| Full text | |
| Author(s): |
Brilhante, Davi da Silva
;
Manjarres, Joanna Carolina
;
Moreira, Rodrigo
;
Veiga, Lucas de Oliveira
;
de Rezende, Jose F.
;
Mueller, Francisco
;
Klautau, Aldebaro
;
Mendes, Luciano Leonel
;
de Figueiredo, Felipe A. P.
Total Authors: 9
|
| Document type: | Journal article |
| Source: | SENSORS; v. 23, n. 9, p. 61-pg., 2023-04-28. |
| Abstract | |
Modern wireless communication systems rely heavily on multiple antennas and their corresponding signal processing to achieve optimal performance. As 5G and 6G networks emerge, beamforming and beam management become increasingly complex due to factors such as user mobility, a higher number of antennas, and the adoption of elevated frequencies. Artificial intelligence, specifically machine learning, offers a valuable solution to mitigate this complexity and minimize the overhead associated with beam management and selection, all while maintaining system performance. Despite growing interest in AI-assisted beamforming, beam management, and selection, a comprehensive collection of datasets and benchmarks remains scarce. Furthermore, identifying the most-suitable algorithm for a given scenario remains an open question. This article aimed to provide an exhaustive survey of the subject, highlighting unresolved issues and potential directions for future developments. The discussion encompasses the architectural and signal processing aspects of contemporary beamforming, beam management, and selection. In addition, the article examines various communication challenges and their respective solutions, considering approaches such as centralized/decentralized, supervised/unsupervised, semi-supervised, active, federated, and reinforcement learning. (AU) | |
| FAPESP's process: | 18/23097-3 - SFI2: slicing future internet infrastructures |
| Grantee: | Tereza Cristina Melo de Brito Carvalho |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 21/06946-0 - Reconfigurable intelligent surface aided communications for 6G and beyond |
| Grantee: | Rausley Adriano Amaral de Souza |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 22/03457-0 - SAMURAI: smart 5G core and MUltiRAn integration |
| Grantee: | Masoud Khazaee |
| Support Opportunities: | Scholarships in Brazil - Technical Training Program - Technical Training |
| FAPESP's process: | 20/05152-7 - PROFISSA: Programmable Future Internet for Secure Software Architectures |
| Grantee: | Lisandro Zambenedetti Granville |
| Support Opportunities: | Research Projects - Thematic Grants |