Machine Learning based Antenna Selection and Power Allocation in Multi-user MISO Systems

Reference : Machine Learning based Antenna Selection and Power Allocation in Multi-user MISO Systems


	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Electrical & electronics engineering
	To cite this reference:	http://hdl.handle.net/10993/41131

Title :	Machine Learning based Antenna Selection and Power Allocation in Multi-user MISO Systems
Language :	English
Author, co-author :	Vu, Thang Xuan [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Lei, Lei [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Chatzinotas, Symeon [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Ottersten, Björn [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Publication date :	Jun-2019
Main document title :	2019 IEEE International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)
Peer reviewed :	Yes
Event name :	2019 IEEE International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)
Event date :	06-19
Permalink :	http://hdl.handle.net/10993/41131
Framework Programme / European Project :	H2020 ; 742648 - AGNOSTIC - Actively Enhanced Cognition based Framework for Design of Complex Systems
FnR project :	FnR ; FNR11691338 > Bjorn Ottersten > ProCAST > Proactive Edge Caching for Content Delivery Networks powered by Hybrid Satellite/Terrestrial Backhauling > 01/07/2018 > 30/06/2021 > 2017; ROSETTA

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