近年来, 人工智能技术已被应用于无线通信领域, 以解决传统无线通信技术面对信息爆炸和万物
互联等新发展趋势所遇到的瓶颈问题. 首先介绍深度学习, 深度强化学习和联邦学习三类具有 …

Wireless communications are envisioned to bring about dramatic changes in the future, with
a variety of emerging applications, such as virtual reality, Internet of Things, and so on …

This book offers the latest advances and results in the fields of Machine Learning and Deep
Learning for Wireless Communication and provides positive and critical discussions on the …

对无线通信系统的高可靠性与超高容量需求促进了第五代移动通信(5G) 的发展, 然而,
随着通信系统的日益复杂, 现有的物理层无线通信技术难以满足这些高的性能需求. 目前 …

随着无线通信应用边界的不断扩展, 无线通信应用环境也日趋复杂多样, 面临射频损伤,
信道衰落, 干扰和噪声等负面影响, 给接收端恢复原始信息带来挑战. 借鉴深度学习方法在计算机 …

How can machine learning help the design of future communication networks-and how can
future networks meet the demands of emerging machine learning applications? Discover the …

Over the past decades, machine learning techniques have demonstrated excellent
superiorities in a wide range of fields, such as computer vision, natural language …

智能通信被认为是5G 之后无线通信发展的主流方向之一, 其基本思想是将人工智能引入无线
通信系统的各个层面, 实现无线通信与人工智能技术的有机融合. 目前, 该方面研究正在向物理层 …

Future wireless networks have a substantial potential in terms of supporting a broad range of
complex compelling applications both in military and civilian fields, where the users are able …

The rapid uptake of mobile devices and the rising popularity of mobile applications and
services pose unprecedented demands on mobile and wireless networking infrastructure …