Efficient Evaluation of Incident Power Density by Millimeter-Wave MIMO User Equipment Using Vectorized Field Superposition and Stochastic Population Optimizers

In this work, stochastic population optimizers are applied with vectorized field values to determine the peak exposure of user equipment (UE) installed with a multiple-input multiple-output (MIMO) antenna operating at 28 GHz. This problem presents a significant challenge due to the difficulty in evaluating all possible configurations of the input values. By aids of optimization on initial population size as well as the sampling spacing, two optimizers incorporating variable population size exhibit good robustness and efficiency, i.e., an error of 1% compared to the results by Monte Carlo (MC) simulation of 1 000 000 times. A reduction in the simulation time of 90% compared to MC simulation of 10 000 times. The proposed method demonstrates its performance in evaluating exposure at both planar and nonplanar surface according to the standards. Besides, the method can be applied in postprocessing of the numerical simulation and the measured data for maximized spatial-average power density. The study provides a new and easy to implement method for efficiently characterizing the maximum exposure from millimeter wave MIMO UE.