Path Loss and Error Statistics Analysis in 5G mmWave Wireless Networks Using Particle Swarm Optimization

Abstract

In wireless communication systems, accurate path loss estimation is one of the major concerns. This study evaluates and estimates path loss in an urban microenvironment using various path loss models, with a focus on optimizing these models to better represent real-world propagation. In this study, we considered particle swarm optimization algorithm to identify the optimized path loss models in the LOS and NLOS scenarios. The analytically calculated path loss is compared with the optimized values, and estimated the error statistics, are used to evaluate each model's performance. Simulation results demonstrate that particle swarm optimization algorithm significantly reduces path loss compared to analytical estimated. The 3GPP-SC model in the LOS scenario, optimized with PSO, achieved minimized error statistics of 3.85, 1.96, and 1.47. In the NLOS scenario, the 5GCM-OS model shows minimized error statistics of 7.84, 2.80, and 1.9. Therefore, in an urban environment, 3GPP-SC and 5GCM-OS models are considered as the optimized path models in LOS and NLOS scenarios to enhance the network performance.