| Full text | |
| Author(s): |
Manjarres, Joanna C.
;
Cardoso, Douglas O.
;
Klautau, Aldebaro
;
de Rezende, Jose Ferreira
Total Authors: 4
|
| Document type: | Journal article |
| Source: | INFORMATION PROCESSING AND MANAGEMENT OF UNCERTAINTY IN KNOWLEDGE-BASED SYSTEMS, IPMU 2024, VOL 1; v. 1174, p. 14-pg., 2024-01-01. |
| Abstract | |
The integration of context information and machine learning techniques can enhance the capabilities of 5G/6G networks when dealing with the beam selection problem. This paper proposes the use of a Weightless Neural Network (WiSARD) with multimodal data as input to address this problem. The performance of the WiSARD is compared to classic machine learning algorithms (KNN, Decision Tree, SVC, Random Forest) based on the top-k accuracy in a vehicular network. The simulation results indicate that the WiSARD is a competitive method for this scenario and can be a valuable asset for future cellular networks. (AU) | |
| FAPESP's process: | 20/05127-2 - SAMURAI: smart 5G core and multiran integration |
| Grantee: | Aldebaro Barreto da Rocha Klautau Junior |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 20/05152-7 - PROFISSA: Programmable Future Internet for Secure Software Architectures |
| Grantee: | Lisandro Zambenedetti Granville |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 18/23097-3 - SFI2: slicing future internet infrastructures |
| Grantee: | Tereza Cristina Melo de Brito Carvalho |
| Support Opportunities: | Research Projects - Thematic Grants |