Random-search algorithms in the problem of the adaptation of an antenna array with discrete phase shifters

The possibility of using discrete controlled phase shifters in the signal-processing system of an adaptive array is investigated. A two-level adaptation algorithm with self-learning based on random-search methods is proposed. The possibility of obtaining quasi-optimal solutions, i.e., sets of phase shifter states in the adaptive array channels that would result in a high signal-to-noise ratio at the output of the device, is demonstrated analytically and experimentally.