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Data aided MSE-optimal time varying channel tracking in massive MIMO systems

Chopra, R and Murthy, CR (2021) Data aided MSE-optimal time varying channel tracking in massive MIMO systems. In: IEEE Transactions on Signal Processing, 69 . pp. 4219-4233.

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Official URL: https://doi.org/10.1109/TSP.2021.3093762


The temporal variations in the wireless propagation channel, referred to as channel aging, cause a mismatch between the estimated channel and the channel state at the time of data detection. This mismatch has been shown to severely impair the performance of massive MIMO systems. In this paper, we present data aided MSE-optimal channel tracking algorithms to decode the received symbols and update the channel estimates at the base station (BS) and the UEs. These algorithms combine ideas from Kalman filtering for channel tracking and deterministic equivalent analysis for symbol estimation. In the uplink case, we first develop a minimum mean squared error (MMSE) data estimator and the MSE-optimal channel predictor based on the Kalman filtering algorithm. We analytically show that the updated channel estimate obtained from the estimates of the data symbols leads to significantly larger signal to interference-plus-noise ratio (SINR), and hence achievable rate, compared to that obtained from the channel estimate based on pilot symbols. Following this, in the downlink case, we develop an algorithm to track the effective channel at the UEs and analyze its MSE, SINR and achievable rate performance. We show that tracking the effective downlink channel mitigates the effects of channel aging and leads to improved performance. However, since the beamforming matrices at the BS are not updated, downlink channel tracking is not as effective as uplink channel tracking. Finally, via Monte Carlo simulations, we validate our derived results, and demonstrate the gains achievable by tracking the time-varying channels in massive MIMO systems. © 1991-2012 IEEE.

Item Type: Journal Article
Publication: IEEE Transactions on Signal Processing
Publisher: Institute of Electrical and Electronics Engineers Inc.
Additional Information: The copyright for this article belongs to Institute of Electrical and Electronics Engineers Inc.
Keywords: Channel capacity; Kalman filters; Mean square error; MIMO systems; Monte Carlo methods; Signal interference; Signal to noise ratio, Deterministic equivalents; Estimated channels; Kalman filtering algorithms; Minimum mean squared error; Signal to interference plus noise ratio; Temporal variation; Time varying channel; Wireless propagation channels, Time varying networks
Department/Centre: Division of Electrical Sciences > Electrical Communication Engineering
Division of Electrical Sciences > Electrical Engineering
Date Deposited: 21 Nov 2021 16:26
Last Modified: 21 Nov 2021 16:26
URI: http://eprints.iisc.ac.in/id/eprint/69922

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