Performance Enhancement via Partitioning Large Intelligent Surfaces in Downlink NOMA Networks

Abstract

Low latency, high-data rates, and massive connectivity are the requirements for the emerging wireless technologies that will give a chance to high-demanding and progressive innovations in many spheres. Reconfigurable intelligent surfaces (RISs) are considered to be a promising technology for the rising wireless communication standards. This paper studies the large intelligent surface (LIS) enabled wireless network deploying non-orthogonal multiple access (NOMA) over Nakagami-m channels with non-fixed LIS positions. We propose the LIS partitioning method, where various LIS elements serve different NOMA users depending on their quality of service. Moreover, we also examine the effect of imperfect successive interference cancellation, the number of LIS elements, and their allocation amongst the users. The simulations and followed-up discussions are provided regarding the system’s ergodic capacity measurements.