Joint Precoding and Reflection Optimization for IRS-Assisted MU-MIMO-OTFS Downlink Systems

Orthogonal time frequency space (OTFS) modulation has been proposed as a promising technique to achieve high-reliability communications in high-mobility scenarios. In this paper, we consider a multi-user (MU) multiple-input multiple-output (MIMO)-OTFS downlink communication scenario, where an intelligent reflecting surface (IRS) is deployed to enhance the performance. Specifically, the delay-Doppler (DD) domain input-output relationship of such a system is first derived, based on which, the joint optimization of the precoding matrices and IRS reflection phase is studied to maximize the weighted sum rate (WSR) considering user fairness. Note that the corresponding optimization problem is non-convex. To tackle this challenge, we first reformulate the problem into a more traceable equivalent form by the weighted mean minimum square error (WMMSE) approach. Utilizing the characteristics of the DD domain signal relationship, we then decouple the reformulated problem and further transform it into two subproblems, which are solved by the Lagrangian function method and the project-descent-retracting (PDR) algorithm, respectively. The precoding matrices and reflection phase are jointly optimized by alternative optimization to maximize WSR. Simulation results demonstrate that, compared with benchmark schemes, the proposed WMMSE-ALT can improve the rate more than 85% in IRS-assisted MU-MIMO-OTFS systems.