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Blind Separation and Equalization Using Novel Hill-Climbing Optimization

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3 Author(s)
Dongxin Xu ; lnfoture, Inc., Boulder ; Hsiao-Chun Wu ; Chong-Yung Chi

In this paper, we construct a maximum-likelihood-equivalent metric or auxiliary function, which can result in a novel expectation-maximization Hill-Climbing (EM-HC) optimization procedure; it can be easily implemented for the estimation, detection and clustering applications since it is based on the simple auxiliary function. In this paper, one major application of our new EM-HC method, namely the blind separation and blind channel equalization, is presented and an efficient Iterative weighted least-mean squared (IWLMS) algorithm is derived thereupon. The new IWLMS algorithm derived from the EM-HC techniques greatly outperforms the prevalent blind equalization algorithm based on the constant-modulus criteria according to simulations.

Published in:

Signals, Systems and Computers, 2007. ACSSC 2007. Conference Record of the Forty-First Asilomar Conference on

Date of Conference:

4-7 Nov. 2007

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