Reinforcement Learning for Link Adaptation and Channel Selection in LEO Satellite Cognitive Communications

Reference : Reinforcement Learning for Link Adaptation and Channel Selection in LEO Satellite Cog...


	Document type :	Scientific journals : Article
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/54384

Title :	Reinforcement Learning for Link Adaptation and Channel Selection in LEO Satellite Cognitive Communications
Language :	English
Author, co-author :	Qureshi, Muhammad Anjum []
	Lagunas, Eva [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
	Kaddoum, Georges []
Publication date :	2023
Journal title :	IEEE Communications Letters
Publisher :	Institute of Electrical and Electronics Engineers
Peer reviewed :	Yes
ISSN :	1089-7798
City :	New York
Country :	United States - New York
Permalink :	http://hdl.handle.net/10993/54384
FnR project :	FnR ; FNR16193290 > Eva Lagunas > SmartSpace > Leveraging Artificial Intelligence To Empower The Next Generation Of Satellite Communications > 01/04/2022 > 31/03/2025 > 2021

File(s) associated to this reference

Fulltext file(s):

	File	Commentary	Version	Size	Access
Open access	IEEECommLetter_Qureshi_Final.pdf		Author preprint	1.09 MB	View/Open

All documents in ORBi^lu are protected by a user license.