{"ID":2875721,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.01117","arxiv_id":"2509.01117","title":"A Bayesian Framework For Cascaded Channel Estimation in RIS-Aided mmWave Systems","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.","short_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...","url_abs":"https://arxiv.org/abs/2509.01117","url_pdf":"https://arxiv.org/pdf/2509.01117v1","authors":"[\"Gyoseung Lee\",\"Junil Choi\"]","published":"2025-09-01T04:22:47Z","proceeding":"eess.SP","tasks":"[\"eess.SP\",\"cs.IT\"]","methods":"[]","has_code":false}