1 code implementation • 25 Mar 2020 • Yiding Yu, Soung Chang Liew, Taotao Wang
This paper aims to design a distributed deep reinforcement learning (DRL) based MAC protocol for a particular network, and the objective of this network is to achieve a global $\alpha$-fairness objective.
Networking and Internet Architecture
no code implementations • 16 Oct 2018 • Yiding Yu, Soung Chang Liew, Taotao Wang
In particular, in a heterogeneous environment with nodes adopting different MAC protocols (e. g., CS-DLMA, TDMA, and ALOHA), a CS-DLMA node can learn to maximize the sum throughput of all nodes.
Networking and Internet Architecture
1 code implementation • 1 Dec 2017 • Yiding Yu, Taotao Wang, Soung Chang Liew
In particular, the use of neural networks in DRL (as opposed to traditional reinforcement learning) allows for fast convergence to optimal solutions and robustness against perturbation in hyper-parameter settings, two essential properties for practical deployment of DLMA in real wireless networks.
Networking and Internet Architecture
