SEQUOIA - Solução para Energia e QUalidade de serviço Otimizadas em Infraestruturas Abertas
Resumo
A rede de acesso rádio (RAN) é o componente que mais consome energia no sistema 5G. No geral, a economia de energia da RAN 5G depende da ativação/desativação de estação base ou componentes de rádio, utilizando soluções proprietárias. Além disso, as categorias de serviço do 5G, como URLCC e eMBB, possuem requisitos rigorosos de qualidade de serviço (QoS), o que exige mecanismos flexíveis para alcançar uma operação eficiente em termos de energia na RAN, mantendo níveis adequados de QoS para essas aplicações. Open RAN permite monitoramento em tempo real e adaptabilidade da rede por meio de interfaces abertas e controladores inteligentes da RAN. Assim, este artigo propõe o SEQUOIA, uma solução baseada em Open RAN e otimização multiobjetivo para garantir QoS e reduzir o consumo de energia.
Palavras-chave:
Open RAN, Rede 5G, Otimização, Energia, Qualidade de Serviço
Referências
3GPP (2017). Radio Access Architecture and Interfaces (Release 14). Technical Report TR 38.801 V2.0.0, 3rd Generation Partnership Project.
3GPP (2022). User equipment (ue) radio access capabilities (release 17). Technical Report TS 38.306, 3rd Generation Partnership Project.
Azariah, W., Bimo, F. A., Lin, C.-W., Cheng, R.-G., Nikaein, N., and Jana, R. (2024). A survey on open radio access networks: Challenges, research directions, and open source approaches. Sensors, 24(3).
Bordin, M., Lacava, A., Polese, M., Satish, S., Nittoor, M. A., Sivaraj, R., Cuomo, F., and Melodia, T. (2024). Design and evaluation of deep reinforcement learning for energy saving in open ran. arXiv preprint arXiv:2410.14021.
Chauhan, A., Bansal, K., and Chaturvedi, A. K. (2019). Weighted sum of spectral efficiency and energy efficiency in spatial modulation-mimo systems. In 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), pages 1–5.
Constantine, J. and Akhtar, H. (2024). Open ran progress report - ericsson. Major Milestones and What’s Next in the Transformation Journey, 2.
Demir, T., Masoudi, M., Björnson, E., and Cavdar, C. (2024). Cell-free massive mimo in o-ran: Energy-aware joint orchestration of cloud, fronthaul, and radio resources. IEEE Journal on Selected Areas in Communications, 42(2):356–372.
Gao, Y., Wang, L., Xie, Z., Qi, Z., and Zhou, J. (2023). Energy- and quality of experience-aware dynamic resource allocation for massively multiplayer online games in heterogeneous cloud computing systems. IEEE Transactions on Services Computing, 16(3):1793–1806.
Hoffmann, M. e. (2024). Energy efficiency in open ran: Rf channel reconfiguration use case. IEEE Access, 12:118493–118501.
Info, H. (2024). Understanding 32 QAM, 64 QAM, 128 QAM, and 256 QAM. Online resource. Accessed: 2024-12-27.
Kolta, E., Hatt, T., and Moore, S. (2021). Going green: Benchmarking the energy efficiency of mobile. Technical report, GSMA Intelligence.
Li, H., Emami, A., Assis, K. D. R., Vafeas, A., Yang, R., Nejabati, R., Yan, S., and Simeonidou, D. (2024). DRL-based energy-efficient baseband function deployments for service-oriented open ran. IEEE Transactions on Green Communications and Networking, 8(1):224–237.
Liang, X., Al-Tahmeesschi, A., Wang, Q., Chetty, S., Sun, C., and Ahmadi, H. (2024). Enhancing energy efficiency in o-ran through intelligent xApps deployment. arXiv preprint arXiv:2405.10116.
Mahmood, F. E., Perrins, E. S., and Liu, L. (2018). Energy consumption vs. bit rate analysis toward massive mimo systems. In 2018 IEEE International Smart Cities Conference (ISC2), pages 1–7.
Pereira de Figueiredo, F. A. (2022). An overview of massive mimo for 5g and 6g. IEEE Latin America Transactions, 20(6):931–940.
Perner, J. v. e. (2024). Beyond 5G white paper supplementary volume “sustainability and energy efficiency”. Project: Green Future Networks.
Thangamayan, S., Walunjkar, M. D., Kumar Ray, D., Venkatesan, M., Banik, A., and Amrutkar, K. P. (2022). 5G modulation technique comparisons using simulation approach. In 2022 3rd International Conference on Intelligent Engineering and Management (ICIEM), pages 848–856.
Urumkar, S., Ramamurthy, B., and Sharma, S. (2023). Improving energy efficiency in open ran through dynamic CPU scheduling. In 2023 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), pages 288–293.
3GPP (2022). User equipment (ue) radio access capabilities (release 17). Technical Report TS 38.306, 3rd Generation Partnership Project.
Azariah, W., Bimo, F. A., Lin, C.-W., Cheng, R.-G., Nikaein, N., and Jana, R. (2024). A survey on open radio access networks: Challenges, research directions, and open source approaches. Sensors, 24(3).
Bordin, M., Lacava, A., Polese, M., Satish, S., Nittoor, M. A., Sivaraj, R., Cuomo, F., and Melodia, T. (2024). Design and evaluation of deep reinforcement learning for energy saving in open ran. arXiv preprint arXiv:2410.14021.
Chauhan, A., Bansal, K., and Chaturvedi, A. K. (2019). Weighted sum of spectral efficiency and energy efficiency in spatial modulation-mimo systems. In 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), pages 1–5.
Constantine, J. and Akhtar, H. (2024). Open ran progress report - ericsson. Major Milestones and What’s Next in the Transformation Journey, 2.
Demir, T., Masoudi, M., Björnson, E., and Cavdar, C. (2024). Cell-free massive mimo in o-ran: Energy-aware joint orchestration of cloud, fronthaul, and radio resources. IEEE Journal on Selected Areas in Communications, 42(2):356–372.
Gao, Y., Wang, L., Xie, Z., Qi, Z., and Zhou, J. (2023). Energy- and quality of experience-aware dynamic resource allocation for massively multiplayer online games in heterogeneous cloud computing systems. IEEE Transactions on Services Computing, 16(3):1793–1806.
Hoffmann, M. e. (2024). Energy efficiency in open ran: Rf channel reconfiguration use case. IEEE Access, 12:118493–118501.
Info, H. (2024). Understanding 32 QAM, 64 QAM, 128 QAM, and 256 QAM. Online resource. Accessed: 2024-12-27.
Kolta, E., Hatt, T., and Moore, S. (2021). Going green: Benchmarking the energy efficiency of mobile. Technical report, GSMA Intelligence.
Li, H., Emami, A., Assis, K. D. R., Vafeas, A., Yang, R., Nejabati, R., Yan, S., and Simeonidou, D. (2024). DRL-based energy-efficient baseband function deployments for service-oriented open ran. IEEE Transactions on Green Communications and Networking, 8(1):224–237.
Liang, X., Al-Tahmeesschi, A., Wang, Q., Chetty, S., Sun, C., and Ahmadi, H. (2024). Enhancing energy efficiency in o-ran through intelligent xApps deployment. arXiv preprint arXiv:2405.10116.
Mahmood, F. E., Perrins, E. S., and Liu, L. (2018). Energy consumption vs. bit rate analysis toward massive mimo systems. In 2018 IEEE International Smart Cities Conference (ISC2), pages 1–7.
Pereira de Figueiredo, F. A. (2022). An overview of massive mimo for 5g and 6g. IEEE Latin America Transactions, 20(6):931–940.
Perner, J. v. e. (2024). Beyond 5G white paper supplementary volume “sustainability and energy efficiency”. Project: Green Future Networks.
Thangamayan, S., Walunjkar, M. D., Kumar Ray, D., Venkatesan, M., Banik, A., and Amrutkar, K. P. (2022). 5G modulation technique comparisons using simulation approach. In 2022 3rd International Conference on Intelligent Engineering and Management (ICIEM), pages 848–856.
Urumkar, S., Ramamurthy, B., and Sharma, S. (2023). Improving energy efficiency in open ran through dynamic CPU scheduling. In 2023 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), pages 288–293.
Publicado
19/05/2025
Como Citar
BARBOSA, Maria; PINHEIRO, Matheus; ALVES, Marcos; QUEIROZ, Anderson; DIAS, Kelvin.
SEQUOIA - Solução para Energia e QUalidade de serviço Otimizadas em Infraestruturas Abertas. In: SIMPÓSIO BRASILEIRO DE REDES DE COMPUTADORES E SISTEMAS DISTRIBUÍDOS (SBRC), 43. , 2025, Natal/RN.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 238-251.
ISSN 2177-9384.
DOI: https://doi.org/10.5753/sbrc.2025.5898.
