A novel single lag auto-correlation minimization (SLAM) algorithm for blind adaptive channel shortening
Rab Nawaz
Jonathon Chambers
2134/5666
https://repository.lboro.ac.uk/articles/conference_contribution/A_novel_single_lag_auto-correlation_minimization_SLAM_algorithm_for_blind_adaptive_channel_shortening/9555227
A blind adaptive channel shortening algorithm based on minimizing
the sum of the squared autocorrelations (SAM) of
the effective channel was recently proposed. We submit
that identical channel shortening can be achieved by minimizing
the square of only a single autocorrelation. Our
proposed single lag autocorrelation minimization (SLAM)
algorithm has, therefore, very low complexity and also it
does not require, a priori, the knowledge of the length of the
channel. We also constrain the autocorrelation minimization
with a novel stopping criterion so that the shortening
signal to noise ratio (SSNR) of the effective channel is not
minimized by the autocorrelation minimization. The simulations
have shown that SLAM achieves higher bit rates
than SAM.
2009-12-14 12:20:53
untagged
Mechanical Engineering not elsewhere classified