Joint Bayesian the Number of Active Users Estimation and the Signatures Detection in DS-CDMA System

Author

Chen Lianghui ; Hu Hanying

Author_Institution

Dept. of Commun. Eng., Inf. Eng. Univ., Zhengzhou

fYear

2007

fDate

21-25 Sept. 2007

Firstpage

846

Lastpage

849

Abstract

The estimation of the number of users and detection of the signatures in the unknown colored noise is considered. We exploit the Reversible Jump Markov Chain Monte Carlo (RJMCMC) method to solve the problem. Through introducing subspace algorithm and converting condition state spaces of the posterior distribution, the method based on Bayesian inference achieves the joint posterior probability density function of desired parameters by integrating out the nuisance. Simulation results support the effectiveness of the algorithm.

Keywords

Bayes methods; Markov processes; Monte Carlo methods; code division multiple access; multiuser detection; spread spectrum communication; statistical distributions; Bayesian inference; DS-CDMA system; active user estimation; joint posterior probability density function; multiuser detection; reversible jump Markov chain Monte Carlo method; signatures detection; subspace algorithm; unknown colored noise; Additive noise; Bayesian methods; Colored noise; Detectors; Gaussian noise; Inference algorithms; Monte Carlo methods; Multiaccess communication; State-space methods; Transmitters;

fLanguage

English

Publisher

ieee

Conference_Titel

Wireless Communications, Networking and Mobile Computing, 2007. WiCom 2007. International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-1311-9

Type

conf

DOI

10.1109/WICOM.2007.218

Filename

4339993