By Topic

A binary adaptive decision-selection equalizer for channels with nonlinear intersymbol interference

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)

An enhanced adaptive decision feedback equalizer (ADFE) is presented for binary data transmission applications where the communication channel exhibits nonlinear intersymbol interference (ISI). The nonlinearity in the channel manifests itself as a distorted constellation space constructed from the equalizer input state variables. Since a conventional ADFE can construct a hyperplane decision boundary of only one orientation with symmetrically spaced distance from the origin as a function of the detected feedback symbols and feedback filter coefficient values, there is room for improvement since the distorted constellation of the nonlinear system is better served by hyperplane boundaries of varying orientation. The method proposed here is not to feed back the decision variables but, instead, to use these binary variables to choose and adapt different sets of coefficients, i.e., different hyperplane boundaries. Hence, the name given to this new method is the adaptive decision-selection equalizer (ADSE). Although the hyperplane may not be the optimum boundary for the conditional constellations, in many cases, it is an adequate approximation. Nonetheless, for nonlinear channels, the ADSE is generally an improvement over the conventional ADFE in high signal-to-noise ratio (SNR) regimes, where the bit error rate (BER) is within the desired operating range. The major advantage of the new method is improved performance on the studied channel while retaining simplicity when implemented as a variation of the least-mean-squared (LMS) algorithm. Some drawbacks are decreased convergence rate and limitations of the minimum mean-squared-error (MMSE) strategy of optimization, as implemented by the LMS algorithm, for a system where error probability, not MMSE, is important.

Published in:

IEEE Transactions on Signal Processing  (Volume:50 ,  Issue: 9 )