A Unified Deep Learning Method for CSI Feedback in Massive MIMO Systems
Release Date：2023-01-28
Author：GAO Zhengguang, LI Lun, WU Hao, TU Xuezhen, HAN Bingtao
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Abstract: A unified deep learning (DL) based algorithm is proposed for channel state information (CSI) compression in massive multiple-input multiple-output (MIMO) systems. More importantly, the element filling strategy is investigated to address the problem of model redesigning and retraining for different antenna typologies in practical systems. The results show that the proposed DL-based algorithm achieves better performance than the enhanced Type II algorithm in Release 16 of 3GPP. The proposed element filling strategy enables one-time training of a unified model to compress and reconstruct different channel state matrices in a practical MIMO system.
Keywords: deep learning; channel state information; element filling strategy
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