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

• Autor(a) principal: OLIVEIRA, Ailton Pinto de
• Data de Publicação: 2021
• Outros Autores: NASCIMENTO, Arthur Matheus do, COSTA, Walter Tadeu Neves Frazão da, TRINDADE, Isabela Pamplona, BASTOS, Felipe Henrique Bastos e, GOMES, Diego de Azevedo, MÜLLER, Francisco Carlos Bentes Frey, KLAUTAU JÚNIOR, Aldebaro Barreto da Rocha
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UFPA
• Texto Completo: http://repositorio.ufpa.br:8080/jspui/handle/2011/14867
• topic: 6G; Artificial intelligence; Machine learning; MIMO; Ray tracing

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.