Variational Bayes inference for data detection in cell-free massive MIMO

Ly V. Nguyen, Hien Quoc Ngo, Le-Nam Tran, A. Lee Swindlehurst, Duy H.N. Nguyen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Cell-free massive MIMO is a promising technology for beyond-5G networks. Through the deployment of many cooperating access points (AP), the technology can significantly enhance user coverage and spectral efficiency compared to traditional cellular systems. Since the APs are distributed over a large area, the level of favorable propagation in cell-free massive MIMO is less than the one in colocated massive MIMO. As a result, the current linear processing schemes are not close to the optimal ones when the number of AP antennas is not very large. The aim of this paper is to develop nonlinear variational Bayes (VB) methods for data detection in cell-free massive MIMO systems. Contrary to existing work in the literature, which only attained point estimates of the transmit data symbols, the proposed methods aim to obtain the posterior distribution and the Bayes estimate of the data symbols. We develop the VB methods accordingly to the levels of cooperation among the APs. Simulation results show significant performance advantages of the developed VB methods over the linear processing techniques.

Original languageEnglish
Title of host publication56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022: Proceedings
EditorsMichael B. Matthews
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages727-732
Number of pages6
ISBN (Electronic)9781665459068
DOIs
Publication statusPublished - 07 Mar 2023
Event56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022 - Virtual, Online, United States
Duration: 31 Oct 202202 Nov 2022

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2022-October
ISSN (Print)1058-6393
ISSN (Electronic)2576-2303

Conference

Conference56th Asilomar Conference on Signals, Systems and Computers, ACSSC 2022
Country/TerritoryUnited States
CityVirtual, Online
Period31/10/202202/11/2022

Bibliographical note

Funding Information:
This work was supported by the U.S. National Science Foundation under Grants ECCS-2146436 and CCF-2225576.

Publisher Copyright:
© 2022 IEEE.

Keywords

  • Cell-free
  • inference
  • massive MIMO
  • variational Bayes

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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