A Novel Demodulation Method for Chaotic Parameter Modulation

Author

Xu, Maoge ; Song, Yaoliang ; Liu, Liwei

Author_Institution

Dept. of Electron. Eng., Nanjing Univ. of Sci. & Technol.

fYear

2006

fDate

22-24 Sept. 2006

Firstpage

1

Lastpage

4

Abstract

This paper proposes a particle filter to demodulate the chaotic parameter modulation (CPM) signal CPM embeds the signal of transmission in the bifurcating parameter of a chaotic dynamical system, and uses the wide-band output of the chaotic system as the transmitted signal. As the bifurcating parameter of the chaotic dynamical system is unknown and the demodulation problem is just a system identification problem. Conventional methods like extended Kalman filter (EKF) and least mean square (LMS) have relatively poor performance. Incorporating Rao-Blackwellisaion (RB) and roughening noise method, particle filtering can be used to estimate the parameter sequentially. Simulation results confirm that the proposed particle filter has the improved performance compared to the EKF and LMS

Keywords

Kalman filters; chaotic communication; demodulation; least mean squares methods; nonlinear filters; particle filtering (numerical methods); Rao-Blackwellisaion; chaotic dynamical system; chaotic parameter modulation; demodulation method; extended Kalman filter; least mean square; parameter bifurcation; parameter estimation; particle filter; roughening noise method; signal transmission; system identification problem; Bifurcation; Chaos; Chaotic communication; Demodulation; Filtering; Least squares approximation; Logistics; Parameter estimation; Particle filters; System identification;

fLanguage

English

Publisher

ieee

Conference_Titel

Wireless Communications, Networking and Mobile Computing, 2006. WiCOM 2006.International Conference on

Conference_Location

Wuhan

Print_ISBN

1-4244-0517-3

Type

conf

DOI

10.1109/WiCOM.2006.156

Filename

4149333