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Journal of Electrical and Computer Engineering
Volume 2012, Article ID 614384, 10 pages
Review Article

On Particle Swarm Optimization for MIMO Channel Estimation

Information and Coding Theory Laboratory, University of Kiel, 24143 Kiel, Germany

Received 7 July 2011; Revised 30 November 2011; Accepted 14 December 2011

Academic Editor: Lisimachos P. Kondi

Copyright © 2012 Christopher Knievel and Peter Adam Hoeher. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Evolutionary algorithms, in particular particle swarm optimization (PSO), have recently received much attention. PSO has successfully been applied to a wide range of technical optimization problems, including channel estimation. However, most publications in the area of digital communications ignore improvements developed by the PSO community. In this paper, an overview of the original PSO is given as well as improvements that are generally applicable. An extension of PSO termed cooperative PSO (CPSO) is applied for MIMO channel estimation, providing faster convergence and, thus, lower overall complexity. Instead of determining the average iterations needed empirically, a method to calculate the maximum number of iterations is developed, which enables the evaluation of the complexity for a wide range of parameters. Knowledge of the required number of iterations is essential for a practical receiver design. A detailed discussion about the complexity of the PSO algorithm and a comparison to a conventional minimum mean squared error (MMSE) estimator are given. Furthermore, Monte Carlo simulations are provided to illustrate the MSE performance compared to an MMSE estimator.