Semantic Utility Loss of Information for Energy Efficient Semantic Status Update Communications

Semantic status update communication (SSUC) is envisioned to provide content-aware and energy efficient information delivery. In this paper, we introduce a new metric in the SSUC system, named Semantic Utility Loss (SUL), which captures both age penalty and estimated error for semantic information. By incorporating the knowledge base (KB)-enabled semantic network into a discrete time Markov chain, we investigate the SUL in a time-slotted status update system. The transmitter samples and extracts the semantic information from the physical process, and transmits the status updates. The receiver can update the local KB to keep semantic match with the transmitter and infer or recover the semantic information from received status updates. To minimize the weighted sum of SUL and energy cost incurred by transmitting status update and updating KB, we formulate an infinite horizon average cost Markov Decision Process. We prove that the joint transmission and updating scheduling policy has optimal threshold structure with respect to SUL. Simulation results show that the optimized policy outperforms the zero-wait and sample-at-change policies. Furthermore, we study a practical SSUC application to validate the superiority of proposed framework over the traditional non-semantic status update system in terms of improving the timeliness and reducing the energy consumption.