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 …

With the continues expansion of the application boundary for wireless communications, the
application environment of wireless communications is becoming increasingly complex and …

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 …

Deep learning is a promising solution to a number of complex problems based on its
inherent capability to approximate almost all types of functions without the demand for …

Machine learning (ML) has been widely applied to the upper layers of wireless
communication systems for various purposes, such as deployment of cognitive radio and …

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 …

The last decade has witnessed the rapid growth of deep learning (DL) applications in
wireless communications, especially for channel estimation and signal detection. However …

Deep learning algorithms have proven themselves powerful in different applications
because of their ability of generalization. In this paper, we introduce a deep learning …

目前深度学习在通信系统的上层中得到了广泛应用ꎬ 随着技术不断发展ꎬ 深度学习正在向通信
系统的底层推进ꎮ 为解决传统算法计算效率低, 复杂度高等问题ꎬ 深度学习已经被应用到无线 …