Machine Learning Approach to Estimating mmWave Signal Measurements During Handover
We propose to estimate mmWave received signal power levels using supervised machine learning and LTE signal measurements in sub-6 GHz bands. Contributions of this paper include 1) introduction of partially blind handovers, 2) demonstration that LTE measurements from sub-6 GHz LTE bands can help improve handover to mmWave frequency bands, and 3) an algorithm to improve handover success rates using an extreme gradient boosting classifier. Simulation results show an improvement of 1.5% in the handover success rate by the proposed method over the baseline method.