Robust Beamforming Design for Intelligent Reflecting Surface Aided MISO Communication Systems

• Published in: IEEE wireless communications letters Vol. 9; no. 10; pp. 1658 - 1662
• Main Authors: Zhou, Gui, Pan, Cunhua, Ren, Hong, Wang, Kezhi, Renzo, Marco Di, Nallanathan, Arumugam
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.10.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE); IEEE comsoc
• Subjects: Array signal processing; Beamforming; Channel state information; Communications systems; Engineering Sciences; imperfect channel state information (CSI); Intelligent reflecting surface (IRS); large intelligent surface (LIS); MISO (control systems); MISO communication; Optimization; Precoding; Quality of service; Reconfigurable intelligent surfaces; robust design; Robustness (mathematics); semidefinite program (SDP); Signal and Image processing; Signal processing; State (computer science); Surface treatment; Uncertainty; imperfect channel state information (CSI); robust design; Intelligent reflecting surface (IRS); semidefinite program (SDP); large intelligent surface (LIS)
• ISSN: 2162-2337; 2162-2345
• DOI: 10.1109/LWC.2020.3000490

Perfect channel state information (CSI) is challenging to obtain due to the limited signal processing capability at the intelligent reflection surface (IRS). This is the first work to study the worst-case robust beamforming design for an IRS-aided multiuser multiple-input single-output (MU-MISO) system under the assumption of imperfect CSI. We aim for minimizing the transmit power while ensuring that the achievable rate of each user meets the quality of service (QoS) requirement for all possible channel error realizations. With unit-modulus and rate constraints, this problem is non-convex. The imperfect CSI further increases the difficulty of solving this problem. By using approximation and transformation techniques, we convert the optimization problem into a squence of semidefinite program (SDP) subproblems that can be efficiently solved. Numerical results show that the proposed robust beamforming design can guarantee the required QoS targets for all the users.