  In 5G cellular networks, frequency range 2 (FR2) introduces higher
frequencies that cause rapid signal degradation and challenge user mobility. In
recent studies, a conditional handover procedure has been adopted as an
enhancement to baseline handover to enhance user mobility robustness. In this
article, the mobility performance of conditional handover is analyzed for a 5G
mm-wave network in FR2 that employs beamforming. In addition, a
resource-efficient random access procedure is proposed that increases the
probability of contention-free random access during a handover. Moreover, a
simple yet effective decision tree-based supervised learning method is proposed
to minimize the handover failures that are caused by the beam preparation phase
of the random access procedure. Results have shown that a tradeoff exists
between contention-free random access and handover failures. It is also seen
that the optimum operation point of random access is achievable with the
proposed learning algorithm for conditional handover. Moreover, a mobility
performance comparison of conditional handover with baseline handover is also
carried out. Results have shown that while baseline handover causes fewer
handover failures than conditional handover, the total number of mobility
failures in the latter is less due to the decoupling of the handover
preparation and execution phases.
