Adaptive equalization based on internal model principle for time-varying fading channels

T. Naito; K. Hidaka; Jingmin Xin; Hiromitsu Ohmori; A. Sano

doi:10.1109/ASSPCC.2000.882501

Adaptive equalization based on internal model principle for time-varying fading channels

T. Naito, K. Hidaka, Jingmin Xin, Hiromitsu Ohmori, A. Sano

Department of System Design Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

A novel adaptive filtering algorithm is presented to identify the time-varying parameters of an FIR channel model. The proposed weights adjusting algorithm incorporates an internal model for compensating the dynamics of the time-varying model parameters. The stability of the adaptive filter can be assured by designing the weights adjusting dynamics in the adaptive algorithm by applying the passivity theorem and the small gain theorem. Its effectiveness of the proposed LMS and RLS types of algorithms is validated by comparing to ordinary LMS approaches in numerical simulation of adaptive identification and decision-feedback equalization of a time-varying fading channel with parameters changing with a first-order function of time.

Original language	English
Title of host publication	IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium, AS-SPCC 2000
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	363-368
Number of pages	6
ISBN (Print)	0780358007, 9780780358003
DOIs	https://doi.org/10.1109/ASSPCC.2000.882501
Publication status	Published - 2000
Event	IEEE Adaptive Systems for Signal Processing, Communications, and Control Symposium, AS-SPCC 2000 - Lake Louise, Canada Duration: 2000 Oct 1 → 2000 Oct 4

Other

Other	IEEE Adaptive Systems for Signal Processing, Communications, and Control Symposium, AS-SPCC 2000
Country/Territory	Canada
City	Lake Louise
Period	00/10/1 → 00/10/4

ASJC Scopus subject areas

Computer Networks and Communications
Signal Processing
Control and Systems Engineering

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10.1109/ASSPCC.2000.882501

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Naito, T., Hidaka, K., Xin, J., Ohmori, H., & Sano, A. (2000). Adaptive equalization based on internal model principle for time-varying fading channels. In IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium, AS-SPCC 2000 (pp. 363-368). Article 882501 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ASSPCC.2000.882501

Adaptive equalization based on internal model principle for time-varying fading channels. / Naito, T.; Hidaka, K.; Xin, Jingmin et al.
IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium, AS-SPCC 2000. Institute of Electrical and Electronics Engineers Inc., 2000. p. 363-368 882501.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Naito, T, Hidaka, K, Xin, J, Ohmori, H & Sano, A 2000, Adaptive equalization based on internal model principle for time-varying fading channels. in IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium, AS-SPCC 2000., 882501, Institute of Electrical and Electronics Engineers Inc., pp. 363-368, IEEE Adaptive Systems for Signal Processing, Communications, and Control Symposium, AS-SPCC 2000, Lake Louise, Canada, 00/10/1. https://doi.org/10.1109/ASSPCC.2000.882501

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N2 - A novel adaptive filtering algorithm is presented to identify the time-varying parameters of an FIR channel model. The proposed weights adjusting algorithm incorporates an internal model for compensating the dynamics of the time-varying model parameters. The stability of the adaptive filter can be assured by designing the weights adjusting dynamics in the adaptive algorithm by applying the passivity theorem and the small gain theorem. Its effectiveness of the proposed LMS and RLS types of algorithms is validated by comparing to ordinary LMS approaches in numerical simulation of adaptive identification and decision-feedback equalization of a time-varying fading channel with parameters changing with a first-order function of time.

AB - A novel adaptive filtering algorithm is presented to identify the time-varying parameters of an FIR channel model. The proposed weights adjusting algorithm incorporates an internal model for compensating the dynamics of the time-varying model parameters. The stability of the adaptive filter can be assured by designing the weights adjusting dynamics in the adaptive algorithm by applying the passivity theorem and the small gain theorem. Its effectiveness of the proposed LMS and RLS types of algorithms is validated by comparing to ordinary LMS approaches in numerical simulation of adaptive identification and decision-feedback equalization of a time-varying fading channel with parameters changing with a first-order function of time.

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Adaptive equalization based on internal model principle for time-varying fading channels

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