Studies of optimum resource allocation mechanisms in NOMA MIMO NOMA networks using different technologies and algorithms for improving system throughput and energy efficiency

Abstract

The objective of this work is to achieve maximum EE and broad coverage by applying the max-min power control algorithm through sub-channel optimization, resource allocation (RA), access point selection (APS), and user association. The resource allocation (RA) for energy efficiency is framed as a mixed non-convex and non-linear function using successive convex approximation and sum ratio decoupling convert in convex and linear. This work formulates a framework for user-centric (UC) joint resource allocation, such as backhaul connection via beam -forming and AP to user connection via MIMO-NOMA. Users are grouped and served by the APs in the backhaul communication, and all APs are organized into clusters that are all served by the macro base station. Further, we used the AP selection and perfect user selection algorithms, as well as MMPCA for the best resource distribution in MIMO-NOMA. As a result, MIMO-NOMA backhaul communication system model has more coverage and improved energy efficiency. However, network complexity is higher, along with increased power consumption due to clustering, user selection, and access point election. Hence, cell-free RIS is used to reduce system complexity and power consumption. newline