SAMURAI: smart 5G core and multiran integration

• 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). Belém , SP, Brazil
• City of the host institution: Belém
• Principal investigators: 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 ; Cláudio Matheus Modesto Barata ; Cleverson Veloso Nahum ; Daniel Campos da Silva ; Davi da Silva Brilhante ; Elton Vivot Dias ; Felipe Hauschild Grings ; Flavio Hernan Figueiredo Nunes ; Gabriel Matheus Faria de Almeida ; Gustavo Dias de Oliveira ; Gustavo Zanatta Bruno ; Hudson de Paula Romualdo ; Ilan Sousa Correa ; Joanna Carolina Manjarres Meneses ; João Paulo Tavares Borges ; Karlla Bianca Chaves Rodrigues ; Kleber Vieira Cardoso ; Leonardo Lira Ramalho ; Luan Assis Gonçalves ; Lucas Costa Shibata ; Lucas Mozart de Souza Carvalho ; Luciano de Souza Fraga ; Lucio Rene Prade ; Mariana Baracat de Mello ; Pedro Henrique Carneiro de Souza ; Pedro Henrique Costa de Sousa ; Rafael Rodrigues Silva ; REBECCA ALMEIDA ABEN ATHAR ; Roberto Michio Marques Kagami ; Rogério Sousa e Silva ; SAND LUZ CORREA ; Thiago Guimarães Tavares ; Victor Hugo Lázaro Lopes ; William Teixeira Pires Junior
• Associated scholarship(s): 25/08468-9 - Development of AI-based solutions for orchestration and monitoring of IoT networks integrated with the 5G core, BP.TT; 25/15794-0 - Modeling and solving the problem of intelligent orchestration of network slices with non-3GPP access, BP.IC; 25/03104-9 - Machine learning and artificial intelligence for SDR proof of concept for long distance networks, BP.TT; + associated scholarships 25/01614-0 - Requirements gathering, solution design, and integration between non-3GPP IoT wireless access networks and the 5G core, BP.TT; 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; 24/07617-8 - Integration, monitoring and intelligent orchestration of non-3GPP IoT wireless access networks with the 5G, BP.IC; 23/14714-7 - Integration of non-3GPP IoT wireless access network with 5G core, BP.TT; 23/09197-3 - IC-REQ-UNISINOS1 scholarship [UNISINOS], BP.IC; 22/14431-2 - XAI algorithms applied to long range 5G networks, BP.PD; 22/14965-7 - SAMURAI - Smart 5G Core And MUltiRAn Integration, BP.TT; 22/03457-0 - SAMURAI: smart 5G core and MUltiRAn integration, BP.TT - 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)

Scientific publications

(37)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

ALMEIDA, GABRIEL M.; PINTO, LEIZER DE L.; BOTH, CRISTIANO B.; CARDOSO, KLEBER, V. Optimal Joint Functional Split and Network Function Placement in Virtualized RAN With Splittable Flows. IEEE WIRELESS COMMUNICATIONS LETTERS, v. 11, n. 8, p. 5-pg., 2022-08-01. (20/05127-2)

ALMEIDA, GABRIEL MATHEUS; LOPES, VICTOR H.; KLAUTAU, ALDEBARO; CARDOSO, KLEBER V.; IEEE. Deep reinforcement learning for joint functional split and network function placement in vRAN. 2022 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2022), v. N/A, p. 6-pg., 2022-01-01. (20/05127-2)

SILVEIRA, LUCAS B. D.; DE RESENDE, HENRIQUE C.; BOTH, CRISTIANO B.; MARQUEZ-BARJA, JOHANN M.; SILVESTRE, BRUNO; CARDOSO, KLEBER, V. Tutorial on communication between access networks and the 5G core. Computer Networks, v. 216, p. 15-pg., 2022-10-24. (20/05182-3, 18/23097-3, 20/05127-2)

MACEDO, CIRO J. A.; DIAS, ELTON V.; BOTH, CRISTIANO BONATO; CARDOSO, KLEBER VIEIRA. FramCo: Frame corrupted detection for the Open RAN intelligent controller to assist UAV-based mission-critical operations. JOURNAL OF INTERNET SERVICES AND APPLICATIONS, v. 15, n. 1, p. 14-pg., 2024-01-01. (20/05127-2)

GASPAR, DANILO; MENDES, LUCIANO L.; PIMENTA, TALES C.. A review on principles, performance and complexity of linear estimation and detection techniques for MIMO systems. FRONTIERS IN COMMUNICATIONS AND NETWORKS, v. 4, p. 21-pg., 2023-02-28. (20/05127-2)

PEREIRA, LUIZ AUGUSTO MELO; MENDES, LUCIANO LEONEL; BASTOS FILHO, CARMELO JOSE ALBANEZ; SODRE JR, ARISMAR CERQUEIRA. Amplified radio-over-fiber system linearization using recurrent neural networks. JOURNAL OF OPTICAL COMMUNICATIONS AND NETWORKING, v. 15, n. 3, p. 11-pg., 2023-03-01. (20/05127-2)

LUIZ A. M. PEREIRA; EDUARDO S. LIMA; LUCIANO L. MENDES; ARISMAR CERQUEIRA S. JR.. Machine Learning-Based Digital Pre-Distortion Scheme for RoF Systems and Experimental 5G mm-waves Fiber-Wireless Implementation. J. Microw. Optoelectron. Electromagn. Appl., v. 22, n. 1, p. 172-183, 2023-03-13. (20/05127-2)

CUNHA, KAIQUE M. R.; CORREA, SAND; SOARES, FABRIZZIO; RIBEIRO, MARIA; MOREIRA, WALDIR; GOMES, RAPHAEL; FREITAS, LEANDRO A.; OLIVEIRA-JR, ANTONIO. A Novel Radio Network Information Service (RNIS) to MEC Framework in B5G Networks. INFORMATION, v. 15, n. 6, p. 24-pg., 2024-06-01. (20/05127-2)

BRUNO, GUSTAVO ZANATTA; DE ALMEIDA, GABRIEL MATHEUS F.; SATHISH, ADITYA; DASILVA, ALOIZIO PEREIRA; DASILVA, LUIZ A.; HUFF, ALEXANDRE; CARDOSO, KLEBER VIEIRA; BOTH, CRISTIANO BONATO. Evaluating the Deployment of a Disaggregated Open RAN Controller on a Distributed Cloud Infrastructure. IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT, v. 21, n. 4, p. 13-pg., 2024-08-01. (20/05127-2, 20/05182-3)

BORGES, JOAO; BASTOS, FELIPE; CORREA, ILAN; BATISTA, PEDRO; KLAUTAU, ALDEBARO. CAVIAR: Co-Simulation of 6G Communications, 3-D Scenarios, and AI for Digital Twins. IEEE INTERNET OF THINGS JOURNAL, v. 11, n. 19, p. 14-pg., 2024-10-01. (20/05127-2)

DE SOUZA, PEDRO H. C.; KHAZAEE, MASOUD; MENDES, LUCIANO LEONEL. Resource-Efficient Configuration of RIS-Aided Communication Systems Under Discrete Phase-Shifts and User Mobility. IEEE TRANSACTIONS ON COMMUNICATIONS, v. 73, n. 1, p. 13-pg., 2025-01-01. (20/05127-2)

LOPES, VICTOR H. L.; ALMEIDA, GABRIEL M.; KLAUTAU, ALDEBARO; CARDOSO, KLEBER V.. O-RAN-oriented approach for dynamic VNF placement focused on interference mitigation. ICC 2024 - IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS, v. N/A, p. 6-pg., 2024-01-01. (20/05127-2)

DE QUEIROZ, GABRIEL F. C.; DE REZENDE, JOSE F.; BARBOSA, VALMIR C.. A flexible algorithm to offload DAG applications for edge computing. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, v. 222, p. 13-pg., 2023-11-23. (21/08211-7, 18/23097-3, 20/05127-2)

DE SOUZA, PEDRO H. C.; MENDES, LUCIANO. Doppler Shift Compensation Assisted by RIS Systems in High-Mobility Communications. IEEE COMMUNICATIONS LETTERS, v. 28, n. 11, p. 5-pg., 2024-11-01. (20/05127-2)

BOAS, EVANDRO C. VILAS C.; S. E SILVA, JEFFERSON D. S.; DE FIGUEIREDO, FELIPE A. P.; MENDES, LUCIANO L. L.; DE SOUZA, RAUSLEY A. A.. Artificial intelligence for channel estimation in multicarrier systems for B5G/6G communications: a survey. EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING, v. 2022, n. 1, p. 63-pg., 2022-12-02. (21/06946-0, 20/05127-2)

GUEDES, RAPHAEL M.; DE REZENDE, JOSE F.; BARBOSA, VALMIR C.. Near-Optimal Pilot Assignment in Cell-Free Massive MIMO. INTERNET TECHNOLOGY LETTERS, v. N/A, p. 6-pg., 2025-01-06. (20/05127-2, 18/23097-3, 21/08211-7)

FRAGA, LUCIANO DE S.; ALMEIDA, GABRIEL MATHEUS; CORREA, SAND; BOTH, CRISTIANO; PINTO, LEIZER; CARDOSO, KLEBER; IEEE. Efficient allocation of disaggregated RAN functions and Multi-access Edge Computing services. 2022 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2022), v. N/A, p. 6-pg., 2022-01-01. (20/05127-2)

LOPES, VICTOR HUGO L.; ALMEIDA, GABRIEL MATHEUS; KLAUTAU, ALDEBARO; CARDOSO, KLEBER; IEEE. A Coverage-Aware VNF Placement and Resource Allocation Approach for Disaggregated vRANs. 2022 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2022), v. N/A, p. 6-pg., 2022-01-01. (20/05127-2)

PIRES-JR, WILLIAM T.; ALMEIDA, GABRIEL M.; CORREA, SAND L.; BOTH, CRISTIANO B.; PINTO, LEIZER L.; CARDOSO, KLEBER V.. Optimizing Energy Consumption for vRAN Placement in O-RAN Systems With Flexible Transport Networks. IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY, v. 6, p. 16-pg., 2025-01-01. (20/05127-2, 18/23097-3)

PEREIRA, L. A. M.; MENDES, L. L.; COX, MITCHELL A.; CERQUEIRA JR, S. ARISMAR. Open dataset initiative for machine learning-based linearization in analog radio over fiber systems. Optics Communications, v. 590, p. 8-pg., 2025-10-01. (20/05127-2, 22/09319-9, 21/06569-1)

MANJARRES, JOANNA C.; CARDOSO, DOUGLAS O.; KLAUTAU, ALDEBARO; DE REZENDE, JOSE FERREIRA. A WiSARD Network Approach for 5G MIMO Beam Selection. INFORMATION PROCESSING AND MANAGEMENT OF UNCERTAINTY IN KNOWLEDGE-BASED SYSTEMS, IPMU 2024, VOL 1, v. 1174, p. 14-pg., 2024-01-01. (20/05127-2, 20/05152-7, 18/23097-3)

OLIVEIRA, AILTON; SUZUKI, DANIEL; BASTOS, SAVIO; CORREA, ILAN; KLAUTAU, ALDEBARO. Machine Learning-Based mmWave MIMO Beam Tracking in V2I Scenarios: Algorithms and Datasets. 2024 IEEE LATIN-AMERICAN CONFERENCE ON COMMUNICATIONS, LATINCOM, v. N/A, p. 5-pg., 2024-01-01. (20/05127-2)

COSTA, LUCAS DOS SANTOS; MENDES, LUCIANO LEONEL; CARNEIRO DE SOUZA, PEDRO HENRIQUE; MATINMIKKO-BLUE, MARJA; LATVA-AHO, MATTI; SAARNISAARI, HARRI. On Spectrum Access Approaches for Connectivity in Remote Areas in Brazil and Finland. 2023 IEEE CONFERENCE ON STANDARDS FOR COMMUNICATIONS AND NETWORKING, CSCN, v. N/A, p. 6-pg., 2023-01-01. (20/05127-2)

ARNHOLD, FELIPE; ANBAZHAGAN, SIVASANKARI S.; PRADE, LUCIO R.; NOGUEIRA, JOSE MARCOS; KLAUTAU, ALDEBARO; BOTH, CRISTIANO BONATO. Network Slicing Support by Fronthaul Interface in Disaggregated Radio Access Networks: A Survey. IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT, v. 21, n. 4, p. 21-pg., 2024-08-01. (20/05127-2, 20/05182-3)

SILVA, ROGERIO S.; PIRES JUNIOR, WILLIAM; CORREA, SAND L.; OLIVEIRA-, ANTONIO, JR.; CARDOSO, KLEBER V.. Dynamic resources allocation in non-3GPP IoT networks involving UAVs. 2023 IEEE 97TH VEHICULAR TECHNOLOGY CONFERENCE, VTC2023-SPRING, v. N/A, p. 5-pg., 2023-01-01. (20/05127-2)

MODESTO, CLAUDIO; MOZART, LUCAS; BATISTA, PEDRO; CAVALCANTE, ANDRE; KLAUTAU, ALDEBARO. Accelerating Ray Tracing-Based Wireless Channels Generation for Real-Time Network Digital Twins. IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY, v. 6, p. 15-pg., 2025-01-01. (20/05127-2)

MORAIS, FERNANDO ZANFERRARI; ALMEIDA, GABRIEL MATHEUS; PINTO, LEIZER; CARDOSO, KLEBER VIEIRA; CONTRERAS, LUIS M.; RIGHI, RODRIGO DA ROSA; BOTH, CRISTIANO BONATO. PlaceRAN: Optimal Placement of Virtualized Network Functions in Beyond 5G Radio Access Networks. IEEE TRANSACTIONS ON MOBILE COMPUTING, v. 22, n. 9, p. 15-pg., 2023-09-01. (20/05127-2)

DAVID, FABIO; REZENDE, JOSE F. DE; BARBOSA, VALMIR C.. Exact Solution of the Full RMSA Problem in Elastic Optical Networks. IEEE NETWORKING LETTERS, v. 6, n. 1, p. 5-pg., 2024-03-01. (21/08211-7, 18/23097-3, 20/05127-2)

MORAIS, FERNANDO ZANFERRARI; BRUNO, GUSTAVO ZANATTA; RENNER, JULIO; DE ALMEIDA, GABRIEL MATHEUS F.; CONTRERAS, LUIS M.; RIGHI, RODRIGO DA ROSA; CARDOSO, KLEBER VIEIRA; BONATO BOTH, CRISTIANO BONATO. OPlaceRAN-A Placement Orchestrator for Virtualized Next-Generation of Radio Access Network. IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT, v. 20, n. 3, p. 15-pg., 2023-09-01. (20/05127-2, 20/05182-3)

ALMEIDA, GABRIEL M.; CAMILO-JUNIOR, CELSO; CORREA, SAND; CARDOSO, KLEBER. A genetic algorithm for efficiently solving the virtualized radio access network placement problem. ICC 2023-IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS, v. N/A, p. 6-pg., 2023-01-01. (20/05127-2)

XAVIER, RUBEN; SILVA, ROGERIO S.; RIBEIRO, MARIA; MOREIRA, WALDIR; FREITAS, LEANDRO; OLIVEIRA, ANTONIO. Integrating Multi-Access Edge Computing (MEC) into Open 5G Core. TELECOM, v. 5, n. 2, p. 18-pg., 2024-06-01. (20/05127-2)

DE SOUZA, PEDRO H. C.; MENDES, LUCIANO L.. RIS-aided Systems under Faulty Configuration. 2023 IEEE CONFERENCE ON STANDARDS FOR COMMUNICATIONS AND NETWORKING, CSCN, v. N/A, p. 4-pg., 2023-01-01. (20/05127-2)

MELO PEREIRA, LUIZ AUGUSTO; MENDES, LUCIANO LEONEL; CERQUEIRA, ARISMAR S., JR.. Proposal of a Fiber/Wireless System Assisted by Machine Learning Towards 6G Communications. 2023 SBMO/IEEE MTT-S INTERNATIONAL MICROWAVE AND OPTOELECTRONICS CONFERENCE, IMOC, v. N/A, p. 3-pg., 2023-01-01. (20/05127-2)

DE SOUZA, PEDRO H. C.; MENDES, LUCIANO L.. Low-complexity deep unfolded neural network receiver for MIMO systems based on the probability data association detector. EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING, v. 2022, n. 1, p. 19-pg., 2022-08-09. (20/05127-2)

PEREIRA, LUIZ A. M.; MENDES, LUCIANO L.; BASTOS-FILHO, CARMELO J. A.; CERQUEIRA S, ARISMAR. Machine Learning-Based Linearization Schemes for Radio Over Fiber Systems. IEEE Photonics Journal, v. 14, n. 6, p. 10-pg., 2022-12-01. (20/05127-2)

DE SOUZA, PEDRO H. C.; MENDES, LUCIANO L.. Lattice Reduction Aided Probability Data Association Detector for MIMO Systems. IEEE COMMUNICATIONS LETTERS, v. 26, n. 10, p. 5-pg., 2022-10-01. (20/05127-2)

MELLO, MARIANA B.; MENDES, LUCIANO L.. Low-Complexity Detection Algorithms Applied to FTN-GFDM Systems. IEEE ACCESS, v. 10, p. 14-pg., 2022-01-01. (20/05127-2)