面向6G的语义通信系统

A Semantic Communication System for 6G Networks

语义通信作为一种全新的通信形式,着重关注信息的内涵,可以大幅提升通信效率,并推动实现真正的智能通信。为了提升在6G中部署语义通信系统的可行性,从移动网络边缘资源的利用和减少模型联合更新的通信开销两个维度出发,提出一种结合边缘智能和分割学习的模型联合训练方法和支持实时交互的语义通信机制,并探索了语义通信的数据隐私泄露问题。结果表明在模型切割和传输过程中,需要对模型切割层数进行合理的划分,以保护数据隐私。

Semantic communication is a novel communication form that emphasizes the meaning of information,leading to significant improvements in communication efficiency and enabling true intelligent communication.To enhance the feasibility of deploying semantic communication systems in 6G,from the two views of the resource utilization at mobile network edge and the communication overhead reduction of model joint update,this paper proposes a model joint training method combining edge intelligence and segmentation learning,and a real-time interactive semantic communication mechanism is also proposed.Furthermore,privacy issues in semantic communication are explored.The results show that a reasonable division of model segmentation layers is crucial during the model segmentation and transmission process to protect data privacy.