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*This work is submitted to IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible. J. Chai is with the School of Artificial Intelligence at the Xidian University, Shaanxi 710071, China (e-mail: chaijingxuan@stu.xidian.edu.cn) Y. Xiao is with the School of Electronic Information and Communications at the Huazhong University of Science and Technology, Wuhan 430074, China, also with the Pengcheng Laboratory, Shenzhen, Guangdong 518055, China and also with the Pazhou Laboratory (Huangpu), Guangzhou, Guangdong 510555, China (e-mail: yongxiao@hust.edu.cn). G. Shi is with the Peng Cheng Laboratory, Shenzhen, Guangdong 518055, China, also with the School of Artificial Intelligence, the Xidian University, Xi鈥檃n, Shaanxi 710071, China (e-mail: gmshi@xidian.edu.cn)
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Semantic communication doesn't have to be computationally expensive: this paper introduces a framework that explicitly trades off rate, semantic distortion, and model complexity, enabling efficient system design.
