Decision-feedback equalization of data with spectral nulls

Research output: Contribution to conferencePaper

1 Citation (Scopus)

Abstract

An adaptive decision-feedback equalizer (DFE) update algorithm called the row-action projection (RAP) algorithm is presented. It does not suffer from the numerical stability and noise amplification problems of conventional adaptive equalization algorithms, and it offers linear computational complexity and fast tracking capability. Simulation results are presented that compare the algorithm to the conventional least-mean-squares (LMS) and recursive least squares (RLS) algorithms for decision-feedback equalization of a time-varying, bandlimited channel. The RAP algorithm is based on multiple use of the filter state vectors, viewed as rows of the system data matrix. The multiple updates have a geometric interpretation as projections toward the hyperplanes described by the rows of the system data matrix. The algorithm provides improved performance over the conventional LMS and RLS algorithms for DFE equalization of data whose frequency spectrum contains nulls as well improved mean square error (MSE) at the output of the DFE compared to the RLS algorithm for spectrally nulled data corrupted by noise. The RAP algorithm also has a lower average output MSE than either the LMS or RLS algorithm, for either the reference-directed or decision-directed modes of the DFE.

Original languageEnglish (US)
Pages76-80
Number of pages5
StatePublished - Dec 1 1990
Event1990 IEEE Military Communications Conference - MILCOM 90 Part 3 (of 3) - Monterey, CA, USA
Duration: Sep 30 1990Oct 3 1990

Other

Other1990 IEEE Military Communications Conference - MILCOM 90 Part 3 (of 3)
CityMonterey, CA, USA
Period9/30/9010/3/90

Fingerprint

Feedback
Decision feedback equalizers
Mean square error
Convergence of numerical methods
Amplification
Computational complexity

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

Doherty, J. F. (1990). Decision-feedback equalization of data with spectral nulls. 76-80. Paper presented at 1990 IEEE Military Communications Conference - MILCOM 90 Part 3 (of 3), Monterey, CA, USA, .
Doherty, John F. / Decision-feedback equalization of data with spectral nulls. Paper presented at 1990 IEEE Military Communications Conference - MILCOM 90 Part 3 (of 3), Monterey, CA, USA, .5 p.
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abstract = "An adaptive decision-feedback equalizer (DFE) update algorithm called the row-action projection (RAP) algorithm is presented. It does not suffer from the numerical stability and noise amplification problems of conventional adaptive equalization algorithms, and it offers linear computational complexity and fast tracking capability. Simulation results are presented that compare the algorithm to the conventional least-mean-squares (LMS) and recursive least squares (RLS) algorithms for decision-feedback equalization of a time-varying, bandlimited channel. The RAP algorithm is based on multiple use of the filter state vectors, viewed as rows of the system data matrix. The multiple updates have a geometric interpretation as projections toward the hyperplanes described by the rows of the system data matrix. The algorithm provides improved performance over the conventional LMS and RLS algorithms for DFE equalization of data whose frequency spectrum contains nulls as well improved mean square error (MSE) at the output of the DFE compared to the RLS algorithm for spectrally nulled data corrupted by noise. The RAP algorithm also has a lower average output MSE than either the LMS or RLS algorithm, for either the reference-directed or decision-directed modes of the DFE.",
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year = "1990",
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Doherty, JF 1990, 'Decision-feedback equalization of data with spectral nulls', Paper presented at 1990 IEEE Military Communications Conference - MILCOM 90 Part 3 (of 3), Monterey, CA, USA, 9/30/90 - 10/3/90 pp. 76-80.

Decision-feedback equalization of data with spectral nulls. / Doherty, John F.

1990. 76-80 Paper presented at 1990 IEEE Military Communications Conference - MILCOM 90 Part 3 (of 3), Monterey, CA, USA, .

Research output: Contribution to conferencePaper

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AU - Doherty, John F.

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Y1 - 1990/12/1

N2 - An adaptive decision-feedback equalizer (DFE) update algorithm called the row-action projection (RAP) algorithm is presented. It does not suffer from the numerical stability and noise amplification problems of conventional adaptive equalization algorithms, and it offers linear computational complexity and fast tracking capability. Simulation results are presented that compare the algorithm to the conventional least-mean-squares (LMS) and recursive least squares (RLS) algorithms for decision-feedback equalization of a time-varying, bandlimited channel. The RAP algorithm is based on multiple use of the filter state vectors, viewed as rows of the system data matrix. The multiple updates have a geometric interpretation as projections toward the hyperplanes described by the rows of the system data matrix. The algorithm provides improved performance over the conventional LMS and RLS algorithms for DFE equalization of data whose frequency spectrum contains nulls as well improved mean square error (MSE) at the output of the DFE compared to the RLS algorithm for spectrally nulled data corrupted by noise. The RAP algorithm also has a lower average output MSE than either the LMS or RLS algorithm, for either the reference-directed or decision-directed modes of the DFE.

AB - An adaptive decision-feedback equalizer (DFE) update algorithm called the row-action projection (RAP) algorithm is presented. It does not suffer from the numerical stability and noise amplification problems of conventional adaptive equalization algorithms, and it offers linear computational complexity and fast tracking capability. Simulation results are presented that compare the algorithm to the conventional least-mean-squares (LMS) and recursive least squares (RLS) algorithms for decision-feedback equalization of a time-varying, bandlimited channel. The RAP algorithm is based on multiple use of the filter state vectors, viewed as rows of the system data matrix. The multiple updates have a geometric interpretation as projections toward the hyperplanes described by the rows of the system data matrix. The algorithm provides improved performance over the conventional LMS and RLS algorithms for DFE equalization of data whose frequency spectrum contains nulls as well improved mean square error (MSE) at the output of the DFE compared to the RLS algorithm for spectrally nulled data corrupted by noise. The RAP algorithm also has a lower average output MSE than either the LMS or RLS algorithm, for either the reference-directed or decision-directed modes of the DFE.

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Doherty JF. Decision-feedback equalization of data with spectral nulls. 1990. Paper presented at 1990 IEEE Military Communications Conference - MILCOM 90 Part 3 (of 3), Monterey, CA, USA, .