Generative neural network based spectrum sharing using linear sum assignment problems

Spectrum management and resource allocation (RA) problems are challenging and critical in a vast number of research areas such as wireless communications and computer networks. The traditional approaches for solving such problems usually consume time and memory, especially for large-size problems. R...

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Vydané v:	China communications Ročník 17; číslo 2; s. 14 - 29
Hlavní autori:	Zaky, Ahmed B., Huang, Joshua Zhexue, Wu, Kaishun, ElHalawany, Basem M.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	China Institute of Communications 01.02.2020 Benha University,Benha,13511,Egypt Big Data Institute,Shenzhen University,518060,China Benha University,Benha,13511,Egypt%Big Data Institute,Shenzhen University,518060,China%Guangdong Laboratory of Artificial Intelligence and Digital Economy(SZ),Shenzhen University,Shenzhen 518060,China PCL Research Center of Networks and Communications,Peng Cheng Laboratory,Shenzhen 518060,China%Guangdong Laboratory of Artificial Intelligence and Digital Economy(SZ),Shenzhen University,Shenzhen 518060,China
Predmet:	autoencoder Computer architecture Device-to-device communication generative models linear sum assignment problems Machine learning Neural networks Optimization resource allocation Resource management Wireless communication generative models autoencoder resource allocation linear sum assignment problems
ISSN:	1673-5447
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