  A typical handover problem requires sequence of complex signaling between a
UE, the serving, and target base station. In many handover problems the down
link based measurements are transferred from a user equipment to a serving base
station and the decision on handover is made on these measurements. These
measurements together with the signaling between the user equipment and the
serving base station is computationally expensive and can potentially drain
user equipment battery. Coupled with this, the future networks are densely
deployed with multiple frequency layers, rendering current handover mechanisms
sub-optimal, necessitating newer methods that can improve energy efficiency. In
this study, we will investigate a ML based approach towards secondary carrier
prediction for inter-frequency handover using the up-link reference signals.
