Home // International Journal On Advances in Systems and Measurements, volume 2, number 1, 2009 // View article

Modified SRF-QRD-LSL Adaptive Algorithm with Improved Numerical Robustness

Authors:
Constantin Paleologu
Felix Albu
Andrei Alexandru Enescu
Silviu Ciochină

Keywords: Adaptive filters, echo cancellation, fixed-point arithmetic, logarithmic number system (LNS), QR-decomposition-based least-squares lattice (QRD-LSL).

Abstract:
The QR-decomposition-based least-squares lattice (QRDLSL) algorithm is one of the most attractive choices for adaptive filters applications, mainly due to its fast convergence rate and good numerical properties. In practice, the square-root-free QRD-LSL (SRF-QRD-LSL) algorithms are frequently employed, especially when fixedpoint digital signal processors (DSPs) are used for implementation. In this context, there are some major limitations regarding the large dynamic range of the algorithm’s cost functions. Consequently, hard scaling operations are required, which further reduce the precision of numerical representation and lead to performance degradation. In this paper we propose a SRF-QRD-LSL algorithm based on a modified update of the cost functions, which offers improved numerical robustness. Simulations performed in fixed-point and logarithmic number system (LNS) implementations support the theoretical findings. Also, in order to outline some practical aspects of this work, the proposed algorithm is tested in the context of echo cancellation. It is shown that this algorithm outperforms by far the normalized least-mean-square (NLMS) algorithm (which is the most common choice for echo cancellation), especially in terms of double-talk robustness.

Pages: 56 to 65

Copyright: Copyright (c) to authors, 2009. Used with permission.

Publication date: June 7, 2009

Published in: journal

ISSN: 1942-261x