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Adaptive soft-constraint satisfaction (SCS) algorithms for fractionally-spaced blind equalizers
conference contribution
posted on 2010-01-26, 12:49 authored by Buyurman Baykal, Oguz Tanrikulu, Jonathon ChambersConstant modulus algorithms based on a deterministic error criterion are presented. Soft-constraint satisfaction methods yield a general family of blind equalization algorithms employing nonlinear functions of the equalizer output which must satisfy certain conditions. The algorithms are also extended to cover fractionally-spaced blind equalization. A normalization factor which appears as a result of the deterministic formulation of the problem helps the blind equalizer improve its performance. Also, the family supports a wide range of nonlinear functions. Extensive simulations are presented to reveal convergence characteristics which also include signals from the signal processing information base (SPIB)
History
School
- Mechanical, Electrical and Manufacturing Engineering
Citation
BAYKAL, B., TANRIKULU, O. and CHAMBERS, J., 1997. Adaptive soft-constraint satisfaction (SCS) algorithms for fractionally-spaced blind equalizers. IN: Proceedings of the 1997 IEEE International Conference on Acoustics, Speech and Signal Processing. ICASSP-97, Munich, 21st-24th April 1997, Vol. 3, pp. 1853-1856Publisher
© IEEEVersion
- VoR (Version of Record)
Publication date
1997Notes
This is a conference paper [© IEEE]. It is also available from: 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.ISBN
0818679190Language
- en