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1 Ergebnisse
1
C-DRX parameters optimization using Multi-Agent Reinforceme..:
, In:
GLOBECOM 2023 - 2023 IEEE Global Communications Conference
,
Song, Juhwan
;
Nam, Yujin
;
Choi, Minsuk
... - p. 3355-3360 , 2023
Link:
https://doi.org/10.1109/GLOBECOM54140.2023.10437057
RT T1 <cTitle>GLOBECOM 2023 - 2023 IEEE Global Communications Conference</cTitle>: T1 <Title>C-DRX parameters optimization using Multi-Agent Reinforcement Learning with Self-attention</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10437057&Exemplar=1&LAN=DE A1 Song, Juhwan A1 Nam, Yujin A1 Choi, Minsuk A1 Jo, Yonghee A1 Lee, Seungyeon A1 Lee, Sanghyun A1 Kim, Nakyoung A1 Lee, Junghwan A1 Kim, Seungmo A1 Kim, Haksung A1 Jang, Seowoo YR 2023 SN 2576-6813 K1 Adaptation models K1 Energy consumption K1 Base stations K1 Scheduling algorithms K1 Heuristic algorithms K1 Traffic control K1 Optimization K1 Discontinuous reception K1 Artificial intelligence K1 Deep reinforcement learning K1 Multi-agent K1 Parameter optimization SP 3355 OP 3360 LK http://dx.doi.org/https://doi.org/10.1109/GLOBECOM54140.2023.10437057 DO https://doi.org/10.1109/GLOBECOM54140.2023.10437057 SF ELIB - SuUB Bremen
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