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Simulation of machine learning-based 6G systems in virtual worlds

Simulation of machine learning-based 6G systems in virtual worlds

Authors: Ailton Oliveira, Felipe Bastos, Isabela Trindade, Walter Frazao, Arthur Nascimento, Diego Gomes, Francisco Müller, Aldebaro Klautau
Status:
Date of publication: 27 August 2021
Published in: ITU Journal on Future and Evolving Technologies, Volume 2 (2021), Issue 4 - AI and machine learning solutions in 5G and future networks, Pages 113-123
Article DOI : https://doi.org/10.52953/SJAS4492
Abstract:
Digital representations of the real world are being used in many applications, such as augmented reality. 6G systems will not only support use cases that rely on virtual worlds but also benefit from their rich contextual information to improve performance and reduce communication overhead. This paper focuses on the simulation of 6G systems that rely on a 3D representation of the environment, as captured by cameras and other sensors. We present new strategies for obtaining paired MIMO channels and multimodal data. We also discuss trade-offs between speed and accuracy when generating channels via ray tracing. We finally provide beam selection simulation results to assess the proposed methodology.

Keywords: 6G, artificial intelligence, machine learning, MIMO, ray tracing
Rights: © International Telecommunication Union, available under the CC BY-NC-ND 3.0 IGO license.
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