To process and transfer large amounts of data in emerging wireless services, it has become increasingly appealing to exploit distributed data communication and learning. Specifically, edge learning (EL) enables local model training on geographically disperse edge nodes and minimizes the need for frequent data exchange. However, the current design of separating EL deployment and communication optimization does not yet reap the promised benefits of distributed signal processing, and sometimes suffers from excessive signalling overhead, long processing delay, and unstable learning convergence. In this paper, we provide an overview on practical distributed EL techniques and their interplay with advanced communication optimization designs. In particular, typical performance metrics for dual-functional learning and communication networks are discussed. Also, recent achievements of enabling techniques for the dual-functional design are surveyed with exemplifications from the mutual perspectives of "communications for learning" and "learning for communications." The application of EL techniques within a variety of future communication systems are also envisioned for beyond 5G (B5G) wireless networks. For the application in goal-oriented semantic communication, we present a first mathematical model of the goal-oriented source entropy as an optimization problem. In addition, from the viewpoint of information theory, we identify fundamental open problems of characterizing rate regions for communication networks supporting distributed learning-and-computing tasks. We also present technical challenges as well as emerging application opportunities in this field, with the aim of inspiring future research and promoting widespread developments of EL in B5G.
翻译:为了处理和转让新兴无线服务的大量数据,人们越来越希望利用分布式数据通信和学习,具体而言,边缘学习(EL)使得在地理上分散边缘节点的地方示范培训能够进行地理分散的边缘节点,并尽量减少经常数据交换的需要;然而,目前设计将EL部署和通信优化分开的设计,尚未从分布式信号处理中获得预期的好处,有时还受到超额信号管理管理、长期处理延迟和学习趋同不稳定的影响。在本文件中,我们概述了实际分布式EL技术及其与先进通信优化设计的相互作用。我们特别讨论了双功能学习和通信网络典型的性能衡量标准。此外,从“学习通信”和“学习通信学习”等共同角度对两功能设计的最新赋能技术成果进行了示范性调查。 将EL技术技术应用于各种未来通信系统的范围也设想在5G(B5G)无线网络之外。 关于目标导向型语义通信的应用,我们提出了第一个面向目标源的数学模型,作为优化型通信网络的一个优化问题。此外,我们从当前理论学时代的角度,还确定了当前技术应用领域的基本应用机会。