Abstract: In order to meet the demand of efficient information transmission between intelligent communication entities, semantic communication research is faced with the basic problems of semantic information representation, encoding and transmission. In view of the communication resource shortage and task delay sensitive transmission scenario of everything intelligent link, a semantic coding algorithm based on semantic importance was proposed, and a semantic communication experiment platform was designed and built to realize semantic information transmission. Firstly, the intelligent task-oriented semantic communication system model was established based on the basic process of wireless communication. Secondly, a semantic importance extraction method was designed to obtain the importance weights of the feature maps to the task results by aggregating the channel features and adaptively calibrating the feature responses. Then, a semantic compression method was designed to filter the feature maps according to the importance weight in the actual transmission to achieve semantic data compression. Finally, the performance of the proposed algorithm was verified on the semantic communication platform by taking the task of surface defect classification of hot rolled strip steel in the industrial Internet scene as an example. Experimental result shows that the proposed algorithm has the advantages of small data transmission, strong anti-noise ability and short task processing delay.

Key words: semantic communication, semantic coding, image classification, experimental platform