Blind beamformer for constant modulus signals based on relevance vector machine

Kyuho Hwang, Sooyong Choi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The blind beamforming method for constant modulus (CM) signals based on relevance vector machine (RVM) is proposed. The proposed beamforming method is obtained by incorporating the constant modulus algorithm (CMA)-like error function into the conventional RVM framework. The RVM framework formulates the parameters of beamfomer by exploiting a probabilistic Bayesian learning procedure with assumption of Gaussian prior for parameters. The simulation results show that the proposed blind beamforming method can restore the desired signals with crowded interference signals.

Original languageEnglish
Title of host publication2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings
Pages2112-2115
Number of pages4
DOIs
Publication statusPublished - 2011 Aug 18
Event36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Prague, Czech Republic
Duration: 2011 May 222011 May 27

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011
CountryCzech Republic
CityPrague
Period11/5/2211/5/27

Fingerprint

Beamforming
Signal interference

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Hwang, K., & Choi, S. (2011). Blind beamformer for constant modulus signals based on relevance vector machine. In 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings (pp. 2112-2115). [5946743] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2011.5946743
Hwang, Kyuho ; Choi, Sooyong. / Blind beamformer for constant modulus signals based on relevance vector machine. 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings. 2011. pp. 2112-2115 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).
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title = "Blind beamformer for constant modulus signals based on relevance vector machine",
abstract = "The blind beamforming method for constant modulus (CM) signals based on relevance vector machine (RVM) is proposed. The proposed beamforming method is obtained by incorporating the constant modulus algorithm (CMA)-like error function into the conventional RVM framework. The RVM framework formulates the parameters of beamfomer by exploiting a probabilistic Bayesian learning procedure with assumption of Gaussian prior for parameters. The simulation results show that the proposed blind beamforming method can restore the desired signals with crowded interference signals.",
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Hwang, K & Choi, S 2011, Blind beamformer for constant modulus signals based on relevance vector machine. in 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings., 5946743, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, pp. 2112-2115, 36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011, Prague, Czech Republic, 11/5/22. https://doi.org/10.1109/ICASSP.2011.5946743

Blind beamformer for constant modulus signals based on relevance vector machine. / Hwang, Kyuho; Choi, Sooyong.

2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings. 2011. p. 2112-2115 5946743 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - The blind beamforming method for constant modulus (CM) signals based on relevance vector machine (RVM) is proposed. The proposed beamforming method is obtained by incorporating the constant modulus algorithm (CMA)-like error function into the conventional RVM framework. The RVM framework formulates the parameters of beamfomer by exploiting a probabilistic Bayesian learning procedure with assumption of Gaussian prior for parameters. The simulation results show that the proposed blind beamforming method can restore the desired signals with crowded interference signals.

AB - The blind beamforming method for constant modulus (CM) signals based on relevance vector machine (RVM) is proposed. The proposed beamforming method is obtained by incorporating the constant modulus algorithm (CMA)-like error function into the conventional RVM framework. The RVM framework formulates the parameters of beamfomer by exploiting a probabilistic Bayesian learning procedure with assumption of Gaussian prior for parameters. The simulation results show that the proposed blind beamforming method can restore the desired signals with crowded interference signals.

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Hwang K, Choi S. Blind beamformer for constant modulus signals based on relevance vector machine. In 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings. 2011. p. 2112-2115. 5946743. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2011.5946743