This book covers the foundations and system design of semantic wireless communications from a joint communication and computation perspective. It introduces semantic and task-oriented communication, semantic information metrics, and key modeling tools such as autoencoders, semantic entropy, knowledge graphs, and probability graphs. It then develops resource-allocation methods for semantic similarity maximization and equivalent-rate and energy optimization under practical wireless constraints.

Later chapters connect these ideas to emerging 6G scenarios. This includes probabilistic semantic communication over space-air-ground integrated networks, federated learning for audio semantic communication, integrated sensing/computing/semantic communication for e-healthcare, semantic feature multiple access with generative AI, and security and privacy. 

This book is intended for researchers and graduate students, as well as engineers building wireless, edge-intelligence, and AI-native network systems. It combines mathematical models, optimization formulations, algorithm design, simulation studies, and open research directions.