This paper focuses on a typical uplink transmission scenario over multiple-input multiple-output multiple access channel (MIMO-MAC) and thus propose a multi-user learnable CSI fusion semantic communication (MU-LCFSC) framework. It incorporates CSI as the side information into both the semantic encoders and decoders to generate a proper feature mask map in order to produce a more robust attention weight distribution. Especially for the decoding end, a cooperative successive interference cancellation procedure is conducted along with a cooperative mask ratio generator, which flexibly controls the mask elements of feature mask maps. Numerical results verify the superiority of proposed MU-LCFSC compared to DeepJSCC-NOMA over 3 dB in terms of PSNR.
@article{arxiv.2504.07969,
title = {Multi-user Wireless Image Semantic Transmission over MIMO Multiple Access Channels},
author = {Bingyan Xie and Yongpeng Wu and Feng Shu and Jiangzhou Wang and Wenjun Zhang},
journal= {arXiv preprint arXiv:2504.07969},
year = {2025}
}
Comments
This paper has been accepted by IEEE Wireless Communications Letters