Shared-Resource Generative Adversarial Network (GAN) Training for 5G URLLC Deep Reinforcement Learning Augmentation

Deep Reinforcement Learning (DRL) solutions to 5G problems often face with communication unreliability issues due to imbalanced state-space distributions and the scarcity of rare samples. Generative Adversarial Network (GAN) is promising to improve DRL reliability. However, employing GANs in resourc...

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Vydané v:	IEEE International Conference on Communications (2003) s. 2998 - 3003
Hlavní autori:	Mehdipourchari, Kaveh, Askarizadeh, Mohammad, Nguyen, Kim Khoa
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 09.06.2024
Predmet:	5G mobile communication 5G URLLC Computer architecture Deep Reinforcement Learning Generative Adversarial Network (GAN) Generative adversarial networks Optimization models Reliability Training Ultra reliable low latency communication Upper bound
ISSN:	1938-1883
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