MMSE Channel Estimation in Fading MIMO Gaussian Channels With Blockage: A Novel Lower Bound via Poincaré Inequality

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 (M...

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Bibliographic Details
Published inarXiv.org
Main Authors Mohajer, Mohammadreza Bakhshizadeh, Barletta, Luca, Tuninetti, Daniela, Tomasoni, Alessandro, Daniele Lo Iacono, Osnato, Fabio
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 30.10.2024
Subjects
Channels
Cramer-Rao bounds
Fading
Lower bounds
MIMO communication
Performance measurement
Waveforms
Wireless communications
Wireless networks
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Summary: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.
ISSN:2331-8422