Reconfigurable intelligent surface (RIS) is an emerging technology to enhance wireless communication in terms of energy cost and system performance by equipping a considerable quantity of nearly passive reflecting elements. This study focuses on a downlink RIS-assisted multiple-input multiple-output (MIMO) wireless communication system that comprises three communication links of Rician channel, including base station (BS) to RIS, RIS to user, and BS to user. The objective is to design an optimal transmit covariance matrix at BS and diagonal phase-shifting matrix at RIS to maximize the achievable ergodic rate by exploiting the statistical channel state information at BS. Therefore, a large-system approximation of the achievable ergodic rate is derived using the replica method in large dimension random matrix theory. This large-system approximation enables the identification of asymptotic-optimal transmit covariance and diagonal phase-shifting matrices using an alternating optimization algorithm. Simulation results show that the large-system results are consistent with the achievable ergodic rate calculated by Monte Carlo averaging. The results verify that the proposed algorithm can significantly enhance the RIS-assisted MIMO system performance.
翻译:重新配置智能表面(RIS)是一种新兴技术,通过装备相当数量的近乎被动的反射元素,在能源成本和系统性能方面加强无线通信。本研究侧重于一个下行链路的RIS辅助多输入多输出输出(MIMO)无线通信系统,由里西亚频道的三个通信连接组成,包括基站(BS)到RIS、RIS到用户,以及BS到用户。目标是设计一个最佳的BS传输共变矩阵和RIS的分级分级转换矩阵,以便通过利用BS统计频道的州信息,最大限度地提高可实现的ergodic比率。因此,利用大维随机矩阵理论的复制方法,可以得出可实现ergodic率的大型系统近似近似值。这种大型系统近似化能够利用一种交替优化算法确定无症状-优化传输惯性通性和分级转换矩阵。模拟结果显示,大型系统的结果与蒙特卡洛平均计算出的可实现的可实现的ergodiced率一致。结果证实,拟议的算算法可以大大加强RIS-辅助IMO系统的性。