RT Journal Article
T1 Diagnosis Based on Genetic Fuzzy Algorithms for LTE Self-Healing.
A1 Khatib, Emil Jatib
A1 Barco-Moreno, Raquel
A1 Gómez-Andrades, Ana
A1 Serrano, Inmaculada
K1 Algoritmos difusos
K1 LTE (Telecomunicaciones)
AB 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.
PB IEEE
YR 2015
FD 2015
LK https://hdl.handle.net/10630/34440
UL https://hdl.handle.net/10630/34440
LA eng
NO 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.
NO https://v2.sherpa.ac.uk/id/publication/3582
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026