Intelligent Reflecting Surface-Assisted Cognitive Radio System

• Published in: IEEE transactions on communications Vol. 69; no. 1; pp. 675 - 687
• Main Authors: Yuan, Jie, Liang, Ying-Chang, Joung, Jingon, Feng, Gang, Larsson, Erik G.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.01.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Array signal processing; Beamforming; Cognitive radio; Downlink; Intelligent reflecting surface (IRS); Interference; MISO (control systems); MISO communication; Optimization; reconfigurable intelligent surface (RIS); Reconfigurable intelligent surfaces; robust beamforming; Uncertainty; Wireless communication; Wireless communication systems; Wireless communications; Intelligent reflecting surface (IRS); cognitive radio; robust beamforming; reconfigurable intelligent surface (RIS)
• ISSN: 0090-6778; 1558-0857; 1558-0857
• DOI: 10.1109/TCOMM.2020.3033006

Cognitive radio (CR) is an effective solution to improve the spectral efficiency (SE) of wireless communications by allowing the secondary users (SUs) to share spectrum with primary users (PUs). Meanwhile, intelligent reflecting surface (IRS), also known as reconfigurable intelligent surface (RIS), has been recently proposed as a promising approach to enhance energy efficiency (EE) of wireless communication systems through intelligently reconfiguring the channel environment. To improve both SE and EE, in this paper, we introduce multiple IRSs to a downlink multiple-input single-output (MISO) CR system, in which a single SU coexists with a primary network with multiple PU receivers (PU-RXs). Our design objective is to maximize the achievable rate of SU subject to a total transmit power constraint on the SU transmitter (SU-TX) and interference temperature constraints on the PU-RXs, by jointly optimizing the beamforming at SU-TX and the reflecting coefficients at each IRS. Both perfect and imperfect channel state information (CSI) cases are considered in the optimization. Numerical results demonstrate that IRS can significantly improve the achievable rate of SU under both perfect and imperfect CSI cases.