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Signal Processing
Volume 83, Issue 3, March 2003, Pages 641-648
 
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doi:10.1016/S0165-1684(02)00452-8    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2002 Elsevier Science B.V. All rights reserved.

Short communication

Constraints in channel shortening equalizer design for DMT-based systems

Geert YsebaertCorresponding Author Contact Information, E-mail The Corresponding Author, a, Katleen Van AckerE-mail The Corresponding Author, b, Marc MoonenE-mail The Corresponding Author, a and Bart De MoorE-mail The Corresponding Author, a

a ESAT/SISTA-Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, B-3001, Leuven-Heverlee, Belgium b Access to Networks, Research and Innovation, ALCATEL, B-2018, Antwerpen, Belgium

Received 25 January 2002; 
revised 31 July 2002. 
Available online 5 December 2002.

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Abstract

In discrete multitone receivers, a time domain equalizer (TEQ) is used to shorten the channel impulse response, so that the equalized channel impulse response is shorter than the inserted prefix. The aim of this paper is to show that the minimum mean square error (MMSE) channel shortening problem with two different energy constraints, remarkably, lead to the same TEQ coefficients, up to a scaling factor. Moreover, implying the two energy constraints together in the MMSE optimization again yields the same result and comes down to a canonical correlation analysis between the subspace spanned by the transmitted samples and the received samples, respectively. Hence, the TEQ obtained by these three distinct MMSE cases yields the same performance in terms of bit rate. Since the resulting problem can easily be reformulated as a maximization problem, an iterative procedure based on power iterations can be devised to reduce the computational complexity.

Author Keywords: High-speed modems; Time domain equalization (TEQ); Channel shortening

AT
transpose of A
A1/2
Cholesky factor of A, i.e. A=AT/2A1/2
J
cost function
ek
zero vector with 1 on the kth position
backward differenceaJ
gradient of cost function J with respect to a
Image
expected value
||a||2
Euclidean norm of a
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identity matrix
left flooraright floor
floor(a)

Article Outline

Nomenclature
1. Introduction
2. MMSE solution with unit-energy constraints
3. Iterative procedure
4. Simulation results
4.1. Bit rate performance
4.2. Iterative procedure for unit-energy constraints
5. Conclusions
Acknowledgements
Appendix A
A.1. Proofs
References




Signal Processing
Volume 83, Issue 3, March 2003, Pages 641-648
 
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