2019/08/05 by Praful D. Mankar, Harpreet S. Dhillon, Mankar, Praful D. +1
Engineering · #Advanced Wireless Communication Technologies #FOS: Computer and information sciences #Information Theory (cs.IT) #Optical Wireless Communication Technologies #Satellite Communication Systems
paper · pdf · doi:10.48550/arxiv.1908.01460
openalex publication_date 2019/08/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper provides a comprehensive downlink analysis of non-orthogonal\nmultiple access (NOMA) enabled cellular networks using tools from stochastic\ngeometry. As a part of this analysis, we develop a novel 3GPP-inspired user\nranking technique to construct a user cluster for the non-orthogonal\ntransmission by grouping users from the cell center (CC) and cell edge (CE)\nregions. This technique allows to partition the users with distinct link\nqualities, which is imperative for harnessing NOMA performance gains. Our\nanalysis is focused on the performance of a user cluster in the typical cell,\nwhich is significantly different from the standard stochastic geometry-based\napproach of analyzing the performance of the typical user. For this setting, we\nfirst derive the moments of the meta distributions for the CC and CE users\nunder NOMA and orthogonal multiple access (OMA). Using this, we then derive the\ndistributions of the transmission rates and mean packet delays under non-real\ntime (NRT) and real-time (RT) service models, respectively, for both CC and CE\nusers. Finally, we study two resource allocation (RA) techniques with the\nobjective of maximizing the cell sum rate (CSR) under NRT service, and the sum\neffective capacity (SEC) under RT service. In addition to providing several\nuseful design insights, our results demonstrate that NOMA provides improved\nrate region and higher CSR as compared to OMA. In addition, we also show that\nNOMA provides better SEC as compared to OMA for the higher user density.\n