Capacity and power allocation optimization in dynamic RIS-enabled mMIMO NOMA systems for 6G

Abstract An innovative approach is proposed to improve capacity performance by including dynamic reconfigurable intelligent surfaces (DRIS) in the downlink (DL) non-orthogonal multiple access (NOMA) power domain (PD) systems with massive multiple-input, multiple-output) (mMIMO) in the setting of 6G wireless networks. To guarantee the system’s best performance in different scenarios, we used a unique optimization approach to distribute power among users efficiently using the water-filling algorithm. Analysis of the influence of different deployment densities of static, and DRIS on the performance of the system is presented in this paper. The effect on the effective area spectral efficiency (EASE), and the ability of RIS to reduce latency and handle higher user loads are also discussed. The paper also demonstrates practical 6G configurations, including 256 quadrature amplitude modulation (256-QAM), channel state information (CSI), and successive interference cancellation (SIC). The results indicate that including DRIS in the mMIMO DL NOMA PD system significantly boosts capacity, and EASE while decreasing latency. Implementing logarithmic water filling has proven to be a highly effective method for distributing power location to maximize the capabilities of suggested systems. These results establish crucial information for enhancing future wireless communication systems, and in agreement with the estimated equation, the Monte Carlo results show that our work is accurate and reliable. Integrating the DRIS with four distinct user groups (4, 8, 16, and 32) improves the system’s capacity performance by 25%, 25.01%, 25.02%, and 25.03% respectively, compared to the performance conventional static RIS that applied in other related works.