Semantic Communication Meets Edge Intelligence

The development of emerging applications, such as autonomous transportation systems, is expected to result in an explosive growth mobile data traffic. As the available spectrum resource becomes more and scarce, there a growing need for paradigm shift from Shannon's Classical Information Theory (CIT) semantic communication (SemCom). Specifically, former adopts “transmit-before-understanding” approach while latter leverages artificial intelligence (AI) techniques “understand-before-transmit,” thereby alleviating bandwidth pressure by reducing amount be exchanged without negating effectiveness transmitted symbols. However, extraction (SE) procedure incurs costly computation storage overheads. In this article, we introduce edge-driven training, maintenance, execution SE. We further investigate how edge can enhanced with SemCom through improving generalization capabilities intelligent agents at lower overheads overhead information exchange. Finally, present case study involving semantic-aware optimization wireless powered Internet Things (IoT).