| Grant number: | 20/05127-2 |
| Support Opportunities: | Research Projects - Thematic Grants |
| Start date: | January 01, 2022 |
| End date: | December 31, 2026 |
| Field of knowledge: | Physical Sciences and Mathematics - Computer Science - Computer Systems |
| Agreement: | MCTI/MC |
| Principal Investigator: | Aldebaro Barreto da Rocha Klautau Junior |
| Grantee: | Aldebaro Barreto da Rocha Klautau Junior |
| Host Institution: | Instituto de Tecnologia. Universidade Federal do Pará (UFPA). Ministério da Educação (Brasil). Belém , SP, Brazil |
| Pesquisadores principais: | Cristiano Bonato Both ; José Ferreira de Rezende ; Kleber Vieira Cardoso ; Luciano Leonel Mendes |
| Associated researchers: | Anderson Reis Rufino Marins ; Antonio Carlos de Oliveira Júnior ; Ciro José Almeida Macedo ; Cleverson Veloso Nahum ; Davi da Silva Brilhante ; Elton Vivot Dias ; Felipe Hauschild Grings ; Gabriel Matheus Faria de Almeida ; Gustavo Dias de Oliveira ; Gustavo Zanatta Bruno ; Hudson de Paula Romualdo ; Ilan Sousa Correa ; Joanna Carolina Manjarres Meneses ; Kleber Vieira Cardoso ; Leonardo Lira Ramalho ; Luan Assis Gonçalves ; Lucas Costa Shibata ; Lucio Rene Prade ; Mariana Baracat de Mello ; Pedro Henrique Carneiro de Souza ; Roberto Michio Marques Kagami ; Rogério Sousa e Silva ; Sand Luz Correa ; Thiago Guimarães Tavares ; Victor Hugo Lázaro Lopes |
| Associated scholarship(s): | 24/19556-3 - AI/ML for beam-selection in 5G networks,
BP.PD 24/16756-1 - Machine learning applied to the beam selection problem in mmwave networks, BP.PD 24/07088-5 - Monitoring, intelligent orchestration of wireless access networks and non-3GPP IoT slices, deployment, testing and use cases, BP.TT + associated scholarships - associated scholarships |
Abstract
5G networks will meet the different requirements of new services and applications, such as IoT, virtual/augmented reality, autonomous cars, and precision agrobusiness. To deal with this diversity, multiple modes of operation, provided by different wireless access technologies, have been defined. In addition, 5G networks are being developed under an intense softwarization process, characterized by the use of cloud, virtualization and programmability. This process is significant in access networks and even more notable in the 5G core. Given the many challenges, there are still several open issues, such as the integration of non-3GPP IoT access network technologies to a 5G core. The SAMURAI project thus proposes to research, deploy and extend 5G systems, developing the software needed to demonstrate the integration of wireless access technologies into the 5G core. Additionally, the project will address issues related to the adoption of Artificial Intelligence/Machine Learning (AI/ML) as a critical component in the evolution of 5G networks. Although standardization institutions are advancing in defining a framework, there are still several gaps for the full use of AI/ML in 5G. To overcome some of the most relevant gaps, the SAMURAI project will determine AI/ML algorithms and techniques suitable for problems in access and core networks, such as link adaptation to channel conditions, beam selection in millimeter waves and functionality positioning, in addition to advancing the state-of-the-art in data collection and use. Bringing together academic institutions and RNP, the project enables the assessment of AI/ML in a nationwide network, allowing the development of solutions that have predictable behavior and can be effectively adopted in production systems that leverage priority use cases in Brazil, such as online education enabled by long-distance networks. (AU)
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