Rate-Distortion Analysis for Semantic-Aware Multi-Terminal Source Coding Problem

A novel distributed source coding model which named semantic-aware multi-terminal source coding problem is proposed and studied in the paper. This is motivated by the new communication paradigm being aware of semantic information, in which invisible semantic features are observed by multiple agents, and both semantic and observation reconstructions are imposed distortion constraints. The theoretical analysis of this model is provided in this work, in which we present a generalized Berger- Tung based sum rate region considering the semantic source, and further obtain upper and lower bounds when sources are joint Gaussian distributed. Under this case, the tradeoff between two distortions and optimal rate allocation scheme are discussed. Moreover, since the model couples the conventional multiterminal coding and CEO problems, the degeneration of generalized bounds to existing works are shown. Finally, we also present the sum rate bounds in special cases when sources are Bernoulli and distortion measure adopts logarithmic loss.