A blind detection-guided approach for normalised multi-modulus crosstalk estimator in sparse multi-user DSL channels

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Abstract

In high-speed digital subscriber lines (DSL), far-end crosstalk is the main limiting factor on data rates. However, most of the crosstalk is due to the neighbouring twisted pairs in the binder. Therefore, the crosstalk channel matrix is sparse. Using Level 3 of Dynamic Spectrum Management, users are co-ordinated at the central office to cancel the crosstalk. Means for estimating the crosstalk canceller matrix are of critical importance for the cancellation to prove effective. Preferably, the estimation procedure should have low overhead both in computation and bandwidth. Normalised least mean squares (NLMS) based adaptive crosstalk cancellers (Gujrathi et al. (2009) [1]) have a low computational overhead but use a training sequence to ensure they converge adequately. However, using a training sequence consumes some amount of bandwidth which can be avoided if an unsupervised or blind algorithm like a normalised multi-modulus algorithm (NMMA) is used instead. A limitation of NMMA is that its convergence time is often longer than that of the NLMS algorithm. Furthermore, this is made worse as the number of canceller coefficients is made larger. In application to adaptive crosstalk cancellation within the multi-user DSL binder-channel, we argue that the convergence time can be significantly decreased by using an activity detector to exclude canceller coefficients below an appropriate minimum. In this paper, we present an activity detector design using a thresholding criterion based on the least squares technique, Akaike's information criterion (Homer et al. (1998) [2]) and Donoho's universal thresholding principle (Donoho (1995) [3]). This enables us to identify the significant crosstalkers within a DSL binder for each user. We further incorporate this strategy within the blind estimation NMMA and propose an enhanced crosstalk canceller. Our simulations indicate this multi-modulus detection-guided crosstalk canceller demonstrates improved convergence speed and has a steady state error close to that of the standard (non-detection-guided) canceller.

Section snippets

Mandar L. Gujrathi was born in Mumbai, India in 1980. He received the B.E. degree in Electronics Engineering from the University of Mumbai, India and the M.E. degree in Electrical Engineering from the University of Queensland, Australia in 2002 and 2003 respectively. In 2004, he was a research associate in optical physics and the following year he commenced his Ph.D. in Telecommunications Engineering in the School of Information Technology and Electrical Engineering at the University of

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Mandar L. Gujrathi was born in Mumbai, India in 1980. He received the B.E. degree in Electronics Engineering from the University of Mumbai, India and the M.E. degree in Electrical Engineering from the University of Queensland, Australia in 2002 and 2003 respectively. In 2004, he was a research associate in optical physics and the following year he commenced his Ph.D. in Telecommunications Engineering in the School of Information Technology and Electrical Engineering at the University of Queensland. He has recently submitted his thesis for examination and holds a Research Officer position in the same school. His research interests include signal processing for telecommunications, lattice theory and optical communications.

John Homer received the B.Sc. degree in Physics from the University of Newcastle, Australia in 1985 and the Ph.D. degree in Systems Engineering from the Australian National University, Australia in 1995. Between his B.Sc. and Ph.D. studies he held a position of Research Engineer at Comalco Research Centre in Melbourne, Australia. Following his Ph.D. studies he has held research positions with the University of Queensland, Veritas DGC Pty Ltd and Katholieke Universiteit Leuven, Belgium and a Senior Lecturing position at the University of Queensland within the School of Information Technology and Electrical Engineering. He is currently a Senior Research Engineer with the Defence Science and Technology Organisation. His research interests include signal and image processing, particularly in the application areas of telecommunications, audio and radar.

I. Vaughan L. Clarkson was born in Brisbane, Queensland, Australia, in 1968. He received the B.Sc. degree in Mathematics and the B.E. degree (Hons. I) in Computer Systems Engineering from the University of Queensland, Brisbane, Australia, in 1989 and 1990, respectively, and the Ph.D. degree in Systems Engineering from the Australian National University, Canberra, Australia, in 1997.

Starting in 1988, he was employed by the Defence Science and Technology Organisation, Adelaide, Australia, first as a Cadet, later as a Professional Officer, and finally as a Research Scientist. From 1998 to 2000, he was a Lecturer at the University of Melbourne, Melbourne, Australia. From 2000 to 2008, he was a Senior Lecturer in the School of Information Technology and Electrical Engineering at the University of Queensland. In 2008, he was promoted to Reader. In 2005, he was a Visiting Professor in the Department of Electrical and Computer Engineering at the University of British Columbia, Vancouver, Canada. His research interests include statistical signal processing for communications and defence, image processing, information theory and lattice theory.

Jennifer Wu was born in Shanghai, China in 1981. She received the B.E. degree (with honours) in Electrical Engineering and the Master of Philosophy degree from the University of Queensland, Australia in 2004 and 2006 respectively. She is currently a Ph.D. student in the Research School of Information Science and Engineering, the Australian National University. Her research interests include multichannel sound reproduction systems, array signal processing, adaptive filtering and physical layer wireless communication systems.

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