Efficient evidence‐based decision fusion scheme for cooperative spectrum sensing in cognitive radio networks

Abstract

In this article, an evidence based decision fusion cooperative spectrum sensing (CSS) schemes has been considered for overcoming the hidden terminal problem, improving reliability, and increasing SU agility. Under practical conditions, the combination of conflicting evidences with the classical Dempster-Shafer theory (DS theory) rule may produce counter-intuitive results when combining the secondary users (SUs) sensing data evidence leading to poor CSS performance. In order to overcome and minimize the effect of conflicting data, and to enhance performance of the CSS system, a novel efficient evidence-based decision fusion scheme CSS is proposed. The approach is based on the credibility of evidence from the SUs sensing decision, which represents the similarity or the relation among the different SUs sensing data evidence, and a dissociability degree measure that indicates the quality or clarity of the SUs sensing data evidence. Furthermore, a weighted averaging factor determined by the credibility and dissociability of the SU sensing data evidence is proposed. Simulation results presented show that under practical conditions the proposed scheme enhances the performance of the CSS system when compared to traditional fusion rules that do not take into account the difference in local sensing reliability between the SUs.

Dueling deep Q-networks for social awareness-aided spectrum sharing

“…PRN and SRN were combined to measure the overall physical-social utility and aimed to maximize the synergy between PRN and SRN [37]. In addition, social relationships such as credibility has been applied to the perception of spectrum usage [40]. They proposed an evidence-based decision fusion cooperative spectrum sensing strategy, while we proposed a DRL technology to utilize the social credibility in spectrum sharing.…”

“…2 The social network of cognitive users with social credibility such as Twitter is used as a reference to judge the credibility of users, and used as one of the conditions for the formation of social networks. Simpson and Sun [40] treat the credibility of the SU as a weighted averaging factor and update it with the change of the SU to improve the efficiency of spectrum sensing. In this study, we take such sociality into consideration and introduce social credibility [41] to establish a social network overlay, as shown in Fig.…”

Joint spectrum sensing and resource allocation against byzantine attack in overlay cognitive radio networks

“…Then the users are classified into three states by RV to differentiate between intentional and unintentional MUs for subsequent processing. To improve CSS performance, Simpson et al proposed an evidence‐based CRN data fusion algorithm that uses both the RV of SUs sensing report evidence and dissociability degree measure in Reference 25. Benedetto et al 26 proposed an RV‐based CSS method that first classifies SUs into three list states (white, gray, and black).…”

Evaluation of cooperative spectrum sensing with filtered bank multi carrier utilized for detecting in cognitive radio network

“…In addition, at wideband spectrum sensing process including correlated sub band occupancy was examined with optimal linear energy combiner detector 20 . The joint optimization issue is developed to raise the aggregate throughput subject to the limited combined interference, then, the efficiency improvement demonstrates through this detector 21 . Unlike the overhead works, the throughput and probability of missed detection simultaneously improved a diagnostic threshold of weights and linear cooperative spectrum sensing 22 .…”