Particle Swarm Optimization Algorithm Based Multi-Path Channel Model Simplification

In a system with a large bandwidth, the number of resolvable paths of the channel model is particularly large, making the computer simulation of the channel model and related applications extremely complicated. Therefore, it is necessary to simplify the channel model on the premise of retaining the basic characteristics of the channel. Our goal is to construct a channel model with less paths to approximate the original multi-path channel model, and the absolute error between the frequency correlation functions of the two is used to measure the similarity between them. In this paper, we propose an improved particle swarm optimization algorithm to simplify a multi-path channel. And Lagrangian multiplier method is applied to calculate the power parameters of the simplified channel. Simulation results show that the performance of this algorithm is better than the weighted merger method.