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1 Ergebnisse
1
Deep Learning-Aided NOMA Codebook Design with Improved Perf..:
, In:
2023 XXXVth General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS)
,
Liu, Hsiang-Yu
;
Su, Hsuan-Jung
;
Takano, Yasuhiro
- p. 1-4 , 2023
Link:
https://doi.org/10.23919/URSIGASS57860.2023.10265593
RT T1 <cTitle>2023 XXXVth General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS)</cTitle>: T1 <Title>Deep Learning-Aided NOMA Codebook Design with Improved Performance</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10265593&Exemplar=1&LAN=DE A1 Liu, Hsiang-Yu A1 Su, Hsuan-Jung A1 Takano, Yasuhiro YR 2023 SN 2642-4339 K1 Training K1 Deep learning K1 NOMA K1 Codes K1 Spectral efficiency K1 Artificial neural networks K1 Decoding SP 1 OP 4 LK http://dx.doi.org/https://doi.org/10.23919/URSIGASS57860.2023.10265593 DO https://doi.org/10.23919/URSIGASS57860.2023.10265593 SF ELIB - SuUB Bremen
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