Energy-Saving Link Scheduling in Energy Harvesting Wireless Multihop Networks With the Non-Ideal Battery
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3014645
Abstract: Emerging energy harvesting technology can harvest and convert ambient energy into electrical power. It is a quite effective way to extend the lifetime of Wireless Multihop Networks (WMNs), and has been widely applied in WMNs.… read more here.
Keywords: wireless multihop; energy; link scheduling; battery ... See more keywords
Geometric Machine Learning Over Riemannian Manifolds for Wireless Link Scheduling
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3153324
Abstract: In this paper, we propose two novel geometric machine learning (G-ML) methods for the wireless link scheduling problem in device-to-device (D2D) networks. In dynamic D2D networks (e.g., vehicular networks), obtaining a large number of training… read more here.
Keywords: wireless link; training; machine; geometric machine ... See more keywords
Link Scheduling in Wireless Networks With RF Energy Harvesting Nodes
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Green Communications and Networking"
DOI: 10.1109/tgcn.2018.2883523
Abstract: In a wireless network, a scheduler ensures links are given frequent transmission opportunities. A short schedule means links transmit frequently and thus the resulting network capacity is high. In this paper, we consider a novel… read more here.
Keywords: energy requirement; link scheduling; schedule; energy ... See more keywords
Wireless Link Scheduling Over Recurrent Riemannian Manifolds
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Vehicular Technology"
DOI: 10.1109/tvt.2022.3228212
Abstract: Deep learning models for scheduling of potentially-interfering communication pairs, in device-to-device (D2D) settings, require large training samples in the order of hundreds to thousands. Some of the dynamic networks, such as vehicular networks, cannot tolerate… read more here.
Keywords: time; training samples; scheduling recurrent; link scheduling ... See more keywords