Blind Equalization Using a Stop-and-Go Decision-Directed Least Squares Algorithm

• Main Authors: Yu-Hang Lin, 林于寒
• Other Authors: Jenq-Tay Yuan
• Format: Others
• Language: en_US
• Published: 2002
• Online Access: http://ndltd.ncl.edu.tw/handle/67394654784070372640

碩士 === 輔仁大學 === 電子工程學系 === 90 === The conventional CMA-based algorithms exhibit slow convergence rate and high mean-squared error (MSE) in the steady state. In this thesis, we propose a new algorithm to improve the performance of the existing blind equalization algorithms. The proposed algorithm combines the advantages of the stop-and-go strategy, the modified constant modulus algorithm (MCMA) and the CMA-RLS algorithm. It not only can significantly accelerate the rate of convergence but also can improve the steady state MSE. Moreover, we combine the algorithm with the fractionally spaced equalizer (FSE) to further improve the performance especially in the severely distorted channels or low SNR environments. Computer simulations demonstrate that the proposed algorithm indeed achieves excellent performance in terms of rate of convergence and steady state MSE.