Single channel blind signal separation with Bayesian-MCMC

Author

Geng, Peng ; Zhi-tao, Huang ; Feng-hua, Wang ; Wen-li, Jiang

Author_Institution

Sch. of Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha, China

fYear

2009

fDate

13-15 Nov. 2009

Firstpage

1

Lastpage

4

Abstract

To solve the problem of single channel blind signal separation with unknown components number, a method based on Bayesian-MCMC is presented. First, single channel mixed signal, whose components have same general parameters, is modeled to change the problem into joint estimation of signal parameters and components number. Then, Bayesian theorem is applied in the joint estimation. Lastly, Bayesian computation of the estimation is accomplished with reversible jump MCMC. Simulation results indicate that the algorithm is practical and effective.

Keywords

Markov processes; Monte Carlo methods; blind source separation; channel estimation; combined source-channel coding; Bayesian theorem; Bayesian-MCMC; Monte Carlo Markov chain; joint estimation; single channel blind signal separation; single channel mixed signal; Bayesian methods; Blind source separation; Filtering; Filters; Frequency estimation; Independent component analysis; Intersymbol interference; Parameter estimation; Signal processing; Signal processing algorithms; Bayesian theorem; SCBSS (single channel blind signal separation); joint estimation; reversible jump MCMC (Monte Carlo Markov Chain);

fLanguage

English

Publisher

ieee

Conference_Titel

Wireless Communications & Signal Processing, 2009. WCSP 2009. International Conference on

Conference_Location

Nanjing

Print_ISBN

978-1-4244-4856-2

Electronic_ISBN

978-1-4244-5668-0

Type

conf

DOI

10.1109/WCSP.2009.5371525

Filename

5371525