A Bayesian Framework For Cascaded Channel Estimation in RIS-Aided mmWave Systems
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arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866908600375443456 |
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| author | Lee, Gyoseung Choi, Junil |
| author_facet | Lee, Gyoseung Choi, Junil |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_01117 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Bayesian Framework For Cascaded Channel Estimation in RIS-Aided mmWave Systems Lee, Gyoseung Choi, Junil Signal Processing Information Theory 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. |
| title | A Bayesian Framework For Cascaded Channel Estimation in RIS-Aided mmWave Systems |
| topic | Signal Processing Information Theory |
| url | https://arxiv.org/abs/2509.01117 |