Blind Equalization Algorithm of Variable Segment Error Function Based on Catfish Effect Particle Swarm Optimization

Authors

Yecai Guo, 1. School of Electronic and Information Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China;;2. Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment, Nanjing University of Information Science & Technology, Nanjing 210044, China;
Jiping Wu, 1. School of Electronic and Information Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China;;

Abstract

Abstract: In order to overcome the disadvantage of the slow convergence rate and big steady state error of constant modulus algorithm (CMA), a variable segment error constant modulus blind equalization algorithm based on the catfish effect particle swarm optimization algorithm (CEPSO-VSCMA) is proposed. The algorithm introduces catfish effect particle swarm optimization on the base of VSCMA, finding the globally optimal solution with the global searching of particle swarm. Meanwhile, vibrant and competitive catfish individual are employed to reactivate particle swarm and accelerate convergence. The simulation results show that the proposed algorithm performs better in improving convergence rate, decreasing inter-symbol interference with CMA, VSCMA and PSO-VSCMA.

Recommended Citation

Guo, Yecai and Wu, Jiping (2019) "Blind Equalization Algorithm of Variable Segment Error Function Based on Catfish Effect Particle Swarm Optimization," Journal of System Simulation: Vol. 30: Iss. 9, Article 42.
DOI: 10.16182/j.issn1004731x.joss.201809042
Available at: https://dc-china-simulation.researchcommons.org/journal/vol30/iss9/42

First Page

3558

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201809042

Last Page

3563

CLC

TN991.5

Recommended Citation

Guo Yecai, Wu Jiping. Blind Equalization Algorithm of Variable Segment Error Function Based on Catfish Effect Particle Swarm Optimization[J]. Journal of System Simulation, 2018, 30(9): 3558-3563.

DOI

10.16182/j.issn1004731x.joss.201809042