Domain Adaptation-Enabled Realistic Map-Based Channel Estimation for MIMO-OFDM
Thien Hieu Hoang, Tri Nhu Do, and Georges Kaddoum

TL;DR
This paper introduces a domain adaptation method for MIMO-OFDM channel estimation that leverages realistic simulations to improve robustness and generalization in dynamic wireless environments.
Contribution
It proposes a novel domain adaptation framework that bridges quasi-static and map-based channel models, enhancing practical channel estimation performance.
Findings
Robust performance with limited true channel data
Effective simulation-based training reduces data needs
Improved generalization across diverse environments
Abstract
Accurate channel estimation is crucial for the improvement of signal processing performance in wireless communications. However, traditional model-based methods frequently experience difficulties in dynamic environments. Similarly, alternative machine-learning approaches typically lack generalization across different datasets due to variations in channel characteristics. To address this issue, in this study, we propose a novel domain adaptation approach to bridge the gap between the quasi-static channel model (QSCM) and the map-based channel model (MBCM). Specifically, we first proposed a channel estimation pipeline that takes into account realistic channel simulation to train our foundation model. Then, we proposed domain adaptation methods to address the estimation problem. Using simulation-based training to reduce data requirements for effective application in practical wireless…
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Taxonomy
TopicsAdvanced MIMO Systems Optimization · Advanced Wireless Communication Techniques · Cooperative Communication and Network Coding
