A Superposition Code Approach for Digital Semantic Communications over Broadcast Channels

This paper investigates digital semantic communications over broadcast channels, where the transmitter has a common observable source to transmit, but the receivers desire to recover different levels of semantic information in adaptation to their respective channel conditions. Inspired by the capacity-achieving superposition coding structure for degraded broadcast channel, we propose a superposition coded modulation (SCM) scheme for semantic information transmission over a two-receiver Gaussian broadcast channel. In specific, the transmitter consists of two separate neural network (NN)-based semantic encoders, one NN-based linear minimum mean square error (LMMSE) decorrelator, and one superposition-based digital modulator. The SCM scheme enables the receiver with lower signal-to-noise ratio (SNR) to decode basic semantic information while the receiver with larger SNR can decode enhanced semantic information. Experiments are conducted on image transmission with coarse and fine classifications as semantics. Results show that our proposed SCM scheme outperforms the basic coded-modulation scheme without a superposition structure for both receivers, especially when channel conditions of the two receivers differ significantly. It also approaches the performance upperbound as if there were only one receiver.