Enhanced Spectral Efficiency in RIS-Assisted MIMO Systems Through Joint Precoding and RIS Configuration

Abstract

Reconfigurable Intelligent Surfaces (RIS) offer a promising solution to enhance wireless communication performance, particularly for 6G networks. This paper proposes a unified joint optimization framework to enhance spectral efficiency in reconfigurable intelligent surface (RIS)-assisted multiple-input multiple-output (MIMO) systems. Unlike conventional approaches that optimize RIS phase shifts and transmitter precoding separately, our method jointly optimizes both using an iterative strategy. Water-filling is used for power allocation across channel eigenmodes, while manifold optimization ensures efficient phase shift updates under unit-modulus constraints. Extensive simulations under diverse channel conditions reveal a consistent spectral efficiency improvement of up to 39.38%, outperforming across RIS sizes and transmit powers. These results highlight the contribution of combining RIS configuration and transmitter precoding into a coordinated optimization loop, guided by channel eigenmode alignment and practical implementation constraints. The enhanced performance stems from the algorithm’s ability to dynamically coordinate power allocation with channel eigenmode alignment, making it a viable solution for next-generation wireless systems requiring high spectral efficiency.