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