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With the increase of the mobile network complexity, minimizing the level of human intervention in the network management and troubleshooting has become a crucial factor. This paper focuses on enhancing the level of automation in the network management by dynamically learning the mobile network cell states and improving the anomaly detection on the(More)
Increased demand for higher user throughput has led to deployment of multi-layer networks commonly called heterogeneous networks (Hetnets). Therein, small cells are deployed alongside traditional macro cells, in many cases on the same spectrum. Such scenarios complicate the configuration of network parameters such as the Physical Cell Identity (PCI). A(More)
There is a major demand for reducing energy consumption in mobile networks and it is expected become even more vital in the future (5G) multi-layer Ultra Dense Networks (UDNs), in which the number and density of cells in the different layers will grow dramatically. In these networks, multiple geographically overlapping layers are deployed to increase the(More)