Artificial Intelligence and Quantum Computing for a Smarter Wireless Network
Year: 2020
Type: article
Abstract: It is widely accepted that networks are getting more complex and it needs smarter ways to deliver
an optimum capability of the network in reality. Millimeter wave will help to meet the demand as it will provide
the higher bandwidth that is needed for 5G. But these higher frequencies also come with challenges, such as low
signal penetration, that we need to counter to get optimum advantage. In this paper, we highlight the challenges
in high frequency wireless networks and put forward ideas involving recent development in telecommunications
and computing technology. In doing so, we critically evaluate the need for Artificial Intelligence (AI) and
Quantum computing (QC) within the network architecture to provide the required capability for beam, resource,
and interference management. The subsequent wireless networks need to be self-predictive and proactive to
handle futuristic applications like holographic communication, haptic feedback, or any latency dependent
application. Radio frequency itself is a dynamically changing component therefore rather than having fixed
rules, it is preferable to have a dynamically adaptable network. Today, the main challenge in the modern
wireless networks is to have a constant knowledge of the radio environment including multipath propagation of
MIMO channels especially, with the introduction of narrow beams in higher frequency, tracking of beams will
be a challenge.
Source: Journal of Critical Reviews
Authors: Rishiraj Sengupta, Dhritiraj Sengupta, Aashish Kumar Kamra, Digvijay Pandey
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W3042559594