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Bayesian Channel Estimation Under Dual Wideband Effects for THz Massive MIMO Communications

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Abstract

Terahertz (THz) communication, with its ultra-wide bandwidth of tens of GHz, holds promise for 6th generation networks. However, employing large bandwidth and massive antennas can lead to delay and beam squint effects (together called dual wideband effects), which are not extensively explored in THz massive multi-input multi-output (MIMO) systems. These effects can cause significant array gain loss and degrade the performance of the system, necessitating the design of transceiver algorithms to address these issues. Also, due to the beam squint effect, analog beamforming/combining will become frequency-dependent. In this paper, we have proposed a sparse Bayesian learning (SBL)-based frequency-selective uplink channel estimation method and an orthogonal matching pursuit-based hybrid combiner for THz massive MIMO systems under dual wideband effects. In addition to the signal propagation loss, THz signal strength varies due to mobility. Furthermore, taking double selectivity (both time and frequency selectivity) into account, we have designed an extended Kalman filter (EKF)-based frequency dependent-phase estimator for the THz massive MIMO systems. The performance of the designed channel and phase estimators is assessed using normalized mean square error and bit error rate. Additionally, the performance of an SBL–EKF-based downlink channel estimator is analyzed for doubly selective THz massive MIMO systems under dual wideband effects. This involves estimating channel gains with SBL and frequency-dependent phases with EKF. Simulation results are presented to compare the performance of the proposed and conventional methods.

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  1. G S Sanyal School of Telecommunications, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, 721302, India

    Soujanya Thallapalli & Debarati Sen

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  1. Soujanya Thallapalli
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  2. Debarati Sen
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Thallapalli, S., Sen, D. Bayesian Channel Estimation Under Dual Wideband Effects for THz Massive MIMO Communications. Wireless Pers Commun (2024). https://doi.org/10.1007/s11277-024-10900-2

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