  For a base station that supports cellular communications in sub-6 GHz LTE and
millimeter (mmWave) bands, we propose a supervised machine learning algorithm
to improve the success rate in the handover between the two radio frequencies
using sub-6 GHz and mmWave prior channel measurements within a temporal window.
The main contributions of our paper are to 1) introduce partially blind
handovers, 2) employ machine learning to perform handover success predictions
from sub-6 GHz to mmWave frequencies, and 3) show that this machine learning
based algorithm combined with partially blind handovers can improve the
handover success rate in a realistic network setup of colocated cells.
Simulation results show improvement in handover success rates for our proposed
algorithm compared to standard handover algorithms.
