31 citations · 69 across the 29 of their papers we have counts for
8 papers · 1 filter
Multicell Power Control under Rate Constraints with Deep Learning
Yinghan Li, Shengqian Han, Chenyang Yang
In the paper we study a deep learning based method to solve the multicell power control problem for sum rate maximization subject to per-user rate constraints and per-base station…
Learning Power Control for Cellular Systems with Heterogeneous Graph Neural Network
Jia Guo, Chenyang Yang
Optimizing power control in multi-cell cellular networks with deep learning enables such a non-convex problem to be implemented in real-time. When channels are time-varying, the de…
A Tutorial on Ultra-Reliable and Low-Latency Communications in 6G: Integrating Domain Knowledge into Deep Learning
Changyang She, Chengjian Sun, Zhouyou Gu +4
As one of the key communication scenarios in the 5th and also the 6th generation (6G) of mobile communication networks, ultra-reliable and low-latency communications (URLLC) will b…
Unsupervised Deep Learning for Optimizing Wireless Systems with Instantaneous and Statistic Constraints
Chengjian Sun, Changyang She, Chenyang Yang
Deep neural networks (DNNs) have been introduced for designing wireless policies by approximating the mappings from environmental parameters to solutions of optimization problems.…
Accelerating Deep Reinforcement Learning With the Aid of Partial Model: Energy-Efficient Predictive Video Streaming
Dong Liu, Jianyu Zhao, Chenyang Yang +1
Predictive power allocation is conceived for energy-efficient video streaming over mobile networks using deep reinforcement learning. The goal is to minimize the accumulated energy…
Deep Learning for Ultra-Reliable and Low-Latency Communications in 6G Networks
Changyang She, Rui Dong, Zhouyou Gu +6
In the future 6th generation networks, ultra-reliable and low-latency communications (URLLC) will lay the foundation for emerging mission-critical applications that have stringent…