MMSE Channel Estimation in Fading MIMO Gaussian Channels With Blockage: A Novel Lower Bound via Poincaré Inequality
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arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866910678400368640 |
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| author | Mohajer, Mohammadreza Bakhshizadeh Barletta, Luca Tuninetti, Daniela Tomasoni, Alessandro Iacono, Daniele Lo Osnato, Fabio |
| author_facet | Mohajer, Mohammadreza Bakhshizadeh Barletta, Luca Tuninetti, Daniela Tomasoni, Alessandro Iacono, Daniele Lo Osnato, Fabio |
| contents | Integrated sensing and communication is regarded as a key enabler for next-generation wireless networks. To optimize the transmitted waveform for both sensing and communication, various performance metrics must be considered. This work focuses on sensing, and specifically on the mean square error (MSE) of channel estimation. Given the complexity of deriving the MSE, the Bayesian Cramer-Rao Bound (BCRB) is commonly recognized as a lower bound on the minimum MSE. However, the BCRB is not applicable to channels with discrete or mixed distributions. To address this limitation, a new lower bound based on a Poincaré inequality is proposed and applied to fading MIMO AWGN channels with blockage probability, and the behavior of the lower bound at high SNR is precisely characterized. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_22941 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | MMSE Channel Estimation in Fading MIMO Gaussian Channels With Blockage: A Novel Lower Bound via Poincaré Inequality Mohajer, Mohammadreza Bakhshizadeh Barletta, Luca Tuninetti, Daniela Tomasoni, Alessandro Iacono, Daniele Lo Osnato, Fabio Information Theory Integrated sensing and communication is regarded as a key enabler for next-generation wireless networks. To optimize the transmitted waveform for both sensing and communication, various performance metrics must be considered. This work focuses on sensing, and specifically on the mean square error (MSE) of channel estimation. Given the complexity of deriving the MSE, the Bayesian Cramer-Rao Bound (BCRB) is commonly recognized as a lower bound on the minimum MSE. However, the BCRB is not applicable to channels with discrete or mixed distributions. To address this limitation, a new lower bound based on a Poincaré inequality is proposed and applied to fading MIMO AWGN channels with blockage probability, and the behavior of the lower bound at high SNR is precisely characterized. |
| title | MMSE Channel Estimation in Fading MIMO Gaussian Channels With Blockage: A Novel Lower Bound via Poincaré Inequality |
| topic | Information Theory |
| url | https://arxiv.org/abs/2410.22941 |