On the achievable rate for double intelligent reflecting surface enhanced cognitive radio network

• Published in: 高技术通讯（英文版） Vol. 30; no. 4; pp. 415 - 423
• Main Authors: MA Junchi, GAO Jing, YANG Maolin, SUN Haonan, CHEN Bing
• Format: Journal Article
• Language: English
• Published: Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission,Tianjin Normal University,Tianjin 300382,P.R.China 01.12.2024
• Subjects: cognitive radio(CR); alternating optimization(AO); beamforming; distributed IRS; intelligent reflective surface(IRS)
• ISSN: 1006-6748
• DOI: 10.3772/j.issn.1006-6748.2024.04.009

Intelligent reflecting surface(IRS)can efficiently improve the performance of wireless commu-nication networks by intelligently reconfiguring the wireless propagation environment.Recently,IRS has been integrated with cognitive radio(CR)network in order to improve the resource utilization of communication systems.It is a challenging issue for IRS-assisted CR networks to improve the rate performance of the secondary user(SU)through the rational design of IRS passive beamforming while limiting the interference to the primary network.This paper investigates the optimization of downlink rate of SU in a double-IRS-assisted CR network.The achievable rate is maximized by jointly optimizing the active beamforming vector at the secondary transmitter(SU-TX)and the coop-eratively passive reflective beamforming at the two distributed IRSs.To solve the proposed non-con-vex joint optimization problem,the alternating optimization(AO)and semidefinite relaxation(SDR)techniques are then adopted to iteratively optimize the two variables.Numerical results vali-date that the proposed double-IRS assisted system can significantly improve the performance of the CR network compared with the existing single-IRS assisted CR system.