Millimeter wave channel characteristics of outdoor microcellular based on improved ray tracing method and BP neural network algorithm

Abstract

The millimeter-wave single-input single-output (SISO) channel and single input multiple output (SIMO) channel are modeled and simulated in the outdoor microcellular scenarios at 28 GHz and 39 GHz based on improved ray tracing method and back propagation (BP) neural network algorithm. Based on the simulation data of wireless channel, the propagation characteristics of millimeter wave channel, such as path loss, root-mean-square (RMS) delay spread and received power, are analyzed and researched. The correctness and effectiveness of the improved ray tracing method are verified by comparing the measured results of the published literature with the simulated results. The results of path loss model parameters fitted by BP neural network algorithm are compared with those of path loss parameters simulated by improved ray tracing method. It is found that the results of path loss parameters fitted by BP neural network algorithm are in good agreement with those obtained by simulation of improved ray tracing method, which verifies that BP neural network algorithm can well predict large-scale parameters of outdoor microcellular millimeter-wave channel. Meanwhile, a universal path loss model for 28 GHz and 39 GHz millimeter-wave channels in outdoor microcellular line-of-sight (LoS) and non-line-of-sight (NLoS) scenarios is presented. The results show that the RMS delay spread and received power in LoS scenario are smaller than those in NLoS scenario. The cumulative distribution function (CDF) of RMS delay spread, horizontal direction angle of arrival and the number of multipath clusters in LoS and NLoS scenarios are found to fit the Gaussian distribution properly. As the frequency increases, the RMS delay spread tends to increase, and the cluster of multipath arriving at receivers shows sparsity in the microcellular scenarios at millimeter-wave band.