  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 to partition the users with distinct link
qualities, which is imperative for harnessing NOMA performance gains. Our
analysis is focused on the performance of a user cluster in 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 with the
objective of maximizing the cell sum rate (CSR) under NRT service, and the sum
effective capacity (SEC) under RT service. In addition to providing several
useful design insights, our results demonstrate that NOMA provides improved
rate region and higher CSR as compared to OMA. In addition, we also show that
NOMA provides better SEC as compared to OMA for the higher user density.
