STAR-RIS-Assisted Hybrid MIMO mmWave Communications - Yang, Xiawei; Liu, Heng; Gong, Shiqi; Wang, Gongpu; Xing, Chengwen (IEEE internet of things journal, 2024)
The simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) has been a promising enabler for the future wireless network due to its full-space coverage capability. In this article, we investigate the STAR-RIS assisted hybrid mmWave multiple-input-multiple-output system, where the two practical operating protocols, i.e., energy splitting (ES) and mode switching (MS), and the coupled transmission and reflection (T&R) phase-shift model for the STAR-RIS are considered. For each operating protocol, we aim to maximize the system weighted sum rate (WSR) by jointly optimizing the passive T&R coefficients at the STAR-RIS and the hybrid analog-digital precoder/combiners, subject to the discrete phase shift constraints. Specifically, we propose an efficient weighted minimum mean-square error based alternating optimization (AO) algorithm to address this highly coupled nonconvex problem. By leveraging the special ordered set of type 1 under the MS protocol, the optimization of both the discrete T&R coefficients and analog precoder/combiners can be equivalently transformed into the standard binary quadratic programming, which can be effectively solved by the mathematical programming with the equilibrium constraints-based exact penalty algorithm. The proposed penalty-based AO algorithm is also applicable to the WSR maximization under the ES protocol. In addition, to avoid high-complexity iterative process wherever possible, we develop a separate analog-digital beamforming scheme, where a fast projection-based gradient descent algorithm is applied to successively optimize discrete T&R coefficients and analog precoder/combiners to maximize the effective channel gain, and then the optimal digital precoder/combiners are obtained in semi-closed forms. Numerical simulation results demonstrate the superior WSR performance and complexity advantage of the proposed algorithms over the existing benchmark schemes.