Numerical optimization based efficient beam switching for 60GHz millimeter-wave communications

Beam-forming training (or beam-steering) in the 60GHz millimeter-wave system is formulated as a numerical optimization problem. Although numerical search is of special promise to this problem, as the objective function (i.e, the signal-to-noise ratio) involves many local optimums, search failures cannot be avoided due to the greedy essence of classical Rosenbrock method. In order to address the great challenge, we develop an appealing direct numerical algorithm inspired by a probabilistic search mechanic. In contrast to classical schemes, numerical probes leading to reward improvement are always accepted, while search moves towards worse solution are permitted with a probability that is associated with an external temperature parameter. In order to enhance search performance of discrete space and exclude the exhaustive search-based neighbor exploitation, we further design a promising two-level annealing schedule. With the new probabilistic framework, the permission of movements to worse solutions is progressively restricted, which is controlled by two iterative parameters respectively corresponding to pattern probe and pattern move processes. Consequently, it may basically escape from local optimums. We then apply the new numerical search to 60GHz beam-switching. Experimental simulations validate this developed beam-switching scheme.