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This paper provides a comprehensive downlink analysis of non-orthogonalmultiple access (NOMA) enabled cellular networks using tools from stochasticgeometry. As a part of this analysis, we develop a novel 3GPP-inspired userranking technique to construct a user cluster for the non-orthogonaltransmission by grouping users from the cell center (CC) and cell edge (CE)regions. This technique allows to partition the users with distinct linkqualities, which is imperative for harnessing NOMA performance gains. Ouranalysis is focused on the performance of a user cluster in the typical cell,which is significantly different from the standard stochastic geometry-basedapproach of analyzing the performance of the typical user. For this setting, wefirst derive the moments of the meta distributions for the CC and CE usersunder NOMA and orthogonal multiple access (OMA). Using this, we then derive thedistributions of the transmission rates and mean packet delays under non-realtime (NRT) and real-time (RT) service models, respectively, for both CC and CEusers. Finally, we study two resource allocation (RA) techniques with theobjective of maximizing the cell sum rate (CSR) under NRT service, and the sumeffective capacity (SEC) under RT service. In addition to providing severaluseful design insights, our results demonstrate that NOMA provides improvedrate region and higher CSR as compared to OMA. In addition, we also show thatNOMA provides better SEC as compared to OMA for the higher user density.

Downlink Analysis of NOMA-enabled Cellular Networks with 3GPP-inspired User Ranking