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Joint User Grouping and Beam Selection for Beamspace mmWave Multi-User MIMO System

  • Jintian Sun
  • , Min Jia*
  • , Qing Guo
  • , Xuemai Gu
  • *Corresponding author for this work
  • School of Electronics and Information Engineering, Harbin Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

Lens antenna arrays based beamspace millimeter-wave multi-user massive MIMO (B-MIMO) can significantly improve energy efficiency without significant loss of spectral efficiency (SE), which is considered as a highly expected technology for future wireless communication networks. Motivated by the requirement of reducing SE loss by efficient user grouping (UG) and beam selection (BS), a joint user grouping and beam selection algorithm is studied. Specifically, a local search based BS algorithm is proposed by proving the convexity of the BS problem after relaxing the constraints. Moreover, a deep learning based UG algorithm is proposed by equivalently transforming the UG problem into a classification problem. The results of theoretical analysis and numerical simulation show that the proposed algorithms can be more closely with the performance of the exhaustive search algorithm and the complexity is lower than that of the traditional algorithms.

Original languageEnglish
Pages (from-to)1170-1174
Number of pages5
JournalIEEE Communications Letters
Volume26
Issue number5
DOIs
StatePublished - 1 May 2022
Externally publishedYes

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

Keywords

  • Beam selection
  • Deep learning
  • Lens antenna array
  • Massive MIMO
  • User grouping

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