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Title: Random partial update sum-squared autocorrelation minimization algorithm for channel shortening (RPUSAM).
Authors: Grira, M.
Chambers, Jonathon
Issue Date: 2008
Publisher: © IEEE
Citation: GRIRA, M. and CHAMBERS, J.A., 2008. Random partial update sum-squared autocorrelation minimization algorithm for channel shortening (RPUSAM). IN: Proceedings of 2008 3rd International Symposium on Communications, Control and Signal Processing (ISCCSP 2008), St. Julians, Malta, 12-14 March, pp. 1400-1403.
Abstract: Partial updating is an effective method for reducing computational complexity in adaptive filter implementations. In this work, a novel random partial update sum-squared auto-correlation minimization (RPUSAM) algorithm is proposed. This algorithm has low computational complexity whilst achieving improved convergence performance, in terms of achievable bit rate, over a partial update sum-squared auto-correlation minimization (PUSAM) algorithm with a deterministic coefficient update strategy. The performance advantage of the RPUSAM algorithm is shown on eight different carrier serving area test loops (CSA) channels and comparisons are made with the original SAM and the PUSAM algorithms.
Description: This is a conference paper [© IEEE]. It is also available at: http://ieeexplore.ieee.org/ Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Version: Published
DOI: 10.1109/ISCCSP.2008.4537445
URI: https://dspace.lboro.ac.uk/2134/5591
Appears in Collections:Conference Papers and Contributions (Mechanical, Electrical and Manufacturing Engineering)

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