Sequential cooperative spectrum sensing in cognitive radio networks: Optimal selection of secondary users and their spectral measurements

2017 ◽  
Author(s):  
Laxminarayana S Pillutla ◽  
Bhuvan Joshi
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Cooperative Spectrum Sensing ◽  
Radio Networks ◽  
Optimal Selection ◽  
Spectral Measurements ◽  
Secondary Users ◽  
Selection Of

Efficient Cooperative Spectrum Sensing with Minimum Sensing Error Probability in Heterogeneous Cognitive Radio Networks

Frequenz ◽  
2012 ◽  
Vol 66 (7-8) ◽  
Author(s):  
Hang Hu ◽  
Ning Li ◽  
Youyun Xu
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Error Probability ◽  
Cooperative Spectrum Sensing ◽  
Radio Networks ◽  
Decision Threshold ◽  
Cognitive Network ◽  
Secondary Users ◽  
Sensing Performance

AbstractTo improve the sensing performance, cooperation among secondary users can be utilized to collect space diversity. We focus on the optimization of cooperative spectrum sensing in which multiple secondary users efficiently cooperate to achieve superior detection accuracy with minimum sensing error probability in heterogeneous cognitive radio (CR) networks. Rayleigh fading and Nakagami fading are considered respectively in cognitive network I and cognitive network II. For each cognitive network, we derive the optimal randomized rule for different decision threshold. Then, the optimal decision threshold is derived according to the rule of minimum sensing error (MSE). MSE rule shows better performance on improving the final false alarm and detection probability simultaneously. By simulations, our proposed strategy optimizes the sensing performance for each secondary user which is randomly distributed in the heterogeneous cognitive radio networks.

scholarly journals Secure Cooperative Spectrum Sensing and Allocation in Distributed Cognitive Radio Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Hui Lin ◽  
Jia Hu ◽  
Chuan Huang ◽  
Li Xu ◽  
Bin Wu
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Cooperative Spectrum Sensing ◽  
Radio Networks ◽  
Security Threats ◽  
Secondary Users ◽  
Allocation Process ◽  
Reputation Model ◽  
Adversarial Environments

Cognitive radio networks (CRNs) are an emerging wireless communications technique for resolving the significant spectrum scarcity problem. Despite their promising characteristics, CRNs also introduce new security threats, especially the internal attacks during the spectrum sensing and allocation process, which can degrade the efficiency of spectrum sensing and allocation. To address this issue, this paper proposes a distributed secure cooperative spectrum sensing strategy (DSCS) based on a dynamic reputation model to defend against attacks and provide reliable spectrum sensing. Moreover, the reputation values are used as weights in a novel distributed cheat-proof spectrum allocation strategy (DCSA) based on the Vickrey-Clarke-Groves (VCG) mechanism. Both theoretical analysis and simulation results indicate that the proposed DSCS and DCSA strategies can provide an effective countermeasure against the internal spectrum sensing data falsification (SSDF) attacks through enabling secondary users to obtain more accurate cooperative sensing results in adversarial environments.

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.

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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