A Genetic Algorithm Applied for Optimization of Antenna Arrays Used in Mobile Radio Channel Characterization Devices

This paper presents a proposed method for synthesizing scenario-dependent channel characterization system arrays that are adapted to the mobile radio environment where measurements take place. The criterion for synthesizing the array is the minimization of the angular Cramer-Rao lower bound, which is the lower bound of the mean square estimation error (MSEE) for an unbiased estimator. The core of the process is a genetic algorithm (GA) that seeks for the most advantageous array topology for each scenario. Simulation results show that the method succeeds in synthesizing feasible antenna arrays that have increased direction of arrival (DoA) estimation accuracy and are superior to the arrays typically used during actual measurement campaigns.