Efficient beamforming and channel estimation techniques for RIS-aided massive MIMO under practical impairments

Date

2026-7-29

Author

Özen, Hakan

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Reconfigurable intelligent surface (RIS)-aided massive multiple-input multiple-output (MIMO) systems have emerged as a promising paradigm for next-generation wireless communications, offering controllable propagation environments with low hardware complexity. However, the practical deployment of such systems at millimeter-wave (mmWave) frequencies introduces several critical challenges that are often overlooked in idealized analyses. In particular, spatial- and frequency-wideband (dual-wideband) propagation effects give rise to the beam-squint phenomenon, which can cause significant performance degradation if not properly addressed. Moreover, practical RIS hardware is subject to inherent impairments such as amplitude-phase coupling (APC) and amplitude-phase-frequency coupling (APFC), which further complicate system design and should be explicitly accounted for. This thesis presents a comprehensive study of channel estimation and RIS beamforming for RIS-aided MIMO systems under these practical constraints. On the channel estimation front, beam-squint-aware frameworks are developed to accurately estimate cascaded channel parameters. Additionally, cascaded channel covariance matrix (C-CCM) estimation is extensively studied under these practical considerations such as beam-squint-effect (BSE), APC/APFC, and angular spread (angular dispersion). The proposed methods leverage tools from compressed sensing and subspace-based processing to achieve efficient and accurate estimation. On the beamforming front, statistical RIS designs are proposed that are jointly aware of beam squint and hardware impairments, and are optimized with respect to signal-to-noise ratio (SNR), statistical mutual information (SMI), and ergodic capacity. Throughout, hypothetical genie-aided bounds and/or theoretical performance bounds are derived and simulation results consistently demonstrate the superiority of the proposed methods over conventional methods in terms of estimation accuracy, spectral efficiency, and outage capacity.

Subject Keywords

RIS, RIS channel estimation, C-CCM estimation, RIS beamforming, MIMO

URI

https://hdl.handle.net/11511/120635

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Graduate School of Natural and Applied Sciences, Thesis