Performance Analysis of Cooperative NOMA Schemes in Spatially Random Relaying Networks

Jianchao Chen, Liang Yang*, Mohamed Slim Alouini

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

20 Scopus citations


In this paper, we propose a general framework to investigate cooperative non-orthogonal multiple access (NOMA) using two-stage relay selection (TSRS) in spatially random relaying networks. More specifically, we consider both amplify-And-forward and decode-And-forward protocols and compare the performance between them. From practical consideration, we adopt a stochastic geometry-based model and assume that the spatial topology of relays is modeled by using homogeneous Poisson point process (PPP). Based on such a setting, an effective coverage area of the relays modeled by using homogeneous PPP in cooperative NOMA systems is developed and performance comparison between TSRS and the conventional max-min RS scheme is also presented. According to the locations of the NOMA users, we develop the complete strategies for calculating the effective coverage area of the relays. Furthermore, in the high signal-To-noise ratio regime, asymptotic expressions are provided to show that the outage probability tends to a constant which is only related to the density of homogeneous PPP and the effective coverage area of the relays. For a given outage probability, we reveal the relationship between the shortest and longest radii of the effective district of the relays. Finally, Monte Carlo simulations are provided to verify the accuracy of the analytical results.

Original languageEnglish (US)
Pages (from-to)33159-33168
Number of pages10
JournalIEEE Access
StatePublished - Jun 12 2018

Bibliographical note

Publisher Copyright:
© 2013 IEEE.


  • Amplify-And-forward (AF)
  • decode-And-forward (DF)
  • homogeneous Poisson point process (PPP)
  • non-orthogonal multiple access (NOMA)
  • two-stage relay selection (TSRS)

ASJC Scopus subject areas

  • General Engineering
  • General Computer Science
  • General Materials Science


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