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A Deep Reinforcement Learning Based Approach for Intelligen..:

, In: 2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech),

Zan, Shiming ; Pang, Yu ; Gravina, Raffaele... - p. 1-7 , 2022

Link: https://doi.org/10.1109/DASC/PiCom/CBDCom/Cy55231.2022..

RT 
T1 <cTitle>2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)</cTitle>: T1 <Title>A Deep Reinforcement Learning Based Approach for Intelligent Reconfigurable Surface Elements Selection</Title>

UL https://suche.suub.uni-bremen.de/peid=ieee-9927779&Exemplar=1&LAN=DE
				
A1 Zan, Shiming
A1 Pang, Yu
A1 Gravina, Raffaele
A1 Cao, Enling
A1 Li, Ye
A1 Zang, Weilin
YR 2022
K1 Training
K1 Neural networks
K1 Reinforcement learning
K1 MISO communication
K1 Network architecture
K1 Energy efficiency
K1 Energy harvesting
K1 intelligent reconfigurable surface
K1 activation IRS reflecting elements selection
K1 deep reinforcement learning
K1 phase shift design
SP 1
OP 7
LK http://dx.doi.org/https://doi.org/10.1109/DASC/PiCom/CBDCom/Cy55231.2022.9927779
DO https://doi.org/10.1109/DASC/PiCom/CBDCom/Cy55231.2022.9927779
SF ELIB - SuUB Bremen

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