Blind Algorithm for Decision Feedback Equalizer
Summary :
In this letter, we propose a blind adaptation method for the decision feedback equalizer (DFE). In the proposed scheme, a DFE is divided into two parts: a front-end linear equalizer (LE), and a prediction error filter (PEF) followed by a feedback part. The coefficients of the filters in each part are updated using constant modulus algorithm and decision feedback prediction algorithm, respectively. The front-end LE removes intersymbol interference ISI, and the PEF with feedback part whitens the noise to reduce noise power enhanced by the LE. Pre-processing by the LE enables the DFE to equalize nonminimum phase channels. Simulation results show that the proposed scheme provides reliable convergence, and the resulting symbol error rate is much less than that of the conventional LE and very close to that of the DFE using a training sequence.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E80-B No.1 pp.200-204
- Publication Date
- 1997/01/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- Category
- Communication Device and Circuit
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Bo Seok SEO, Jae Hyok LEE, Choong Woong LEE, "Blind Algorithm for Decision Feedback Equalizer" in IEICE TRANSACTIONS on Communications,
vol. E80-B, no. 1, pp. 200-204, January 1997, doi: .
Abstract: In this letter, we propose a blind adaptation method for the decision feedback equalizer (DFE). In the proposed scheme, a DFE is divided into two parts: a front-end linear equalizer (LE), and a prediction error filter (PEF) followed by a feedback part. The coefficients of the filters in each part are updated using constant modulus algorithm and decision feedback prediction algorithm, respectively. The front-end LE removes intersymbol interference ISI, and the PEF with feedback part whitens the noise to reduce noise power enhanced by the LE. Pre-processing by the LE enables the DFE to equalize nonminimum phase channels. Simulation results show that the proposed scheme provides reliable convergence, and the resulting symbol error rate is much less than that of the conventional LE and very close to that of the DFE using a training sequence.
URL: https://global.ieice.org/en_transactions/communications/10.1587/e80-b_1_200/_p
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@ARTICLE{e80-b_1_200,
author={Bo Seok SEO, Jae Hyok LEE, Choong Woong LEE, },
journal={IEICE TRANSACTIONS on Communications},
title={Blind Algorithm for Decision Feedback Equalizer},
year={1997},
volume={E80-B},
number={1},
pages={200-204},
abstract={In this letter, we propose a blind adaptation method for the decision feedback equalizer (DFE). In the proposed scheme, a DFE is divided into two parts: a front-end linear equalizer (LE), and a prediction error filter (PEF) followed by a feedback part. The coefficients of the filters in each part are updated using constant modulus algorithm and decision feedback prediction algorithm, respectively. The front-end LE removes intersymbol interference ISI, and the PEF with feedback part whitens the noise to reduce noise power enhanced by the LE. Pre-processing by the LE enables the DFE to equalize nonminimum phase channels. Simulation results show that the proposed scheme provides reliable convergence, and the resulting symbol error rate is much less than that of the conventional LE and very close to that of the DFE using a training sequence.},
keywords={},
doi={},
ISSN={},
month={January},}
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TY - JOUR
TI - Blind Algorithm for Decision Feedback Equalizer
T2 - IEICE TRANSACTIONS on Communications
SP - 200
EP - 204
AU - Bo Seok SEO
AU - Jae Hyok LEE
AU - Choong Woong LEE
PY - 1997
DO -
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E80-B
IS - 1
JA - IEICE TRANSACTIONS on Communications
Y1 - January 1997
AB - In this letter, we propose a blind adaptation method for the decision feedback equalizer (DFE). In the proposed scheme, a DFE is divided into two parts: a front-end linear equalizer (LE), and a prediction error filter (PEF) followed by a feedback part. The coefficients of the filters in each part are updated using constant modulus algorithm and decision feedback prediction algorithm, respectively. The front-end LE removes intersymbol interference ISI, and the PEF with feedback part whitens the noise to reduce noise power enhanced by the LE. Pre-processing by the LE enables the DFE to equalize nonminimum phase channels. Simulation results show that the proposed scheme provides reliable convergence, and the resulting symbol error rate is much less than that of the conventional LE and very close to that of the DFE using a training sequence.
ER -
English
