Efficient techniques for cooperative spectrum sensing in cognitive radio networks

2021 ◽  
Author(s):  
Lamiaa Khalid
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Cooperative Spectrum Sensing ◽  
Selection Criterion ◽  
Radio Networks ◽  
Joint Detection ◽  
Secondary Users ◽  
Simulation Results ◽  
Time Offset

In this thesis, we focus on two important design aspects of cooperative spectrum sensing (CSS) in cognitive radio networks which are the selection criterion of cooperating secondary users and the fusion technique for combining their local sensing decisions. We propose a novel adaptive user-group assignment algorithm that addresses the problem of sensing accuracy-efficiency trade-off in group-based CSS with heterogeneous cooperating secondary users. The performance of the proposed algorithm is bounded by 4.2% of the optimal solution. Through extensive simulations, we demonstrate that the proposed algorithm can effectively improve the performance of CSS in terms of the opportunistic throughput, sensing overhead and the number of sensing rounds needed to discover an available channel. Considering the different detection performance of cooperating secondary users, we propose a novel reliability-based decision fusion scheme in which a weight is assigned to each secondary user's local decision based on its reliability. Since the knowledge of the local probabilities of detection and false alarm for each secondary detector may not be known in practice, we employ a counting process to estimate those probabilities based on past global and local decisions. We then formulate the problem of minimizing the network probability of sensing error and develop a dual search algorithm, based on a non-linear Lagrangian approach, to solve the formulated problem. Our simulation results show that the dual algorithm converges to the optimal value with zero duality gap using few numbers of iterations. We also show that the probability of error is reduced by 18% and 88% compared to the OR and AND fusion rules, respectively, when the number of secondary users is eight. We then address the practical concern of secondary users reporting correlated local decisions to the fusion center. For this scenario, we formulate the problem of minimizing the network probability of sensing error optimization problem and employ the genetic algorithm to jointly find the optimal K*-out-of-M fusion rule and the optimal local threshold for a certain correlation index. Simulation results show that the network probability of sensing error degrades as the degree of correlation between cooperating secondary users increases. We also study the problem of multiband cooperative joint detection in the presence of sensing errors due to time offset. We derive the aggregate opportunistic throughput and aggregate interference to primary users for multiband cooperative joint detection in the presence of time offset. Our numerical results demonstrate the negative impact of the time offset on the aggregate opportunistic throughput of multiband cooperative joint detection.

Sensing Confidence Level-Based Cooperative Spectrum Sensing Algorithm

2013 ◽  
Vol 380-384 ◽  
pp. 1499-1504
Author(s):  
Shi Ding Zhang ◽  
Hai Lian Wang ◽  
Jing Ping Mei
Keyword(s):  
False Alarm ◽  
Spectrum Sensing ◽  
Confidence Level ◽  
Detection Probability ◽  
Cooperative Spectrum Sensing ◽  
False Alarm Probability ◽  
Control Channel ◽  
Fusion Center ◽  
Local Spectrum ◽  
Secondary Users

Cooperative spectrum sensing is a key technology to tackle the challenges such as fading or hidden terminal problem in local spectrum sensing of cognitive radio system. Conventional cooperative method can improve the detection performance in some sense, but increase overhead of control channel. In order to reduce the overhead, a new cooperative spectrum sensing algorithm based on confidence level is proposed. In this algorithm, the maximum-eigenvalue-based detection scheme is carried out to obtain the local spectrum detection and the detection probability and false alarm probability of each secondary user are used to estimate the reliability of the sensing decision. The test statistic of the secondary users with high reliability are chosen and sent to fusion center. Then weighted factors of chosen secondary users are derived from creditability values, and the global decision is made by weighted fusion at fusion center. The simulation results show that the proposed algorithm improves the detection probability in the guarantee of the false-alarm probability close to 0 and saves half of the overhead in the control channel.

scholarly journals An SETM Algorithm for Combating SSDF Attack in Cognitive Radio Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
S. Tephillah ◽  
J. Martin Leo Manickam
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Trust Management ◽  
Cooperative Spectrum Sensing ◽  
Radio Networks ◽  
Second Phase ◽  
Common Channel ◽  
Secondary Users ◽  
Management Algorithm ◽  
Different Types

Security is a pending challenge in cooperative spectrum sensing (CSS) as it employs a common channel and a controller. Spectrum sensing data falsification (SSDF) attacks are challenging as different types of attackers use them. To address this issue, the sifting and evaluation trust management algorithm (SETM) is proposed. The necessity of computing the trust for all the secondary users (SUs) is eliminated based on the use of the first phase of the algorithm. The second phase is executed to differentiate the random attacker and the genuine SUs. This reduces the computation and overhead costs. Simulations and complexity analyses have been performed to prove the efficiency and appropriateness of the proposed algorithm for combating SSDF attacks.

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