Secure and Energy Efficient Transmission for IRS-Assisted Cognitive Radio Networks

• Published in: IEEE transactions on cognitive communications and networking Vol. 8; no. 1; pp. 170 - 185
• Main Authors: Wu, Xuewen, Ma, Jingxiao, Xing, Zhe, Gu, Chenwei, Xue, Xiaoping, Zeng, Xin
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.03.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Array signal processing; Beamforming; Cognitive radio; Eavesdropping; Energy consumption; Intelligent reflecting surface; Interference; Iterative methods; Optimization; Penalty function; physical layer security; Radio networks; secrecy energy efficiency; Security; Simulation; Tradeoffs; Wireless communications
• ISSN: 2332-7731; 2332-7731
• DOI: 10.1109/TCCN.2021.3114176

The spectrum efficiency (SE) and security of the secondary users (SUs) in the cognitive radio networks (CRNs) have become two main issues due to the limitation interference to the primary users (PUs) and the shared spectrum with the PUs. Intelligent reflecting surface (IRS) has been recently proposed as a revolutionary technique which can help to enhance the SE and physical layer security of wireless communications. This paper investigates the application of IRS in an underlay CRN, where a multi-antenna cognitive base station (CBS) utilizes spectrum assigned to the PU to communicate with a SU via IRS in the presence of multiple coordinated eavesdroppers (Eves). To achieve the trade-off between the secrecy rate (SR) and energy consumption, we investigate the secrecy energy efficiency (SEE) maximization problem by jointly designing the transmit beamforming at the CBS and the reflect beamforming at the IRS. To solve the non-convex problem with coupled variables, we propose an iterative alternating optimization algorithm to solve the sub-problems alternately, by utilizing an iterative penalty function based algorithm for sub-problem 1 and the difference of two-convex functions method for sub-problem 2. Furthermore, we provide a second-order-cone-programming (SOCP) approximation approach to reduce the computational complexity. Finally, the simulation results demonstrate that IRS can help significantly improve the SE and enhance the physical layer security in the CRNs. Moreover, the effectiveness and superiority of our proposed algorithm in achieving the trade-off between the SR and energy consumption are verified.