构建无线网络内生智能通信验证系统的挑战与方法OA

With the successful application of artificial intelligence and deep learning in the fields of computer vision,robotics,and medical treatment,wireless network intelligence is one of key technologies for the development of the next-generation wireless communication.This paper explores the key technical challenges and deployment options for constructing a verification system for endogenous intelligent communication in wireless networks.This works builds a versification system for endogenous intelligent communication that integrates wireless data collection and analysis,network state modeling and prediction,artificial intelligent model deployment and application,and dynamic monitoring and visualization of data by adopting advanced technologies such as network function virtualization,software-defined networking,containers and microservices,with Kubernetes as the foundation,signal processing timeline as the main pipeline,and pooling management of computing,network,data and wireless resources as the key method.This system has the abilities of real-time data collection and analysis,comprehensive understanding and monitoring of the wireless network state,and realizes the goals of testing and validation of endogenous intelligent communication technologies,such as flexible,agile and intelligent scheduling and management of data,calculus,resources in wireless communication network,as well as intelligent tuning of transmission strategies.