Publications (7)
Multi-Agent Deep Reinforcement Learning Multiple Access for Heterogeneous Wireless Networks with Imperfect Channels
Yiding Yu, Soung Chang Liew, Taotao Wang
This paper investigates a futuristic spectrum sharing paradigm for heterogeneous wireless networks with imperfect channels. In the heterogeneous networks, multiple wireless network…
Exploring the Focusing Mechanism of the NuMI Horn Magnets
Katsuya Yonehara, Sudeshna Ganguly, Don Athula Wickremasinghe +2
Neutrinos at the Main Injector (NuMI) is a project at Fermilab that provides an intense beam of neutrinos used by a number of experiments. NuMI creates a beam of pions that decay i…
Non-Uniform Time-Step Deep Q-Network for Carrier-Sense Multiple Access in Heterogeneous Wireless Networks
Yiding Yu, Soung Chang Liew, Taotao Wang
This paper investigates a new class of carrier-sense multiple access (CSMA) protocols that employ deep reinforcement learning (DRL) techniques, referred to as carrier-sense deep-re…
Carrier-Sense Multiple Access for Heterogeneous Wireless Networks Using Deep Reinforcement Learning
Yiding Yu, Soung Chang Liew, Taotao Wang
This paper investigates a new class of carrier-sense multiple access (CSMA) protocols that employ deep reinforcement learning (DRL) techniques for heterogeneous wireless networking…
Deep-Reinforcement Learning Multiple Access for Heterogeneous Wireless Networks
Yiding Yu, Taotao Wang, Soung Chang Liew
This paper investigates the use of deep reinforcement learning (DRL) in a MAC protocol for heterogeneous wireless networking referred to as Deep-reinforcement Learning Multiple Acc…
Algorithms for Interference Minimization in Future Wireless Network Decomposition
Péter L. ErdÅs, Tamás Róbert Mezei, Yiding Yu +3
We propose a simple and fast method for providing a high quality solution for the sum-interference minimization problem. As future networks are deployed in high density urban areas…