Joint Sensing and Transmission Optimization for IRS-Assisted Cognitive Radio Networks

• Published in: IEEE transactions on wireless communications Vol. 22; no. 9; p. 1
• Main Authors: Wu, Wei, Wang, Zi, Wu, Yuhang, Zhou, Fuhui, Wang, Baoyun, Wu, Qihui, Ng, Derrick Wing Kwan
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Approximation; Array signal processing; Autonomous aerial vehicles; Cognitive radio; Communication networks; Convexity; False alarms; Intelligent reflecting surface; Mathematical analysis; Optimization; sensing-throughput tradeoff; Sensors; Signal to noise ratio; spectrum sensing; Throughput; Wireless communications; Wireless networks; Wireless sensor networks
• ISSN: 1536-1276; 1558-2248
• DOI: 10.1109/TWC.2023.3238684

Cognitive radio (CR) is one of the most disruptive techniques for enabling the next generation wireless communication networks due to its potential in improving the spectral efficiency. In this paper, intelligent reflecting surface (IRS) is exploited to enhance both the accuracy of spectrum sensing and the secondary transmission in a CR network (CRN) employing the opportunistic spectrum access. A novel detection threshold based on the probability of false alarm is derived for improving the spectrum sensing performance. The average achievable rate of the secondary network is maximized under both the two-stage and one-stage IRS phase shifts case. To tackle the challenging non-convex optimization problem under the two-stage case, a computationally efficient block coordinate descent (BCD)-based algorithm is proposed coputilizing the techniques of successive convex approximation (SCA) and semidefinite relaxation (SDR). Moreover, a BCD method and a tractable approximation of the probability of detection are exploited to tackle the problem under one-stage IRS phase shifts case. Simulation results demonstrate that our proposed designs are superior to the benchmark schemes in terms of the achievable rate and the sensing performance, and IRS can greatly improve the spectral efficiency of the CRN.