Theoretical stopping criteria guided Greedy Algorithm for Compressive Cooperative Spectrum Sensing

Liang, Wei; Chien, Tsung Hsun; Lu, Chun Shien

doi:10.1016/j.comcom.2017.08.007

Cited by 6 publications

(1 citation statement)

References 36 publications

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“…Collaborative spectrum sensing (CSS) technology is one of the key solutions to CR technical problems. Most of the existing research builds models and algorithms under fading channel conditions, and use the spatial diversity of multi-nodes sensing to achieve the purpose of reducing sensing cost or improving sensing robustness [7][8][9][10][11][12]. However, when users provide false sensing results maliciously, the performance and security of spectrum sensing will be significantly affected [13] Zhang Linyuan et al discuss various situations of Byzantine attack and defense in reputation-based cooperative spectrum sensing [14].…”

Section: Introductionmentioning

confidence: 99%

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

Xie

Chen

et al. 2021

Electronics

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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.

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