Super Exponential Iteration Adaptive Minimum Entropy Blind Equalization Algorithm Based on Quantum Artificial Fish Swarm Optimization

Ye Cai Guo; Wei Huan; Li Fu Wu; Ke Cheng Leng

doi:10.4028/www.scientific.net/AMR.779-780.1793

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 779-780Super Exponential Iteration Adaptive Minimum...

Super Exponential Iteration Adaptive Minimum Entropy Blind Equalization Algorithm Based on Quantum Artificial Fish Swarm Optimization

Abstract:

In order to improve equalization performance of higher-order non-constant modulus signals, adaptive minimum entropy super-exponential iteration blind equalization algorithm based on quantum artificial fish swarm optimization was proposed. The proposed algorithm can accelerate convergence rate via super-exponential iteration algorithm and decease mean square error (MSE) further via quantum artificial fish swarm algorithm. The simulation results demonstrate that the proposed algorithm has different equalization performance to the different modulation systems and can speed up convergence rate and decrease state MSE.

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Periodical:

Advanced Materials Research (Volumes 779-780)

Pages:

1793-1796

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.779-780.1793

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Online since:

September 2013

Authors:

Ye Cai Guo, Wei Huan, Li Fu Wu, Ke Cheng Leng

Keywords:

Amplitude Phase Shift Key, Blind Equalization Algorithm, Convergence Rate, Quantum Artificial Fish Swarm

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