A new self-planning methodology based on signal quality and user traffic in Wi-Fi networks
Document typeConference report
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Wi-Fi networks have become one of the most popular technologies for the provisioning of multimedia services. Due to the exponential increase in the number of Access Points (AP) in these networks, the automation of the planning, configuration, optimization and management tasks has become of prime importance. The efficiency of these automated processes can be improved with the inclusion of data analytics mechanisms able to process the large amount of data that can be collected from Wi-Fi networks by powerful monitoring systems. This paper presents a new self-planning methodology that collects historical network measurements and extracts knowledge about user signal quality and traffic demands to determine adequate AP relocations. The performance of the proposed AP relocation methodology based on a genetic algorithm is validated in a real Wi-Fi network. The proposed approach can be easily adapted to other contexts such as small cell networks.
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-030-19909-8_2
CitationSanchez, J.; Perez-Romero, J.; Sallent, J. A new self-planning methodology based on signal quality and user traffic in Wi-Fi networks. A: International Conference on Artificial Intelligence Applications and Innovations. "Artificial Intelligence Applications and Innovations: AIAI 2019 IFIP WG 12.5 International Workshops: MHDW and 5G-PINE 2019 Hersonissos, Crete, Greece: May 24-26, 2019: proceedings". Berlín: Springer, 2019, p. 19-30.