Dimensionamento ótimo de fronthaul óptico com divisão flexível de funções de processamento em CF-RAN
Resumo
A centralização do processamento das funções de banda base em um pool de nuvem emergiu como alternativa para redução de CAPEX e OPEX para as redes 5G. No entanto, esta centralização apresenta sérios desafios para a redes de acesso fronthaul em termos de largura de banda e de atraso. Para mitigar tais problemas, várias alternativas propostas mostraram-se promissoras, dentre elas a divisão funcional e o uso de arquiteturas híbridas. Neste trabalho, nós propomos uma solução ótima para decidir de forma flexível a divisão funcional considerando o estado da rede e a eficiência energética como decisão de projeto em uma arquitetura híbrida CF-RAN. O objetivo principal é fazer a escolha ideal da opção de divisão centralizando ao máximo as funções de processamento na nuvem.
Referências
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Pelekanou, A., Anastasopoulos, M., Tzanakaki, A., and Simeonidou, D. (2018). Provisioning of 5g services employing machine learning techniques. In International Conference on Optical Network Design and Modeling (ONDM), pages 200–205.
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Ranaweera, C., Wong, E., Nirmalathas, A., Jayasundara, C., and Lim, C. (2018). 5g c-ran with optical fronthaul: An analysis from a deployment perspective. Journal of Lightwave Technology, 36(11):2059–2068.
Riva, M., Donâncio, H., Almeida, F. R., Figueiredo, G. B., Tinini, R. I., Cesar Jr, R. M., and Batista, D. M. (2018). An elastic optical network-based architecture for the 5g fronthaul. In Anais do XXXVI Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos. SBC.
Tinini, R. I., Batista, D. M., Figueiredo, G. B., Tornatore, M., and Mukherjee, B. (2019). Energy-efficient baseband processing via vbbu migration in virtualized cloud-fog ran. In IEEE GLOBECOM.
Tinini, R. I., Batista, D. M., Figueiredo, G. B., Tornatore, M., and Mukherjee, B. (2019). Low-latency and energy-efficient bbu placement and vpon formation in virtualized cloud-fog ran. IEEE/OSA Journal of Optical Communications and Networking, 11(4):B37–B48.
Tinini, R. I., dos Santos, M. R. P., Figueiredo, G. B., and Batista, D. M. (2020). 5GPy: A SimPy-based simulator for performance evaluations in 5G hybrid Cloud-Fog RAN architectures. Simulation Modelling Practice and Theory, 101:102030.
Tohidi, M., Bakhshi, H., and Parsaeefard, S. (2020). Flexible function splitting and resource allocation in c-ran for delay critical applications. IEEE Access, 8:26150–26161.
Wang, X., Alabbasi, A., and Cavdar, C. (2017). Interplay of energy and bandwidth consumption in cran with optimal function split. In IEEE Intl. Conf. on Communications.
Wu, J., Zhang, Z., Hong, Y., and Wen, Y. (2015). Cloud radio access network (c-ran): a primer. IEEE Network, 29(1):35–41.
3GPP (2017b). Study on new radio access technology: Radio access architecture and interfaces. Technical report 38.801, 3rd Generation Partnership Project (3GPP). Version 14.0.0.
Alimi, I. A., Teixeira, A. L., and Monteiro, P. P. (2018). Toward an efficient c-ran optical fronthaul for the future networks: A tutorial on technologies, requirements, challenges, and solutions. IEEE Communications Surveys Tutorials, 20(1):708–769.
Consortium, G. et al. (2017). Study on new radio access technology: Radio access architecture and interfaces. Technical report, Technical Report TR-38.801 Release.
Figueiredo, G. B., Wang, X., Meixner, C. C., Tornatore, M., and Mukherjee, B. (2016). Load balancing and latency reduction in multi-user comp over twdm-vpons. In IEEE Intl. Conf. on Communications (ICC).
Gao, Z., Zhang, J., Yan, S., Xiao, Y., Simeonidou, D., and Ji, Y. (2019). Deep reinforcement learning for bbu placement and routing in c-ran. In Optical Fiber Communications.
Guizani, Z. and Hamdi, N. (2017). Cran, h-cran, and f-ran for 5g systems: Key capabilities and recent advances. International Journal of Network Management, 27(5):e1973. e1973 nem.1973.
Harutyunyan, D. and Riggio, R. (2018). Flex5g: Flexible functional split in 5g networks. IEEE Trans. on Network and Service Management, pages 961–975.
Konstantinou, D., Bressner, T. A., Rommel, S., Johannsen, U., Johansson, M. N., Ivashina, M. V., Smolders, A. B., and Tafur Monroy, I. (2020). 5g ran architecture based on analog radio-over-fiber fronthaul over udwdm-pon and phased array fed reector antennas. Optics Communications, 454:124464.
Larsen, L. M. P., Checko, A., and Christiansen, H. L. (2019). A survey of the functional IEEE Communications Surveys splits proposed for 5g mobile crosshaul networks. Tutorials, 21(1):146–172.
Marotta, A., Cassioli, D., Kondepu, K., Antonelli, C., and Valcarenghi, L. (2019). Exploiting exible functional split in converged software defined access networks. IEEE/OSA Journal of Optical Communications and Networking, 11(11):536–546.
Mei, H. and Peng, L. (2020). Flexible functional split for cost-efficient c-ran. Computer Communications, 161:368–374.
Moreira Zorello, L. M., Troia, S., Quagliotti, M., and Maier, G. (2020). Power-aware optimization of baseband-function placement in cloud radio access networks. In 2020 International Conference on Optical Network Design and Modeling (ONDM), pages 1–6.
Pelekanou, A., Anastasopoulos, M., Tzanakaki, A., and Simeonidou, D. (2018). Provisioning of 5g services employing machine learning techniques. In International Conference on Optical Network Design and Modeling (ONDM), pages 200–205.
Peng, C., Lee, S.-B., Lu, S., Luo, H., and Li, H. (2011). Traffic-driven power saving in operational 3g cellular networks. In Proceedings of the 17th annual international conference on Mobile computing and networking, pages 121–132.
Ranaweera, C., Wong, E., Nirmalathas, A., Jayasundara, C., and Lim, C. (2018). 5g c-ran with optical fronthaul: An analysis from a deployment perspective. Journal of Lightwave Technology, 36(11):2059–2068.
Riva, M., Donâncio, H., Almeida, F. R., Figueiredo, G. B., Tinini, R. I., Cesar Jr, R. M., and Batista, D. M. (2018). An elastic optical network-based architecture for the 5g fronthaul. In Anais do XXXVI Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos. SBC.
Tinini, R. I., Batista, D. M., Figueiredo, G. B., Tornatore, M., and Mukherjee, B. (2019). Energy-efficient baseband processing via vbbu migration in virtualized cloud-fog ran. In IEEE GLOBECOM.
Tinini, R. I., Batista, D. M., Figueiredo, G. B., Tornatore, M., and Mukherjee, B. (2019). Low-latency and energy-efficient bbu placement and vpon formation in virtualized cloud-fog ran. IEEE/OSA Journal of Optical Communications and Networking, 11(4):B37–B48.
Tinini, R. I., dos Santos, M. R. P., Figueiredo, G. B., and Batista, D. M. (2020). 5GPy: A SimPy-based simulator for performance evaluations in 5G hybrid Cloud-Fog RAN architectures. Simulation Modelling Practice and Theory, 101:102030.
Tohidi, M., Bakhshi, H., and Parsaeefard, S. (2020). Flexible function splitting and resource allocation in c-ran for delay critical applications. IEEE Access, 8:26150–26161.
Wang, X., Alabbasi, A., and Cavdar, C. (2017). Interplay of energy and bandwidth consumption in cran with optimal function split. In IEEE Intl. Conf. on Communications.
Wu, J., Zhang, Z., Hong, Y., and Wen, Y. (2015). Cloud radio access network (c-ran): a primer. IEEE Network, 29(1):35–41.
Publicado
16/08/2021
Como Citar
SANTOS, Matias R. P. dos; TININI, Rodrigo I.; JANUARIO, Tiago; FIGUEIREDO, Gustavo B..
Dimensionamento ótimo de fronthaul óptico com divisão flexível de funções de processamento em CF-RAN. In: SIMPÓSIO BRASILEIRO DE REDES DE COMPUTADORES E SISTEMAS DISTRIBUÍDOS (SBRC), 39. , 2021, Uberlândia.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 210-223.
ISSN 2177-9384.
DOI: https://doi.org/10.5753/sbrc.2021.16722.
