NOMA and OMA-Based Massive MIMO and Clustering Algorithms for Beyond 5G IoT Networks

Abstract

The Internet of Things (IoT) has brought about various global changes, as all devices will be connected. This article examines the latest 5G solutions for enabling a massive cellular network. It further explored the gaps in previously published articles, demonstrating that to deal with the new challenges. The mobile network must use massive multiple input and output (MIMO), nonorthogonal multiple access (NOMA), orthogonal multiple access (OMA), signal interference cancellation (SIC), channel state information (CSI), and clustering. Furthermore, this article has two objectives such as (1) to introduce the cluster base NOMA to reduce the computational complexity by applying SIC on a cluster, which ultimately results in faster communication and (2) to achieve massive connectivity by proposing massive MIMO with NOMA and OMA. The proposed NOMA clustering technique working principle pairs the close user with the far user; thus, it will reduce computational complexity, which was one such big dilemma in the existing articles. This will specifically help those users that are far away from the base station by maintaining the connectivity. Despite NOMA’s extraordinary benefits, one cannot deny the significance of the OMA; hence, the other objective of the proposed work is to introduce OMA with MIMO in small areas where the user is low in number, it is already in use, and quite cheap. The next important aspect of the proposed work is SIC, which helps remove interference and leads to enhancement in network performance. The simulation result has clearly stated that NOMA has gained a higher rate than OMA: current NOMA users’ power requirement (weak signal user 0.06, strong signal user 0.07), spectral efficiency ratio for P-NOMA and C-NOMA (21%, 5%), signal-to-noise ratio OMA, P-NOMA, C-NOMA (28, 40, 55%), and user rate pairs NOMA, OMA (7, 3), C-NOMA, and massive MIMO NOMA SINR (4.0, 2.5).