By Topic

Performance Analysis of Adaptive Decision Feedback Turbo Equalization (ADFTE) Using Recursive Least Square (RLS) Algorithm over Least Mean Square (LMS) Algorithm

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

3 Author(s)

In modern digital communication noise plays an important role. It essential to minimise the amount of noise added in the communication channel. The signal quality can be enhanced, by modelling the channel at the receiver, by means of equalization. Given large number of users employed in the system over multipath channels causing significant multiple-access interference (MAI) & inter symbol interference (ISI), the optimal MUD is thus prohibitively complex. Hence the sub-optimal detectors such as low-complexity linear & non-linear equalizers have to be considered. In this paper, recursive least square (RLS) adaptation algorithm for adaptive decision feedback turbo equalizer (ADFTE) is proposed. Along with the application of the adaptive method to the DFE-RLS equalizer, turbo-principle can easily be applied. The performance of the system is improved in the fashion of exchanging the extrinsic information iteratively among the soft-input/soft-output (SISO) equalizer & SISO channel decoder until convergence is achieved. The proposed turbo equalization implements the LOG-MAP (maximum a posterior) exclusively for both equalization & decoding. At each iteration, the estimated symbol is then saved as a priori information for next iteration. The simulation results shows that the proposed algorithm for DFE & turbo decoding offers performance gain improvement of 0.7 dB over the DFE-LMS.

Published in:

Conference on Computational Intelligence and Multimedia Applications, 2007. International Conference on  (Volume:4 )

Date of Conference:

13-15 Dec. 2007