By Topic

Fast computation of channel-estimate based equalizers in packet data transmission

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
$31 $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)
Al-Dhahir, N. ; Corp. Res. & Dev., Gen. Electr. Co., Schenectady, NY, USA ; Cioffi, J.M.

Computationally efficient procedures are introduced for the real-time calculation of finite-impulse-response (FIR) equalizers for packet-based data transmission applications, such as wireless data networks. In such packet data applications, the FIR equalizer filters are computed indirectly by first estimating the channel pulse response from a known training pattern embedded in each packet and then computing the equalizer for use in the recovery of the remaining unknown data in the packet. We find that a minimum mean-square-error decision-feedback equalizer (MMSE-DFE) with a finite-length constraint on its feedforward and feedback filters can be very efficiently computed from this pulse response. We combine a recent theory of finite-spectral factorization for the MMSE-DFE with the theory of structured matrices to derive these efficient procedures for computing the equalizer settings. The introduced method is much more computationally efficient than direct computation by matrix inversion or the use of popular gradient or least-squares algorithms over the duration of the packet

Published in:

Signal Processing, IEEE Transactions on  (Volume:43 ,  Issue: 11 )