Foundation models,such as generative pre-trained transformers(GPT),have gained significant attention due to their applications across various computational tasks.This paper introduces the concept of wireless foundation models,which extend these capabilities to the wireless communication domain.The fundamental concept of wireless foundation models is presented,followed by a review of the current research landscape in four key aspects:security,privacy,ethics,and energy efficiency.In terms of security,threats such as poisoning attacks and backdoor attacks are analyzed.For privacy protection,techniques like differential privacy and federated learning are explored for safeguarding user data.Energy efficiency is addressed through strategies like model compression and data selection,which aim to balance performance and power consumption.Finally,an architecture for endogenous intelligent wireless foundation models in 6G networks is proposed,highlighting their potential applications in cloud-edge collaborative computing,semantic communication,and cross-domain integration.
关键词
6G/AI大模型/联邦学习/语义通信
Key words
6G/AI foundation models/federated learning/semantic communication
维普
万方数据