  In this paper, we develop an efficient training beam sequence design approach
for millimeter wave MISO tracking systems. We impose a discrete state Markov
process assumption on the evolution of the angle of departure and introduce the
maximum a posteriori criterion to track it in each beam training period. Since
it is infeasible to derive an explicit expression for the resultant tracking
error probability, we turn to its upper bound, which possesses a closed-form
expression and is therefore leveraged as the objective function to optimize the
training beam sequence. Considering the complicated objective function and the
unit modulus constraints imposed by analog phase shifters, we resort to the
particle swarm algorithm to solve the formulated optimization problem.
Numerical results validate the superiority of the proposed training beam
sequence design approach.
