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AI based Beam Management for 5G (mmWave) at Wireless Edge : Opportunities and Challenges

Authors:
Chitwan Arora

Keywords: mmWave; beam management; artifical intelligence; wireless edge

Abstract:
Fast and efficient beam management mechanism is the key enabler in 5G (millimeter wave) to achieve low latency and high data rate requirements. Recent advances in Artificial Intelligence (AI) have shown that Machine Learning (ML) and Deep Learning (DL) based techniques can play a significant role in efficient beam management. These techniques can continuously learn and adapt themselves based on the highly varying traffic and channel conditions. For effective operation, it is essential that the ML and DL based beam management algorithm should be deployed at the place in network where all the relevant input parameters needed for beam management are available continuously as well as the output of the beam management can be applied instantly. In this paper, advantages along with challenges of deploying ML and DL based beam management techniques at the wireless edge of 5G Network are explored.

Pages: 27 to 32

Copyright: Copyright (c) IARIA, 2019

Publication date: July 28, 2019

Published in: conference

ISSN: 2308-4030

ISBN: 978-1-61208-727-6

Location: Nice, France

Dates: from July 28, 2019 to August 2, 2019