A Novel Distributed Compressive Wideband Spectrum Sensing Method in Cognitive Radio Networks

2014 ◽  
Vol 667 ◽  
pp. 311-317
Author(s):  
Chang Lin ◽  
Qi Zhu ◽  
Chang Shu
Keyword(s):  
Spectrum Sensing ◽  
Radio Networks ◽  
Detection Performance ◽  
Detection Sensitivity ◽  
Fusion Center ◽  
Recovery Algorithm ◽  
Wideband Spectrum Sensing ◽  
Sensing Technology ◽  
System Robustness ◽  
Distributed Compressive Sensing

In this paper, we present an optimum weighted approach for wideband spectrum sensing. Distributed compressive sensing technology is exploited to obtain dramatic rate reductions while differential procedure is deduced to extremely enhance the detection sensitivity. The measurements are collected from each SU at a fusion center, where a C-out-of-J method is proposed to dramatically heighten the detection performance. SCSMP recovery algorithm is utilized to reconstruct the signals, which are then weighted by the estimated SNRs. Corroborating simulation results show that the raised algorithm can effectively reduce sampling rates at each SU, substantially raise the detection performance and saliently improve system robustness against noise.

scholarly journals A Sequential Compressed Spectrum Sensing Algorithm against SSDH Attack in Cognitive Radio Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Zhuhua Hu ◽  
Yong Bai ◽  
Lu Cao ◽  
Mengxing Huang ◽  
Mingshan Xie
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Detection Probability ◽  
Signal Reconstruction ◽  
Sampling Rate ◽  
Radio Networks ◽  
Wideband Spectrum Sensing ◽  
Sensing Technology ◽  
Key Technologies ◽  
Simulation Results

Spectrum sensing is one of the key technologies in wireless wideband communication. There are still challenges in respect of how to realize fast and robust wideband spectrum sensing technology. In this paper, a novel nonreconstructed sequential compressed wideband spectrum sensing algorithm (NSCWSS) is proposed. Firstly, the algorithm uses a sequential spectrum sensing method based on history memory and reputation to ensure the robustness of the algorithm. Secondly, the algorithm uses the strategy of compressed sensing without reconstruction, which thus ensures the sensing agility of the algorithm. The algorithm is simulated and analyzed by using the centralized cooperative sensing. The theoretical analysis and simulation results reveal that, under the condition of ensuring the certain detection probability, the proposed algorithm effectively reduces complex computation of signal reconstruction, significantly reducing the wideband spectrum sampling rate. At the same time, in the cognitive wideband communication scenarios, the algorithm also achieves a better defense against the SSDF attack in spectrum sensing.

scholarly journals An Active and Passive Reputation Method for Secure Wideband Spectrum Sensing Based on Blockchain

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1346
Author(s):  
Xinyu Xie ◽  
Zhuhua Hu ◽  
Min Chen ◽  
Yaochi Zhao ◽  
Yong Bai
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Cooperative Spectrum Sensing ◽  
Sampling Rate ◽  
Radio Networks ◽  
Single Node ◽  
Decision Algorithm ◽  
Collusion Attacks ◽  
Wideband Spectrum Sensing

Spectrum is a kind of non-reproducible scarce strategic resource. A secure wideband spectrum sensing technology provides the possibility for the next generation of ultra-dense, ultra-large-capacity communications to realize the shared utilization of spectrum resources. However, for the open collaborative sensing in cognitive radio networks, the collusion attacks of malicious users greatly affect the accuracy of the sensing results and the security of the entire network. To address this problem, this paper proposes a weighted fusion decision algorithm by using the blockchain technology. The proposed algorithm divides the single-node reputation into active reputation and passive reputation. Through the proposed token threshold concept, the active reputation is set to increase the malicious cost of the node; the passive reputation of the node is determined according to the historical data and recent performance of the blockchain. The final node weight is obtained by considering both kinds of reputation. The proposed scheme can build a trust-free platform for the cognitive radio collaborative networks. Compared with the traditional equal-gain combination algorithm and the centralized sensing algorithm based on the beta reputation system, the simulation results show that the proposed algorithm can obtain reliable sensing results with a lower number of assistants and sampling rate, and can effectively resist malicious users’ collusion attacks. Therefore, the security and the accuracy of cooperative spectrum sensing can be significantly improved in cognitive radio networks.

A rapid coarse-grained blind wideband spectrum sensing method for cognitive radio networks

2021 ◽  
Vol 166 ◽  
pp. 234-243
Author(s):  
Peng Feng ◽  
Yuebin Bai ◽  
Yuhao Gu ◽  
Jun Huang ◽  
Xiaolin Wang ◽  
...  
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Radio Networks ◽  
Coarse Grained ◽  
Wideband Spectrum Sensing

scholarly journals A Double Adaptive Approach to Tackle Malicious Users in Cognitive Radio Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Muhammad Sajjad Khan ◽  
Muhammad Jibran ◽  
Insoo Koo ◽  
Su Min Kim ◽  
Junsu Kim
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Cooperative Spectrum Sensing ◽  
Evidence Theory ◽  
Adaptive Threshold ◽  
Radio Networks ◽  
Maximal Ratio Combining ◽  
Fusion Center ◽  
Adaptive Approach

Cognitive radio (CR) is being considered as a vital technology to provide solution to spectrum scarcity in next generation network, by efficiently utilizing the vacant spectrum of the licensed users. Cooperative spectrum sensing in cognitive radio network has a promising performance compared to the individual sensing. However, the existence of the malicious users’ attack highly degrades the performance of the cognitive radio networks by sending falsified data also known as spectrum sensing data falsification (SSDF) to the fusion center. In this paper, we propose a double adaptive thresholding technique in order to differentiate legitimate users from doubtful and malicious users. Prior to the double adaptive approach, the maximal ratio combining (MRC) scheme is utilized to assign weight to each user such that the legitimate users experience higher weights than the malicious users. Double adaptive threshold is applied to give a fair chance to the doubtful users to ensure their credibility. A doubtful user that fails the double adaptive threshold test is declared as a malicious user. The results of the legitimate users are combined at the fusion center by utilizing Dempster-Shafer (DS) evidence theory. Effectiveness of the proposed scheme is proved through simulations by comparing with the existing schemes.

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.

An Improved SNR-Based Cooperative Spectrum Sensing in Cognitive Radio Networks

2014 ◽  
Vol 631-632 ◽  
pp. 874-877
Author(s):  
Jie Guo ◽  
Yan Gu ◽  
Da Hai Jing
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Network ◽  
Cooperative Spectrum Sensing ◽  
New Technology ◽  
Radio Networks ◽  
Fusion Center ◽  
Detector Performance ◽  
Performance Simulation ◽  
Optimal Detector

Spectrum sensing is a new technology in cognitive radio network, whose main purpose is to design an optimal detector. This paper studies a soft linear cooperative spectrum sensing method. We propose a SNR-based algorithm for weight setting at fusion center to improve the detector performance. Simulation results shows that the SNR-based method has better detector performance than the others.

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