Energy Efficiency and Resource Allocation Optimization with MIMO-NOMA and Backhaul Beam-Forming in User Centric Ultra Dense Networks

Abstract

Non-orthogonal multiple access (NOMA) is viewed as the key multiple access technology for 5G and beyond networks, attracting the attention of academics and Industries. NOMA and the multiple input multiple output (MIMO-NOMA) technology can improve a system’s throughput, latency, and energy efficiency (EE) in future-generation communication networks. The objective of this paper is to achieve maximum EE by applying the Max-min Power Control Algorithm (MMPCA) through sub-channel optimization, resource allocation (RA) optimization, access point selection (APS), and user association. The EE results obtained with and without using MMPCA are compared to the RA optimization from a conventional water-filling algorithm (WFA). This paper formulates a framework for user-centric (UC) joint resource allocation, such as backhaul connection via beam-forming and Access point AP to user connection via MIMO-NOMA. The user without interference is decoded using the NOMA principle. The MMPCA was also used to optimize cooperative power allocation, sub-channel allocation, and efficient user association. The RA for EE is framed as a mixed non-convex and non-linear function using successive convex approximation and sum ratio decoupling convert in convex and linear. A bisection method was used to achieve optimal RA, user association, and sub-channel assignment. The simulation shows energy efficiency (EE) improvement. Similarly, it is observed that MMPCA outperforms the WFA.