Optimization of Handover Parameters for LTE/LTE-A in-Building Systems

The optimization of handover (HO) parameters for in-building systems is investigated in this paper. We proposed a novel methodology that provides in-building base stations with the flexibility to customize HO parameters to specific radio frequency conditions at the cell-edge for different loading scenarios. We propose the use of machine learning and data mining techniques to allow the base stations to autonomously learn and identify characteristic patterns in the received signal strength values (reported by users during the HO process), and apply optimal HO parameters for each case. Our optimization strategy jointly considers the radio frequency conditions at the cell-edge and the load levels of the base stations, to determine optimal HO parameters that maximize the quality of service and guarantee the continuity of service at the cell-edge. We evaluated our methodology with experimental data collected from two fully operational LTE in-building systems deployed in a university campus. Our results show that with our methodology the spectral efficiency at the cell-edge can be greatly improved. Downlink data rate gains at the cell-edge reached a value close to 150% for a certain loading scenario compared to the traditional approach of selecting a unique set of HO parameters for the entire in-building system.