Equalization For Discrete Multitone Transceivers

Mr. Guner Arslan
The University of Texas at Austin

Wednesday, November 15th, 10;00 AM, ENS 602

arslan@ece.utexas.edu


Abstract

G.DMT and G.lite Asymmetric Digital Subscriber Line (ADSL) modems and some Very-high-speed Digital Subscriber Line (VDSL) modems rely on discrete multitone modulation (DMT). In an ADSL discrete multitone receiver, a time-domain equalizer (TEQ) reduces intersymbol interference (ISI) by shortening the effective duration of the channel impulse response. Methods such as minimum mean-squared error (MSE), maximum shortening SNR (SSNR), and geometric TEQ design methods do not directly optimize channel capacity. We present a TEQ design method to optimize channel capacity. We also present a computationally-efficient, near-optimal minimum-ISI (min-ISI) method that generalizes the maximum SSNR (MSSNR) method by weighting the ISI in the frequency domain.

Biography

Guner Arslan graduated as Valedictorian with BS in Electronics and Telecommunication Engineering degree from Yildiz University at Kocaeli, Kocaeli, Turkey in July 1994. He joined the Dept. of Electronics and Telecommunication Engineering of Yildiz Technical University in Istanbul as a Research Assistant in 1995 where he worked on DTMF detection, stereophonic acoustic echo cancellation, SAR image processing, and speech recognition. He received his MS in Electronics and Telecommunication Engineering from Yildiz Technical University, Istanbul, Turkey in July 1996.

While taking classes for his Ph.D. at Yildiz Technical University he received a full scholarship from the Turkish Government in 1998 to continue his graduate education abroad. He is working towards his Ph.D.E.E degree in the area of Telecommunications and Information Systems Engineering from The Dept. of Electrical and Computer Engineering at the University of Texas at Austin, Austin, TX. His current research interests are digital signal processing for communications, audio/speech applications and learning systems (neural networks, genetic algorithms, adaptive filters).


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