面向智能服务的雾无线接入网络:原理、技术与挑战

Intelligent service oriented fog radio access network:principles,technologies and challenges

大数据和人工智能的兴起推动了智能服务的蓬勃发展。然而由于数据管理和模型训练成本高昂,以及用户对时延和隐私等的需求愈加突出,基于现有的集中式网络架构难以实现整体网络的智能化。为此,提出了一种支持分布式机器学习的基于人工智能的雾无线接入网络(AI-FRAN)架构,并探讨了支撑该架构的基础理论,明确了充分利用雾无线接入网络(F-RAN)中通信资源、计算资源以及缓存资源的关键赋能技术。最后,讨论了AI-FRAN未来的发展机遇与挑战。

Big data and artificial intelligence has promoted the development of intelligent service.However,due to the high cost of data management and model training,as well as the increasing demands of users for latency and privacy,it is difficult to achieve the intelligent network based on the existing centralized network architecture.To address this issue,an artificial intelligence-based fog radio access network(AI-FRAN)architecture that supported distributed machine learning was proposed,and the fundamental principles that support the architecture were discussed.The key enabling techniques were identified that can realize the full utilization of communication resources,computing resources and cache resources in fog radio access network(F-RAN).Finally,the opportunities and challenges of AI-FRAN were discussed.