activity
20182021
most citedThe optimal network throughputs when the model-aware node coexists with other nodes using different MAC protocols

1 citations · 2 across the 3 of their papers we have counts for

collaborators

5 papers

cs.SI20211 cited

Algorithms for Interference Minimization in Future Wireless Network Decomposition

Péter L. Erdős, 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…

cs.NI20201 cited

The optimal network throughputs when the model-aware node coexists with other nodes using different MAC protocols

Xiaowen Ye, Yiding Yu, Liqun Fu

In this document, we give the optimal network throughput when the DR-DLMA node (see our paper for definition) coexists with the nodes using other protocol (e.g., TDMA and/or ALOHA)…

cs.NI2020

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…

cs.NI2019

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…

cs.NI2018

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…