Score-Based Generative Models for Wireless Channel Modeling and EstimationDownload PDF

Published: 29 Mar 2022, Last Modified: 05 May 2023ICLR 2022 DGM4HSD workshop PosterReaders: Everyone
Keywords: score-based, generative, wireless, estimation
TL;DR: Score-based models are very good at wireless channel modeling
Abstract: In this work, we investigate score-based models for learning the distribution of multiple-input multiple-output (MIMO) wireless channels in structured stochastic environments, using either clean or corrupted (noisy) data for training. We find that score-based models are capable of generating high-quality synthetic channels, and have robust downstream estimation performance, sometimes surpassing strong baselines by up to $10$ dB in estimation error, when the inverse problem is ill-posed. Our preliminary results on training with corrupted data show improved performance against simple baselines, and introduce a very promising future research direction. Code will be made publicly available upon paper acceptance.
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