Cell identification based on received signal strength fingerprints: concept and application towards energy saving in cellular networks

The increasing deployment of small cells aimed at off-loading data traffic from macrocells in heterogeneous networks has resulted in a drastic increase in energy consumption in cellular networks. Energy consumption can be optimized in a selforganized way by adapting the number of active cells in response to the current traffic demand. In this paper we concentrate on the complex problem of how to identify small cells to be reactivated in situations where multiple cells are concurrently inactive. Solely based on the received signal strength, we present cell-specific patterns for the generation of unique cell fingerprints. The cell fingerprints of the deactivated cells are matched with measurements from a high data rate demanding mobile device to identify the most appropriate candidate. Our scheme results in a matching success rate of up to 100% to identify the best cell depending on the number of cells to be activated

Una visión basada en QoE para algoritmo MRO en redes LTE

Due to the huge increase in traffic and services in mobile networks, network management has changed its main focus from Quality of Service (QoS) to a Quality of Experience (QoE) perspective. In addition, SON (Self organization Networks) techniques have been developed to automate network management, being Mobility Robustness Optimization a key use case. Traditionally, Mobility Robustness Optimization aims to improving Handover performance by reducing too-early, too-late and ping-pong handovers. Nevertheless, these techniques may fail when pursuing maximum user QoE at cell edge. In this work, a novel Mobility Robustness Optimization algorithm is proposed to reach maximum QoE at cell edge in a realistic LTE network with a file download service.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech