Downlink Analysis of NOMA-Enabled Cellular Networks With 3GPP-Inspired User Ranking

Abstract

This paper provides a comprehensive downlink analysis of non-orthogonal multiple access (NOMA) enabled cellular networks using tools from stochastic geometry. As a part of this analysis, we develop a novel 3GPP-inspired user ranking technique to construct a user cluster for the non-orthogonal transmission by grouping users from the cell center (CC) and cell edge (CE) regions. This technique allows the pairing of users with distinct link qualities, which is imperative for harnessing NOMA performance gains. The analysis is performed from the perspective of the typical cell , which is significantly different from the standard stochastic geometry-based approach of analyzing the performance of the typical user . For this setting, we first derive the moments of the meta distributions for the CC and CE users under NOMA and orthogonal multiple access (OMA). Using this, we then derive the distributions of the transmission rates and mean packet delays under non-real time (NRT) and real-time (RT) service models, respectively, for both CC and CE users. Finally, we study two resource allocation (RA) techniques to maximize the cell sum-rate ( $\mathtt {CSR}$ ) under NRT service, and the sum effective capacity ( $\mathtt {SEC}$ ) under RT service. In addition to providing several useful design insights, our results demonstrate that NOMA provides improved rate region and higher $\mathtt {CSR}$ as compared to OMA. In addition, we also show that NOMA provides better $\mathtt {SEC}$ as compared to OMA for the higher user density.