# Multi-user Wireless Image Semantic Transmission over MIMO Multiple Access Channels

arXiv: https://arxiv.org/abs/2504.07969 · HTML: https://mlsanity.com/paper/2504.07969/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 13 references that are in the map.
- First posted on arXiv 18 Mar 2025.

## Builds on (most cited first, 10 of 10)

- [Swin Transformer: Hierarchical Vision Transformer using Shifted Windows](https://mlsanity.com/paper/2103.14030/) (2021)
- [Deep Learning Enabled Semantic Communication Systems](https://mlsanity.com/paper/2006.10685/) (2020)
- [Nonlinear Transform Source-Channel Coding for Semantic Communications](https://mlsanity.com/paper/2112.10961/) (2021)
- [Unsupervised Deep Image Stitching: Reconstructing Stitched Features to Images](https://mlsanity.com/paper/2106.12859/) (2021)
- [DeepWiVe: Deep-Learning-Aided Wireless Video Transmission](https://mlsanity.com/paper/2111.13034/) (2021)
- [WITT: A Wireless Image Transmission Transformer for Semantic Communications](https://mlsanity.com/paper/2211.00937/) (2022)
- [Distributed Deep Joint Source-Channel Coding over a Multiple Access Channel](https://mlsanity.com/paper/2211.09920/) (2022)
- [Robust Image Semantic Coding with Learnable CSI Fusion Masking over MIMO Fading Channels](https://mlsanity.com/paper/2406.07389/) (2024)
- [Non-Orthogonal Multiple Access Enhanced Multi-User Semantic Communication](https://mlsanity.com/paper/2303.06597/) (2023)
- [A General 3D Non-Stationary 5G Wireless Channel Model](https://mlsanity.com/paper/2311.16783/) (2023)

## Built on by (most cited first, 4 of 4)

- [E2E Learning Massive MIMO for Multimodal Semantic Non-Orthogonal Transmission and Fusion](https://mlsanity.com/paper/2509.19312/) (2025)
- [Robust Nonlinear Transform Coding: A Framework for Generalizable Joint Source-Channel Coding](https://mlsanity.com/paper/2511.18884/) (2025)
- [Context Video Semantic Transmission with Variable Length and Rate Coding over MIMO Channels](https://mlsanity.com/paper/2601.06059/) (2025)
- [Wireless Backdoor Attack and Defense for Semantic Communications over Multiple Access Channel](https://mlsanity.com/paper/2606.30595/) (2026)

## Abstract (arXiv)

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.