Forcible search scheme for mixed gibbs sampling massive mimo detection

Kenji YAMAZAKI, Yukitoshi SANADA

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, mixed Gibbs sampling multiple-input multiple-output (MIMO) detection with forcible search is proposed. In conventional Gibbs sampling MIMO detection, the problem of stalling occurs under high signal-to-noise ratios (SNRs) which degrades the detection performance. Mixed Gibbs sampling (MGS) is one solution to this problem. In MGS, random sampling is carried out with a constant probability regardless of whether a current search falls into a local minimum. In the proposed scheme, combined with MGS, multiple candidate symbols are forcibly changed when the search is captured by a local minimum. The search restarts away from the local minimum which effectively enlarges the search area in the solution space. Numerical results obtained through computer simulation show that the proposed scheme achieves better performance in a large scale MIMO system with QPSK signals.

Original languageEnglish
Pages (from-to)419-427
Number of pages9
JournalIEICE Transactions on Communications
VolumeE104.B
Issue number4
DOIs
Publication statusPublished - 2021 Apr

Keywords

  • Gibbs sampling
  • MIMO detection

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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