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Description
Description
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.
Project goals
The SAMURAI project aims to leverage the use of AI/ML techniques in different wireless access networks, as well as in the 5G core, which are found at different stages of development by the research groups in this project. The access networks considered are: millimeter wave networks, long-distance access networks and IoT access networks, as illustrated in Figure 1. When application requirements include high transmission rates, the use of millimeter wave bands is interesting, due to the large bandwidths. In this case, the use of intelligent beam steering, based on AI/ML techniques, is fundamental.
Figure 1. Access and core networks addressed in the SAMURAI project
In addition, the SAMURAI project aims to develop a scalable 5G core that allows the integration of 3GPP and non-3GPP technologies, and that facilitates the use of AI/ML techniques in the various layers. The project also aims at the development and evaluation of AI/ML techniques applied to the various components of the 5G network. The expected results will result in contributions to the field of mobile networks, ranging from the availability of a 5G core with AI/ML, to solutions for the integration and optimization of wireless access networks employing AI/ML techniques.
Development
Development
The 5G system is based on cloud computing concepts, whose core is service-oriented with native support for network resource slicing, virtualization and mobile edge computing [3GPP-TS-24.502]. Aspects of 5G architecture allow virtualized deployment of 5G networks which can be fully distributed, redundant and scalable. Furthermore, the various instances of network functions can be present individually or together with services and microservices, representing the fullness of this new generation of mobile networks.
As described by 3GPP Release 15, the main functions are: Session Management Function (SMF), Mobility Management Function (AMF), User Plan Function (UPF), Application Function (AF), Policies (PCF), Unified Data Management (UDM), Authentication Server Function (AUSF), Network Exposure Function (NEF), Network Function Repository (NRF), Network Slice Selection Function (NSSF) , Non-3GPP Interconnect Function (N3IWF) and Network Data Analysis Function (NWDAF).
These functions are critical to support the requirements of new 5G services, both in the context of the data and control planes. Thus, these functions will be used in the SAMURAI project to integrate the different access networks through the concept of network slicing, as can be seen in Figure 2.
Figure 2. 5G Core and SAMURAI Platform
In addition, one of the main objectives of the project is the implementation of the 5G core in RNP's software-defined infrastructure, called IDS@RNP. This infrastructure consists of a central cloud and a physically distributed edge cloud, both interconnected by an SDN network overlaid on the backbone, as well as by a tunneling service native to the equipment of this backbone. At the end of the implementation, it will be possible to interconnect the four access networks arranged in the RNP client institutions involved in this project (UFPA, UNISINOS, UFG and Inatel), as illustrated in Figure 3.
Figure 3. Integration of the SAMURAI project with IDS@RNP
Publications
Publications
Almeida, G.M., Pinto, L.D.L., Both, C.B. and Cardoso, K.V. Optimal joint functional split and network function placement in virtualized RAN with splittable flows. IEEE Wireless Communications Letters, 2022.
Grings, F.H., Silveira, L.B.D., Muller, N.J., Lúcio Prade, L., Cardoso, K.V., Correa, S.L. and Both, C.B. Orquestração dinâmica total de fatiamento de rede no núcleo 5G sobre plataforma nativa de computação em nuvem. 40º Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos, 2022.
Rodrigues, K.B.C., Bruno, G.Z., Cardoso, K.V., Corrêa, S.L. and Both, C. Uma Investigação Empírica sobre Observabilidade em Sistemas 5G Nativos de Nuvem. 40º Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos, 2022.
Correa, I., Oliveira, A., Du, B., Nahum, C., Kobuchi, D., Bastos, F., Ohzeki, H., Borges, J., Mehta, M., Batista, P. and Kondo, R. Simultaneous beam selection and users scheduling evaluation in a virtual world with reinforcement learning. ITU Journal on Future and Evolving Technologies, 2022.
Both, C.B., Borges, J., Gonçalves, L., Nahum, C., Macedo, C., Klautau, A. and Cardoso, K. System intelligence for UAV-based mission critical with challenging 5G/B5G connectivity. ITU Journal on Future and Evolving Technologies, 2021.
Grings, F., Dominato, L., Cardoso, K., Correa, S., Prade, L., Both, C.. Full dynamic orchestration in 5G core network slicing over a cloud-native platform. IEEE Global Communications Conference, 2022.
Lima, H., Bruno, G., Grings, F., Both, C., Alberti, A., Cardoso, K., Correa, S. Controle de Admissão para Network Slicing Ciente de Recursos de Rede e de Processamento. XL Simpósio Brasileiro de Telecomunicações e Processamento de Sinais, 2022.
Macedo, C., Vivot, E., Júnior, J., Bruno, G., Grings, F., Alberti, A., Both, C., Cardoso, K.. Improved support for UAV-based computer vision applications in Search and Rescue operations via RAN Intelligent Controllers. XL Simpósio Brasileiro de Telecomunicações e Processamento de Sinais, 2022.
Silveiras, L. B.D., Resende, H. C., Both, C., Marquez-Barja, J. B., Silvestre, B., Cardoso, K. V. Tutorial on communication between access networks and the 5G core. Computer Networks, 2022.
Aben-Athar, R.A., Nahum, C., Brilhante, D. da S., Rezende, J.F., Mendes, L.L., Klautau, A. User Scheduling and Beam-Selection with Tabular and Deep Reinforcement Learning. XL Simpósio Brasileiro de Telecomunicações e Processamento de Sinais, 2022.
De Souza, P.H., Mendes, L.L. Lattice Reduction Aided Probability Data Association Detector for MIMO Systems. IEEE Communications Letters, 2022.
Mello, M.B., Mendes, L.L. Low-Complexity Detection Algorithms Applied to FTN-GFDM Systems. IEEE Access, 2022.
De Souza, P.H., Mendes, L.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, 2022.
Pereira, L.A., Mendes, L.L., Bastos-Filho, C.J., Cerqueira, A. Machine Learning-based Linearization Schemes for Radio over Fiber Systems. IEEE Photonics Journal, 2022.
Souza, P.H.C., Mendes, L.L., Brilhante, D. da S., Rezende, J.F. Symbol Detection Performance and Complexity in Large-scale MIMO Systems. XL Simpósio Brasileiro de Telecomunicações e Processamento de Sinais, 2022.
Morais, F., B., Renner, J., Almeida, G. M., Contreras, L., Righi, R., Cardoso, K., Both, C. OPlaceRAN -- a Placement Orchestrator for Virtualized Next-Generation of Radio Access Network. IEEE Transactions on Network and Service Management, 2022.
Vilas Boas, E.C., Silva, J.D.S., de Figueiredo, F.A.P., Mendes, L. L., Souza, R. A. A. Artificial intelligence for channel estimation in multicarrier systems for B5G/6G communications: a survey. Journal of Wireless Communication Network, 2022.
Kagami R., Figueiredo, F. A. P., Lopes, V. H. L., Mendes, L. L. A Novel Technique for Link Adaptation Based on Inner Receiver Statistics. XL Simpósio Brasileiro de Telecomunicações e Processamento de Sinais, 2022.
Almeida, G., Lopes, V., Klautau, A., Cardoso, K. Deep reinforcement learning for joint functional split and network function placement in vRAN. IEEE Global Communications Conference, 2022.
Lopes, V., Almeida, G., Klautau, A., Cardoso, K. A Coverage-Aware VNF Placement and Resource Allocation Approach for Disaggregated vRANs. IEEE Global Communications Conference, 2022.
Fraga, L., Almeida, G., Correa, S., Both, C., Pinto, L., Cardoso, K. Efficient allocation of disaggregated RAN functions and Multi-access Edge Computing services. IEEE Global Communications Conference, 2022.
J. F. Santos, D. d. S. Brilhante, J. F. de Rezende, N. Marchetti, M. Ruffini, L. A. D. Silva, "Optimal Embedding of Heterogeneous RAN Slices for Secure and Technology-agnostic RANaaS," in IEEE Transactions on Network and Service Management, 2022.
Suzuki, D., Oliveira, A., Gonçalves, L., Correa, I., Klautau, A., Lins, S., Batista, P., Ray-Tracing MIMO Channel Dataset for Machine Learning Applied to V2V Communication, IEEE Latin-American Conference on Communications, 2022.
L. Augusto Melo Pereira, L. L. Mendes, C. J. A. Bastos Filho and A. Cerqueira Sodre. "Amplified radio-over-fiber system linearization using recurrent neural networks," in Journal of Optical Communications and Networking, vol. 15, no. 3, pp. 144-154, March 2023. https://ieeexplore.ieee.org/document/10046414
Pereira, L. A. M., Lima, E. S., Mendes, L. L., & Cerqueira S. Jr., A.. (2023). Machine Learning-Based Digital Pre-Distortion Scheme for RoF Systems and Experimental 5G mm-waves Fiber-Wireless Implementation. Journal of Microwaves, Optoelectronics and Electromagnetic Applications, 22(1), 172–183. https://doi.org/10.1590/2179-10742023v22i1270779
L. A. M. Pereira, L. L. Mendes, C. J. A. Bastos-Filho and A. Cerqueira Sodré, "Novel Machine Learning Linearization Scheme for 6G A-RoF Systems" in Journal of Lightwave Technology. https://ieeexplore.ieee.org/document/10216303
Gustavo Bruno, Karlla B. Chaves Rodrigues, Kleber Vieira Cardoso, Sand Luz Correa and Cristiano Bonato Both. Anomaly Detection in Cloud-native B5G Systems using Observability and Machine Learning COTS Solutions. Journal of Internet Services and Applications, 2023, 14:1. https://doi.org/10.5753/jisa.2023.3551
Gabriel M. Almeida, Gustavo Z. Bruno, Alexandre Huff, Matti Hiltunen, Elias P. Duarte, Cristiano B. Both and Kleber V. Cardoso, RIC-O: Efficient placement of a disaggregated and distributed RAN Intelligent Controller with dynamic clustering of radio nodes, in IEEE Journal on Selected Areas in Communications. https://ieeexplore.ieee.org/document/10329927
Cleverson V. Nahum, Victor Hugo Lopes, Ryan M. Dreifuerst, Pedro Batista, Ilan Correa, Kleber V. Cardoso, Aldebaro Klautau and Robert W. Heath Jr. Intent-aware Radio Resource Scheduling in a RAN Slicing Scenario using Reinforcement Learning. IEEE Transactions On Wireless Communication. https://doi.org/10.1109/TWC.2023.3297014
Brilhante, D.d.S.; Manjarres, J.C.; Moreira, R.; de Oliveira Veiga, L.; de Rezende, J.F.; Müller, F.; Klautau, A.; Leonel Mendes, L.; P. de Figueiredo, F.A. A Literature Survey on AI-Aided Beamforming and Beam Management for 5G and 6G Systems. Sensors 2023, 23, 4359. https://doi.org/10.3390/s23094359
F. David, J. F. de Rezende and V. C. Barbosa, "Exact Solution of the Full RMSA Problem in Elastic Optical Networks," in IEEE Networking Letters, https://doi.org/10.1109/LNET.2023.3337041
Gabriel F.C. de Queiroz, José F. de Rezende, Valmir C. Barbosa, A flexible algorithm to offload DAG applications for edge computing, Journal of Network and Computer Applications 2024, 222, 103791, https://doi.org/10.1016/j.jnca.2023.103791
Davi da Silva Brilhante, José F. de Rezende, Nicola Marchetti, Handover optimisation for high-capacity low-latency 5G NR mmWave communication, Ad Hoc Networks 2024, 153, 103328, https://doi.org/10.1016/j.adhoc.2023.103328
Luiz Augusto Pereira; Luciano Leonel Mendes; Arismar Cerqueira S. Jr.. Proposal of a Fiber/Wireless System Assisted by Machine Learning Towards 6G Communication. 20th SBMO/IEEE MTT-S International Microwave and Optoelectronics Conference (IMOC 2023), 2023. https://www.events.sbmo.org.br/imoc2023/pagina/30/technical-program
Pedro Henrique Carneiro Souza and Luciano Leonel. RIS-aided Systems under Faulty Configuration. IEEE Conference on Standards for Communications and Networking, 6–8 November, 2023. https://cscn2023.ieee-cscn.org/program/technical-papers
Lucas dos Santos Costa; Luciano Leonel Mendes; Pedro Henrique Carneiro Souza; Marja Matinmikko-Blue; Matti Latva-aho; Harri Saarnisaari. On Spectrum Access Approaches for Connectivity in Remote Areas in Brazil and Finland. IEEE Conference on Standards for Communications and Networking, 6–8 November, 2023. https://cscn2023.ieee-cscn.org/program/technical-papers
Gabriel M. Almeida; Celso Camilo-Junior; Sand Correa; Kleber Cardoso. A Genetic Algorithm for Efficiently Solving the Virtualized Radio Access Network Placement Problem. IEEE International Conference on Communications, 2023. https://ieeexplore.ieee.org/document/10279334.
Rogério S. Silva; William Pires; Sand L. Correa; Antonio Oliveira; Kleber V. Cardoso. Dynamic resources allocation in non-3GPP IoT networks involving UAVs. IEEE Conference on Vehicular Technology (VTC), Florence, Italy, 20-23/06/2023. https://doi.org/10.1109/VTC2023-Spring57618.2023.10199941
Gustavo Zanatta Bruno; Vikas Krishnan Radhakrishnan; Gabriel Almeida; Alexandre Huff; Aloizio Pereira da Silva; Kleber V Cardoso; Luiz da Silva; Cristiano Bonato Both. RIC-O: An Orchestrator for the Dynamic Placement of a Disaggregated RAN Intelligent Controller, IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops, Hoboken, NJ, USA, 2023, pp. 1-2, https://ieeexplore.ieee.org/document/10225753.
Pedro Henrique Carneiro Souza, Masoud Khazaee, Luciano Leonel Mendes. Continuous and Discrete Phase-shifts for RIS-aided Systems in Wideband Communication Channels. XLI Simpósio Brasileiro de Telecomunicações e Processamento de Sinais (SBrT2023), 08–11 de Outubro, 2023. http://dx.doi.org/10.14209/sbrt.2023.1570908239
João Henrique Delfino, Juliano Silveira Ferreira, Roberto Kagami, Luciano Leonel Mendes. Implementação e análise de técnica para estimação de SNR baseado em Deep Learning. XLI Simpósio Brasileiro de Telecomunicações e Processamento de Sinais (SBrT2023), 08–11 de Outubro, 2023. http://dx.doi.org/10.14209/sbrt.2023.1570913356
Rafael Veiga, Cristiano B. Both, Iago Medeiros, Denis Rosario, Eduardo Cerqueira. A Federated Learning Approach for Authentication and User Identification based on Behavioral Biometrics. XLI Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos (SBC 2023), 22-26 de maio, 2023. https://doi.org/10.5753/sbrc.2023.536
Lucas Costa, Rebecca Aben-Athar, Cleverson Nahum, Glauco Gonçalves, Ilan Correa e Aldebaro Klautau. Near-RT RIC and Emulated Basestation for Initial xApps Development. XLI Simpósio Brasileiro de Telecomunicações e Processamento de Sinais (SBrT2023), 08–11 de Outubro, 2023. DOI: 10.14209/sbrt.2023.1570923608
Lucas Matni, Rebecca Aben-Athar, Cleverson Nahum, Glauco Gonçalves, Ilan Correa, Silvia Lins e Aldebaro Klautau. Implementing Service Management and Orchestration for ORAN Software Community. XLI Simpósio Brasileiro de Telecomunicações e Processamento de Sinais (SBrT2023), 08–11 de Outubro, 2023. DOI: 10.14209/sbrt.2023.1570923577
Heitor Anglada, Cleverson Nahum, Glauco Gonçalves, Ilan Correa, Silvia Lins e Aldebaro Klautau. Automated Generation of RAN Scenarios for Experimentation. XIII Conferência Nacional em Comunicações, Redes e Segurança da Informação (ENCOM 2023), 27-29 de outubro, 2023. https://www.iecom.org.br/encom2023/programacao.html#detalhada
Eduardo Guedes Filho, Francisco Muller e Aldebaro Klautau. Integrated Teaching of DSP, Telecommunications and Machine Learning using Jupyter Notebooks. XIII Conferência Nacional em Comunicações, Redes e Segurança da Informação (ENCOM 2023), 27-29 de outubro, 2023. https://www.iecom.org.br/encom2023/programacao.html#detalhada
Frank Morte, Rebecca Aben-Athar, Cleverson Nahum, Glauco Gonçalves, Ilan Correa, Silvia Lins e Aldebaro Klautau. Performance Evaluation of the E2 Interface in O-RAN Setups. XIII Conferência Nacional em Comunicações, Redes e Segurança da Informação (ENCOM 2023), 27-29 de outubro,2023. https://www.iecom.org.br/encom2023/programacao.html#detalhada
De Souza, Pedro HC, Masoud Khazaee, and Luciano Mendes. "Resource-efficient configuration of RIS-aided communication systems under discrete phase-shifts and user mobility." IEEE Transactions on Communications (2024). doi: 10.1109/TCOMM.2024.3432690.
P. H. C. De Souza and L. Mendes, "Doppler Shift Compensation Assisted by RIS Systems in High-mobility Communications," in IEEE Communications Letters, doi: 10.1109/LCOMM.2024.3466562.
M. J. Abdel-Rahman, E. A. MAZIED, F. HASSAN, K. TEAGUE, A. B. MACKENZIE, S. F. MIDKIFF, K. V. CARDOSO, D. S. NIKOLOPOULOS, "On Robust Optimal Joint Deployment and Assignment of RAN Intelligent Controllers in O-RANs," in IEEE Open Journal of the Communications Society, vol. 5, pp. 2358-2376, 2024, doi: 10.1109/OJCOMS.2024.3383607.
Macedo, C. J. A., Dias, E. V., Both, C. B., & Cardoso, K. V. (2024). FramCo: Frame corrupted detection for the Open RAN intelligent controller to assist UAV-based mission-critical operations. Journal of Internet Services and Applications, 15(1), 125–138. doi: https://doi.org/10.5753/jisa.2024.4036
Cláudio Modesto, Rebecca Aben-Athar, Andrey Silva, Silvia Lins, Glauco Gonçalves, Aldebaro Klautau. “Delay estimation based on multiple stage message passing with attention mechanism using a real network communication dataset”. ITU Journal on Future and Evolving Technologies, Volume 5, Issue 4, December 2024, doi: http://dx.doi.org/10.52953/RBNE4256
J. Borges, F. Bastos, I. Correa, P. Batista and A. Klautau, "CAVIAR: Co-Simulation of 6G Communications, 3-D Scenarios, and AI for Digital Twins," in IEEE Internet of Things Journal, vol. 11, no. 19, pp. 31287-31300, 1 Oct.1, 2024, doi: 10.1109/JIOT.2024.3418675.
Bruno, G. Z., Almeida, G. M., Sathish, A., da Silva, A. P., Huff, L. A. D. A., Cardoso, K. V., & Both, C. B. (2024). Evaluating the Deployment of a Disaggregated Open RAN Controller On a Distributed Cloud Infrastructure. IEEE Transactions on Network and Service Management, doi: https://doi.org/10.1109/TNSM.2024.3386902.
Arnhold, F., Anbazhagan, S. S., Prade, L. R., Nogueira, J. M., Klautau, A., & Both, C. B. (2024). Network Slicing Support by Fronthaul Interface in Disaggregated Radio Access Networks: A Survey. IEEE Transactions on Network and Service Management, doi: https://doi.org/10.1109/TNSM.2024.3400019
Da Silva Brilhante, Davi; de Rezende, José F.; Marchetti, Nicola. Handover optimisation for high-capacity low-latency 5G NR mmWave communication. Ad Hoc Networks, v. 153, p. 103328, 2024. http://dx.doi.org/10.1016/j.adhoc.2023.103328
De Souza, Cláudio Diego T.; De Rezende, José F.; Campos, Carlos Alberto V.. Federated Learning assisted framework to periodically identify user communities in urban space. Ad Hoc Networks, v. 163, p. 103589, 2024. http://dx.doi.org/10.1016/j.adhoc.2024.103589
David, Fabio; de Rezende, José F.; Barbosa, Valmir C.. Exact Solution of the Full RMSA Problem in Elastic Optical Networks. IEEE Networking Letters, v. 6, p. 55-59, 2024. http://dx.doi.org/10.1109/lnet.2023.3337041
V. H. L. Lopes, G. M. Almeida, A. Klautau and K. V. Cardoso, "O-RAN-Oriented Approach for Dynamic VNF Placement Focused on Interference Mitigation", ICC 2024 - IEEE International Conference on Communications, Denver, CO, USA, 2024, pp. 5479-5484, doi: 10.1109/ICC51166.2024.10622781.
Douglas Santos, Gustavo Souza, Rodrigo Dutra, Amir H. Mohajerzadeh, Leonardo Ramalho, Aldebaro Klautau, Igor Almeida. "Machine Learning-Based Holdover for IEEE 1588 PTP Packet Fronthauling." 2024 19th International Symposium on Wireless Communication Systems (ISWCS). IEEE, 2024.
Manjarres, Joanna Carolina; Cardoso, D. O.; Klautau, Aldebaro; De Rezende, Jose Ferreira. WiSARD Network Approach for 5G MIMO Beam Selection. In: IPMU 2024, 2024, Lisboa. 20th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2024. p. 1-12.
Oliveira, A., Suzuki, D., Bastos, S., Correa, I., & Klautau, A. (2024, November). Machine Learning-Based mmWave MIMO Beam Tracking in V2I Scenarios: Algorithms and Datasets. In 2024 IEEE Latin-American Conference on Communications (LATINCOM) (pp. 1-5). IEEE.
H. Romualdo, L. Fraga, P. Conceição, F. Rocha, and K. Cardoso. "Otimização da associação entre estações base e equipamentos de usuário com auxílio de Aprendizado Federado para suporte a Realidade Aumentada Móvel", in Anais do XLII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos, Niterói/RJ, 2024, pp. 616-629, doi: https://doi.org/10.5753/sbrc.2024.1448.
Pires-Jr, W. T., da Silva, D. C., Silva, R. S., Pinto, L. D. L., Oliveira-Jr, A., Abdel-Rahman, M. J., & Cardoso, K. V. QoS-aware Optimal Deployment of LoRa Gateways in UAV-enabled LoRaWANs, in Anais do XLII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos, Niterói/RJ, 2024, pp. 574-587, doi: https://doi.org/10.5753/sbrc.2024.1443.
Silva, R. S., Oliveira, R. R., Carvalho, L. T., Freitas, L. A., Sebastião, X. P., Reis, C. B., Cardoso, K. V. Soluções baseadas em aprendizado por reforço profundo para implantar VANTs como gateways LoRaWAN com foco na Qualidade de Serviço IoT, in Anais do XLII Simpósio Brasileiro de Telecomunicações e Processamento de Sinais, Belém/PA, 2024. https://doi.org/10.14209/sbrt.2024.15710 36460
Almeida, G. M., Abdel-Rahman, M. J.; Cardoso, K. V. (2024). “Constraint-Aware Deep Reinforcement Learning for vRAN Dynamic Placement”, in Anais do XLII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos, Niterói/RJ, 2024, pp. 337-350. ISSN 2177-9384. DOI: https://doi.org/10.5753/sbrc.2024.1379.
Campos, D., et al. (2024). “Stepwise Optimal Inter-Slices Radio Resource Scheduling for Service-Level Agreement Assurance”, in Anais do XLII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos, Niterói/RJ, 2024, pp. 840-853. ISSN 2177-9384. DOI: https://doi.org/10.5753/sbrc.2024.1482.
Campos, D., de Almeida, G. M., Junior, W. T., Nahum, C. V., Klautau, A., Abdel-Rahman, M. J., & Cardoso, K. V. Stepwise Optimal Inter-Slices Radio Resource Scheduling for Service-Level Agreement Assurance, in Anais do XLII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos, Niterói/RJ, 2024, pp. 840-853. ISSN 2177-9384. DOI: https://doi.org/10.5753/sbrc.2024.1482.
Weskley Mauricio, Cleverson Nahum, Francisco Parente, Maykon Silva, Aldebaro Klautau. “Análise da Proteção de Serviços URLLC através de RL em Diferentes Cenários da Indústria 4.0”, in Anais do Encontro Anual do Iecom em Comunicações, Redes e Criptografia (Encom), Natal/RN, 2024.
Lucas Mozart, João Borges, Ilan Correa and Aldebaro Klautau. “Adjusting the Level of Detail in 3D Models for Wireless Channel Generation using Ray-Tracing” in Anais do XLII Simpósio Brasileiro de Telecomunicações e Processamento de Sinais, Belém/PA, 2024.
Cleverson Nahum, Weskley Mauricio, Maykon Silva, Francisco Parente e Aldebaro Klautau. “Proteção de Serviços URLLC para Indústria 4.0 utilizando Aprendizagem por Reforço Multi-Agente” in Anais do XLII Simpósio Brasileiro de Telecomunicações e Processamento de Sinais, Belém/PA, 2024.
Gabriel Kopper, Eduardo Schulz, Alexandre Huff, Cristiano Both. “Uma análise de interoperabilidade e desempenho de projetos Open RAN com núcleos de redes móveis de quinta geração”. in Anais do XLII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos, Niterói/RJ, 2024.
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Acknowledgement
Acknowledgement
Samurai Project has received funding from the Brazilian Ministry of Science, Technology and Innovation (MCTI) through FAPESP.
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