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20122022
most citedDeep Reinforcement Learning Aided Packet-Routing For Aeronautical Ad-Hoc Networks Formed by Passenger Planes

31 citations · 69 across the 23 of their papers we have counts for

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Showing cs.LGShow all

7 papers · 1 filter

cs.LG2020

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…

cs.LG2020

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…

cs.LG20201 cited

Constructing Deep Neural Networks with a Priori Knowledge of Wireless Tasks

Jia Guo, Chenyang Yang

Deep neural networks (DNNs) have been employed for designing wireless systems in many aspects, say transceiver design, resource optimization, and information prediction. Existing w…

cs.LG20202 cited

Optimizing Wireless Systems Using Unsupervised and Reinforced-Unsupervised Deep Learning

Dong Liu, Chengjian Sun, Chenyang Yang +1

Resource allocation and transceivers in wireless networks are usually designed by solving optimization problems subject to specific constraints, which can be formulated as variable…

cs.LG2019

Structure of Deep Neural Networks with a Priori Information in Wireless Tasks

Jia Guo, Chenyang Yang

Deep neural networks (DNNs) have been employed for designing wireless networks in many aspects, such as transceiver optimization, resource allocation, and information prediction. E…

cs.LG2019

Model-Free Unsupervised Learning for Optimization Problems with Constraints

Chengjian Sun, Dong Liu, Chenyang Yang

In many optimization problems in wireless communications, the expressions of objective function or constraints are hard or even impossible to derive, which makes the solutions diff…