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Automatic Feature Selection Technique for Next Generation Self-Organizing Networks
2018
IEEE Communications Letters
Despite self-organizing networks (SONs) pursue the automation of management tasks in current cellular networks, the selection of the most useful performance indicators (PIs), used as inputs for SON functions, is still performed by network experts. In this letter, a novel supervised technique for the automatic selection of PIs for self-healing functions is proposed, relying on the dissimilarity of their statistical behavior under different network states. Results using data from a live network
doi:10.1109/lcomm.2018.2825392
fatcat:wsrdm37x6fbjxoio4324tk7cwy