@ARTICLE{7254244,
  author={A. {Gómez-Andrades} and P. {Muñoz} and E. J. {Khatib} and I. {de-la-Bandera} and I. {Serrano} and R. {Barco}},
  journal={IEEE Transactions on Vehicular Technology}, 
  title={Methodology for the Design and Evaluation of Self-Healing LTE Networks}, 
  year={2016},
  volume={65},
  number={8},
  pages={6468-6486},
  abstract={Self-healing networks aim to detect cells with service degradation, identify the fault cause of their problem, and execute compensation and repair actions. The development of this type of automatic system presents several challenges to be confronted. The first challenge is the scarce number of historically reported faults, which greatly complicates the evaluation of novel self-healing techniques. For this reason, in this paper, a system model to simulate faults in Long-Term Evolution (LTE) networks, along with their most significant key performance indicators, is proposed. Second, the expert knowledge required to build a self-healing system is usually not documented. Therefore, in this paper, a methodology to extract this information from a collection of reported cases is proposed. Finally, following the proposed methodology, an automatic fuzzy-logic-based system for fault identification in LTE networks is designed. Evaluation results show that the fuzzy system provides fault identification with a high success rate.},
  keywords={fault diagnosis;fuzzy logic;Long Term Evolution;telecommunication network reliability;Long-Term Evolution;self-healing LTE networks;service degradation;automatic system;self-healing system;automatic fuzzy-logic-based system;fault identification;Mobile communication;Mobile computing;Interference;Fault diagnosis;Design methodology;Long Term Evolution;Antenna radiation patterns;Diagnosis;fault identification;fault management;fuzzy logic;Long-Term Evolution (LTE);root cause analysis;self-healing;troubleshooting},
  doi={10.1109/TVT.2015.2477945},
  ISSN={1939-9359},
  month={Aug},}