Research Article
RSS based Cell Fingerprint Patterns and Algorithms for Cell Identification in the Context of Self-organized Energy Saving
@INPROCEEDINGS{10.4108/icst.mobiquitous.2014.258231, author={Elke Roth-Mandutz and Stephen S. Mwanje and Andreas Mitschele-Thiel}, title={RSS based Cell Fingerprint Patterns and Algorithms for Cell Identification in the Context of Self-organized Energy Saving}, proceedings={11th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services}, publisher={ICST}, proceedings_a={MOBIQUITOUS}, year={2014}, month={11}, keywords={fingerprinting energy saving son lte small cells}, doi={10.4108/icst.mobiquitous.2014.258231} }- Elke Roth-Mandutz
Stephen S. Mwanje
Andreas Mitschele-Thiel
Year: 2014
RSS based Cell Fingerprint Patterns and Algorithms for Cell Identification in the Context of Self-organized Energy Saving
MOBIQUITOUS
ICST
DOI: 10.4108/icst.mobiquitous.2014.258231
Abstract
Due to the large number of newly deployed small cells in heterogeneous networks needed for off-loading the mobile data traffic, the energy consumption in mobile cellular networks is strongly increasing. Energy consumption can be optimized in a self-organized way by adapting the number of active cells to the current traffic demand. In this paper we concentrate on how to identify small cells to be reactivated. Solely based on the received signal strength, we present cell-specific patterns for the generation of unique cell fingerprints. Using matching algorithms, the cell fingerprints of the deactivated cells are matched with a measurement sample from a User Entity (UE) to identify the most appropriate candidate. Our results give a matching success rate of 95% to identify the best cell to be activated.