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 …

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 …

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 …

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 …

In recent years, artificial intelligence technology has been widely used in the field of wireless
communication to solve the bottleneck problems encountered by traditional wireless …

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 …

目前深度学习方法在物理层通信中得到了广泛的应用, 信道估计是物理层通信中的关键部分,
与传统信道估计算法相比, 深度学习方法在信道估计方面具有一定的优势 …

Deep learning has become the most successful learning method in machine learning. While
deep learning provides a clear advantage over other machine learning methods, especially …

With the rapid development of the communication industry in the fifth generation and the
advance towards the intelligent society of the sixth generation wireless networks, traditional …