Performance Analysis of Non-Regenerative Massive-MIMO-NOMA Relay Systems for 5G

Di Zhang, Yuanwei Liu, Zhiguo Ding, Zhenyu Zhou, Arumugam Nallanathan, Takuro Sato

Research output: Contribution to journalArticlepeer-review

58 Citations (Scopus)

Abstract

The non-regenerative massive multi-input-multi-output (MIMO) non-orthogonal multiple access (NOMA) relay systems are introduced in this paper. The NOMA is invoked with a superposition coding technique at the transmitter and successive interference cancellation (SIC) technique at the receiver. In addition, a maximum mean square error-SIC receiver design is adopted. With the aid of deterministic equivalent and matrix analysis tools, a closed-form expression of the signal to interference plus noise ratio (SINR) is derived. To characterize the performance of the considered systems, closed-form expressions of the capacity and sum rate are further obtained based on the derived SINR expression. Insights from the derived analytical results demonstrate that the ratio between the transmitter antenna number and the relay number is a dominate factor of the system performance. Afterward, the correctness of the derived expressions are verified by the Monte Carlo simulations with numerical results. Simulation results also illustrate that: 1) the transmitter antenna, averaged power value, and user number display the positive correlations on the capacity and sum rate performances, whereas the relay number displays a negative correlation on the performance and 2) the combined massive-MIMO-NOMA scheme is capable of achieving higher capacity performance compared with the conventional MIMO-NOMA, relay-assisted NOMA, and massive-MIMO orthogonal multiple access (OMA) scheme.

Original languageEnglish
Article number8010439
Pages (from-to)4777-4790
Number of pages14
JournalIEEE Transactions on Communications
Volume65
Issue number11
DOIs
Publication statusPublished - 2017 Nov

Keywords

  • 5G
  • MMSE-SIC
  • Massive MIMO
  • NOMA
  • Non-regenerative relay assisted systems

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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