Algoritmo Genético Aplicado à Configuração Adaptativa da Potência de Transmissão de Antenas no 5G
Abstract
This work proposes an implementation called GA4PC (Genetic Algorithm for Power Configuration), based on the genetic algorithm, to minimize the total energy consumption of the Small Cells Base Station (BS) by switching off and decreasing the antennas transmission power. The results show that on a daily average GA4PC saved 26.43% of energy compared to LTE-A while maintaining the minimum required QoS.References
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Cisco, U. (2020). Cisco annual internet report (2018-2023) white paper. Cisco: San Jose, CA, USA.
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.
Guo, X., Niu, Z., Zhou, S., and Kumar, P. (2016). Delay-constrained energy-optimal base station sleeping control. IEEE Journal on Selected Areas in Communications, 34(5):1073-1085.
Kylasa, S. B., Kollias, G., and Grama, A. (2015). Social ties and checkin sites: connections and latent structures in location based social networks. pages 194-201.
Published
2022-11-16
How to Cite
SANTOS, Albert Einstein C. dos; CARDOSO, Diego L.; PAIXÃO, Ermínio Augusto R. da.
Algoritmo Genético Aplicado à Configuração Adaptativa da Potência de Transmissão de Antenas no 5G. In: REGIONAL SCHOOL OF HIGH PERFORMANCE NORTH 2 (ERAD-NO2) AND REGIONAL SCHOOL OF MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE NORTH 2 (ERAMIA-NO2), 2. , 2022, Belém/PA.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
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p. 5-8.
DOI: https://doi.org/10.5753/erad-no2.2022.228117.
