Hybrid TDMA-NOMA Based M2M Communications over Cellular Networks with Dynamic Clustering and 3D Channel Models

Abstract

Machine-to-Machine (M2M) communications will be experiencing multifarious challenges and complexities in the future standardization of 5G cellular networks. This paper proposes a neoteric architecture for M2M communication over the 5G cellular networks. Dynamic clustering method is applied in order to increase the system throughput and balance the power consumption within the machines increasing their battery life. For communication from CH to member machines and CH to BS, hybrid multiple access technology comprising time division multiple access (TDMA) and non-orthogonal multiple access (NOMA) technology is proposed. NOMA based power coding and successive interference cancellation (SIC) is implemented on CH and BS. Extensive simulations are carried out for evaluating the system performance considering the newly developed 3D 5G wireless channel models. Results clearly demonstrates the capability of the proposed architecture in improving the energy efficiency, throughput and lifetime of machines. Comparisons with other counterparts also attests superior energy efficiency and throughput performance of the proposed architecture.