Detecting Abrupt Change in Channel Covariance Matrix for MIMO Communication

Runnan Liu, Liang Liu, Dazhi He, Wenjun Zhang, Erik G. Larsson

Research output: Journal article publicationJournal articleAcademic researchpeer-review

3 Citations (Scopus)

Abstract

The acquisition of the channel covariance matrix is of paramount importance to many strategies in multiple-input-multiple-output (MIMO) communications, such as the minimum mean-square error (MMSE) channel estimation. Therefore, plenty of efficient channel covariance matrix estimation schemes have been proposed in the literature. However, an abrupt change in the channel covariance matrix may happen occasionally in practice due to the change in the scattering environment and the user location. Our paper aims to adopt the classic change detection theory to detect the change in the channel covariance matrix as accurately and quickly as possible such that the new covariance matrix can be re-estimated in time. Specifically, this paper first considers the technique of on-line change detection (also known as quickest/sequential change detection), where we need to detect whether a change in the channel covariance matrix occurs at each channel coherence time interval. Next, because the complexity of detecting the change in a high-dimension covariance matrix at each coherence time interval is too high, we devise a low-complexity off-line strategy in massive MIMO systems, where change detection is merely performed at the last channel coherence time interval of a given time period. Numerical results show that our proposed on-line and off-line schemes can detect the channel covariance change with a small delay and a low false alarm rate. Therefore, our paper theoretically and numerically verifies the feasibility of detecting the channel covariance change accurately and quickly in practice.

Original languageEnglish
Article number10077554
Pages (from-to)1
Number of pages1
JournalIEEE Transactions on Wireless Communications
DOIs
Publication statusAccepted/In press - 20 Mar 2023

Keywords

  • change detection
  • Channel estimation
  • Coherence time
  • Covariance matrices
  • Delays
  • MIMO communication
  • Multiple-input multiple-output (MIMO)
  • off-line change detection
  • quickest (sequential) change detection
  • Scattering
  • Wireless communication

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

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