Estimation of Channel Parameters in a Multipath Environment via Optimizing Highly Oscillatory Error-Functions Using a Genetic Algorithm

TL;DR

This paper presents a genetic algorithm-based method for estimating multipath channel parameters in noisy wireless environments, focusing on maximizing likelihood estimates despite complex, oscillatory error functions.

Contribution

It introduces a novel application of genetic algorithms to optimize highly oscillatory error functions for channel parameter estimation in multipath scenarios.

Findings

Genetic algorithms effectively estimate channel parameters in noisy multipath environments.

The proposed method demonstrates robustness to estimation errors.

Simulation results validate the accuracy of the maximum likelihood estimates.

Abstract

Channel estimation is of crucial importance for tomorrow's wireless mobile communication systems. This paper focuses on the solution of channel parameters estimation problem in a scenario involving multiple paths in the presence of additive white Gaussian noise. We assumed that number of paths in the multipath environment is known and the transmitted signal consists of attenuated and delayed replicas of a known transient signal. In order to determine the maximum likelihood estimates one has to solve a complicated optimization problem. Genetic Algorithms (GA) are well known for their robustness in solving complex optimization problems. A GA is considered to extract channel parameters to minimize the derived error-function. The solution is based on the maximum-likelihood estimation of the channel parameters. Simulation results also demonstrate GA's robustness to channel parameters estimation errors.