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Degraded broadcast channels (DBC) are a typical multi-user communicationsscenario. There exist classic transmission methods, such as superpositioncoding with successive interference cancellation, to achieve the DBC capacityregion. However, semantic communications method over DBC remains lack ofin-depth research. To address this, we design a fusion-based multi-usersemantic communications system for wireless image transmission over DBC in thispaper. The proposed architecture supports a transmitter extracting semanticfeatures for two users separately, and learns to dynamically fuse thesesemantic features into a joint latent representation for broadcasting. The keyhere is to design a flexible image semantic fusion (FISF) module to fuse thesemantic features of two users, and to use a multi-layer perceptron (MLP) basedneural network to adjust the weights of different user semantic features forflexible adaptability to different users channels. Experiments present thesemantic performance region based on the peak signal-to-noise ratio (PSNR) ofboth users, and show that the proposed system dominates the traditionalmethods.

Fusion-Based Multi-User Semantic Communications for Wireless Image Transmission over Degraded Broadcast Channels