31 citations · 69 across the 28 of their papers we have counts for
7 papers · 1 filter
Deep Reinforcement Learning Aided Packet-Routing For Aeronautical Ad-Hoc Networks Formed by Passenger Planes
Dong Liu, Jingjing Cui, Jiankang Zhang +2
Data packet routing in aeronautical ad-hoc networks (AANETs) is challenging due to their high-dynamic topology. In this paper, we invoke deep reinforcement learning for routing in…
Deep Reinforcement Learning with Symmetric Prior for Predictive Power Allocation to Mobile Users
Jianyu Zhao, Chenyang Yang
Deep reinforcement learning has been applied for a variety of wireless tasks, which is however known with high training and inference complexity. In this paper, we resort to deep d…
Unsupervised Deep Learning for Ultra-reliable and Low-latency Communications
Chengjian Sun, Chenyang Yang
In this paper, we study how to solve resource allocation problems in ultra-reliable and low-latency communications by unsupervised deep learning, which often yield functional optim…
Caching at the Wireless Edge: Design Aspects, Challenges and Future Directions
Dong Liu, Binqiang Chen, Chenyang Yang +1
Caching at the wireless edge is a promising way of boosting spectral efficiency and reducing energy consumption of wireless systems. These improvements are rooted in the fact that…
Deep Reinforcement Learning for Resource Management in Network Slicing
Rongpeng Li, Zhifeng Zhao, Qi Sun +5
Network slicing is born as an emerging business to operators, by allowing them to sell the customized slices to various tenants at different prices. In order to provide better-perf…
A Learning-based Approach to Joint Content Caching and Recommendation at Base Stations
Dong Liu, Chenyang Yang
Recommendation system is able to shape user demands, which can be used for boosting caching gain. In this paper, we jointly optimize content caching and recommendation at base stat…