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arXiv · 2509.01117

A Bayesian Framework For Cascaded Channel Estimation in RIS-Aided mmWave Systems

Gyoseung Lee·Junil Choi
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Abstract

In this paper, we investigate cascaded channel estimation for reconfigurable intelligent surface (RIS)-aided millimeter-wave multi-user communication systems. Since the complex channel gains of the cascaded RIS channel are generally non-Gaussian, the use of the linear minimum mean squared error (LMMSE) estimator leads to inevitable performance degradation. To tackle this issue, we propose a variational inference-based framework that approximates the complex channel gains using a complex adaptive Laplace prior, which effectively captures their probability distributions in a tractable way. Numerical results demonstrate that the proposed estimator outperforms conventional estimators including least squares and LMMSE in terms of cascaded channel estimation error.

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Gyoseung Lee, Junil Choi. 2025-09-01. A Bayesian Framework For Cascaded Channel Estimation in RIS-Aided mmWave Systems. https://arxiv.org/abs/2509.01117

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