This paper tackles the problem of joint active and passive beamforming optimization for an intelligent reflective surface (IRS)-assisted multi-user downlink multiple-input multiple-output (MIMO) communication system. We aim to maximize spectral efficiency of the users by minimizing the mean square error (MSE) of the received symbol. For this, a joint optimization problem is formulated under the minimum mean square error (MMSE) criterion. First, block coordinate descent (BCD) is used to decouple the joint optimization into two sub-optimization problems to separately find the optimal active precoder at the base station (BS) and the optimal matrix of phase shifters for the IRS. While the MMSE active precoder is obtained in a closed form, the optimal phase shifters are found iteratively using a modified version (also introduced in this paper) of the vector approximate message passing (VAMP) algorithm. We solve the joint optimization problem for two different models for IRS phase shifts. First, we determine the optimal phase matrix under a unimodular constraint on the reflection coefficients, and then under the constraint when the IRS reflection coefficients are modeled by a reactive load, thereby validating the robustness of the proposed solution. Numerical results are presented to illustrate the performance of the proposed method using multiple channel configurations. The results validate the superiority of the proposed solution as it achieves higher throughput compared to state-of-the-art techniques.
翻译:本文针对智能反射表面(IRS)辅助多用户下链接多输出多输出输出(MIMO)通信系统的联合主动和被动波束优化问题。 我们的目标是最大限度地提高用户的光谱效率, 尽量减少收到符号的平均平方差( MSE) 。 为此, 在最小平均平方差( MMSE) 标准下制定了联合优化问题。 首先, 区块协调底部( BCD) 用于将联合优化分解为两个亚优化问题, 以便分别找到基础站( BS) 和ISS 阶段转换器的最佳组合。 虽然 MMSE 活动前科以封闭的形式获得, 但最佳的阶段转换者会通过修改版本( 也在本文中引入) 传递的矢量近信息( MAMP) 算法。 我们解决了IRS 阶段转换的两个不同模式的联合优化问题。 首先, 我们确定最佳阶段矩阵, 由对映射系数的不与状态制约下找到最佳的前置式前置式前置式前置式前置式前置式, 然后在以封闭式的姿态下, 将所拟议的稳态压式图像反射式反射法的图像结果,, 以模拟反射式反射压式反演算为模式, 模拟后演算式式式式式式式的压后, 模拟式式的演制成为制成为制式式制式式式式式式式式式式式式式式式式式式式式的压后, 。