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Optimized Load Balancing Mobile Network using a Generative Adversarial Network Based Network Simulator

Authors:
Tin-Yu Wu
Yueh Wu
Fu Jie Tey
Bo-Hong Huang

Keywords: 5G, GAN (Generative Adversarial Network), load balance, neural network

Abstract:
With the advances of neural networks and the 5th generation mobile networks (5G), how to use artificial intelligence (AI) in 5G wireless networks has become a widely discussed topic while neural network is one form of artificial intelligence. Due to the complexity of 5G networks, it would be difficult to achieve load balancing. For this reason, before the 5G networks are officially launched, this study would like to investigate the processing capacity and learning capacity of neural networks over complicated problems. We combine Generative Adversarial Network (GAN) with the network simulator ns-3 and use neural networks for load-balancing simulation parameter adjustment and load balancing optimization.

Pages: 27 to 30

Copyright: Copyright (c) IARIA, 2019

Publication date: November 24, 2019

Published in: conference

ISSN: 2326-9286

ISBN: 978-1-61208-758-0

Location: Valencia, Spain

Dates: from November 24, 2019 to November 28, 2019