By Topic

Noise Robust Multichannel Frequency-Domain LMS Algorithms for Blind Channel Identification

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Mohammad Ariful Haque ; Bangladesh Univ. of Eng. & Technol., Dhaka ; Md Kamrul Hasan

A number of multichannel least mean square (LMS)-type algorithms have been proposed in the literature to identify single-input multi-output finite impulse response channels. All of these algorithms share the common characteristic of good initial convergence followed by a rapid misconvergence in the presence of noise. This misconvergence characteristic is due to the nonuniform spectral attenuation of the estimated channel coefficients as reported in some research results. In this letter, we formulate a novel cost function that inherently oppose such spectral attenuation resulting from the noisy update vector. We show analytically that the gradient of the proposed penalty term enforces uniform distribution of the estimated channel spectral energy over the entire frequency band and thus contribute to ameliorating the misconvergence of these multichannel algorithms in the presence of noise. The robustness of the proposed algorithm is verified using numerical examples for different channels in a wide range of signal-to-noise ratios.

Published in:

IEEE Signal Processing Letters  (Volume:15 )