Downlink Non-Orthogonal Multiple Access (NOMA) in Poisson Networks

Konpal Shaukat Ali*, Martin Haenggi, Hesham Elsawy, Anas Chaaban, Mohamed Slim Alouini

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

56 Scopus citations

Abstract

A network model is considered, where Poisson distributed base stations transmit to N power-domain non-orthogonal multiple access (NOMA) users (UEs) each that employ successive interference cancellation (SIC) for decoding. We propose three models for the clustering of NOMA UEs and consider two different ordering techniques for the NOMA UEs: mean signal power-based and instantaneous signal-to-intercell-interference-and-noise-ratio-based. For each technique, we present a signal-to-interference-and-noise ratio analysis for the coverage of the typical UE. We plot the rate region for the two-user case and show that neither ordering technique is consistently superior to the other. We propose two efficient algorithms for finding a feasible resource allocation that maximize the cell sum rate R tot, for general N, constrained to: 1) a minimum throughput \mathcal T for each UE, 2) identical throughput for all UEs. We show the existence of: 1) an optimum N that maximizes the constrained \mathcal Rtot given a set of network parameters and 2) a critical SIC level necessary for NOMA to outperform orthogonal multiple access. The results highlight the importance in choosing the network parameters N, the constraints, and the ordering technique to balance the \mathcal R tot and fairness requirements. We also show that interference-aware UE clustering can significantly improve performance.

Original languageEnglish
Article number8501939
Pages (from-to)1613-1628
Number of pages16
JournalIEEE Transactions on Communications
Volume67
Issue number2
DOIs
StatePublished - Feb 2019

Bibliographical note

Publisher Copyright:
© 1972-2012 IEEE.

Keywords

  • NOMA
  • Non-orthogonal multiple access
  • resource allocation
  • stochastic geometry

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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