2026-06-05T13:55:34Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/344402026-02-03T11:35:42Zcom_10630_2254col_10630_37953
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
Khatib, Emil Jatib
author
Barco-Moreno, Raquel
author
Gómez-Andrades, Ana
author
Serrano, Inmaculada
2024-10-07T11:10:09Z
2024-10-07T11:10:09Z
2015
E. J. Khatib, R. Barco, A. Gómez-Andrades and I. Serrano, "Diagnosis Based on Genetic Fuzzy Algorithms for LTE Self-Healing," in IEEE Transactions on Vehicular Technology, vol. 65, no. 3, pp. 1639-1651, March 2016, doi: 10.1109/TVT.2015.2414296.
https://hdl.handle.net/10630/34440
10.1109/TVT.2015.2414296
Self-organizing network (SON) mechanisms reduce operational expenditure in cellular networks while enhancing the offered quality of service. Within a SON, self-healing aims to autonomously solve problems in the radio access network and to minimize their impact on the user. Self-healing comprises automatic fault detection, root cause analysis, fault compensation, and recovery. This paper presents a root cause analysis system based on fuzzy logic. A genetic algorithm is proposed for learning the rule base. The proposed method is adapted to the way of reasoning of troubleshooting experts, which ease knowledge acquisition and system output interpretation. Results show that the obtained results are comparable or even better than those obtained when the troubleshooting experts define the rules, with the clear benefit of not requiring the experts to define the system. In addition, the system is robust, since fine tuning of its parameters is not mandatory.
eng
Algoritmos difusos
LTE (Telecomunicaciones)
Diagnosis Based on Genetic Fuzzy Algorithms for LTE Self-Healing.
journal article
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