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1.
  • Liu, Runnan, et al. (author)
  • Detecting Abrupt Change in Channel Covariance Matrix for MIMO Communication
  • 2023
  • In: IEEE Transactions on Wireless Communications. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 1536-1276 .- 1558-2248. ; 22:11, s. 7834-7847
  • Journal article (peer-reviewed)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.
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2.
  • Liu, Runnan, et al. (author)
  • Detection of Abrupt Change in Channel Covariance Matrix for Multi-Antenna Communication
  • 2021
  • In: 2021 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM). - : IEEE. - 9781728181042
  • Conference paper (peer-reviewed)abstract
    • The knowledge of channel covariance matrices is of paramount importance to the estimation of instantaneous channels and the design of beamforming vectors in multi-antenna systems. In practice, an abrupt change in channel covariance matrices may occur due to the change in the environment and the user location. Although several works have proposed efficient algorithms to estimate the channel covariance matrices after any change occurs, how to detect such a change accurately and quickly is still an open problem in the literature. In this paper, we focus on channel covariance change detection between a multiantenna base station (BS) and a single-antenna user equipment (UE). To provide theoretical performance limit, we first propose a genie-aided change detector based on the log-likelihood ratio (LLR) test assuming the channel covariance matrix after change is known, and characterize the corresponding missed detection and false alarm probabilities. Then, this paper considers the practical case where the channel covariance matrix after change is unknown. The maximum likelihood (ML) estimation technique is used to predict the covariance matrix based on the received pilot signals over a certain number of coherence blocks, building upon which the LLR-based change detector is employed. Numerical results show that our proposed scheme can detect the change with low error probability even when the number of channel samples is small such that the estimation of the covariance matrix is not that accurate. This result verifies the possibility to detect the channel covariance change both accurately and quickly in practice.
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  • Result 1-2 of 2
Type of publication
conference paper (1)
journal article (1)
Type of content
peer-reviewed (2)
Author/Editor
Larsson, Erik G (2)
Liu, Liang (2)
Zhang, Wenjun (2)
Liu, Runnan (2)
He, Dazhi (2)
University
Linköping University (2)
Language
English (2)
Research subject (UKÄ/SCB)
Engineering and Technology (2)

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