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Spectrum efficiency analysis of signal alignment-based beamspace millimetre wave MIMO-NOMA systems

  • Ahmed Abdelaziz Salem*
  • , A. M. Benaya
  • , Sayed El-Rabaie
  • , Mona Shokair
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Non-orthogonal multiple access (NOMA) has been integrated with beamspace multi-input multi-output (MIMO) to enhance system spectrum efficiency (SE) by serving more than one user per dedicated radio frequency (RF) chain. However, balancing the system performance with significant RF reduction is still challenging. In this study, the authors propose beamspace MIMO-NOMA system based on signal alignment (SA) concept, where they will be able to tackle the issue of hardware complexity with a significant performance. Spectrum and energy efficiencies are analysed through two main stages. First, the excess degrees-of-freedom of beamspace MIMO-NOMA are exploited by SA to suppress the inter-beam/pair interference through designing user detection vectors and precoding matrix. Accordingly, a significant RF-chains reduction is provided. Second, power allocation coefficients are evaluated upon the optimal SE in order to mitigate intra-beam/pair interference. Moreover, the authors derive a tight closed formula for optimal SE based on Karush-Kuhn-Tucker analysis, which is validated by a heuristic-based optimal solution. Simulation results show a superior performance gain over orthogonal multiple access technique. Furthermore, the Monte-Carlo numerical solution depicts the marginal performance gap between the analytical and heuristic-based optimisation approach. This confirms the accuracy and rigidity of the proposed system.

Original languageEnglish
Pages (from-to)818-829
Number of pages12
JournalIET Communications
Volume14
Issue number5
DOIs
StatePublished - 17 Mar 2020
Externally publishedYes

Bibliographical note

Publisher Copyright:
© The Institution of Engineering and Technology 2019

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering

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