Name
Abstract | ||
|---|---|---|
This paper presents a novel approach for characterizing wide- band (CDMA) multiple dimensional channels for the wireless en- vironment in arbitrarily coloured additive Gaussian noise. This characterization is sufficient for the specification of optimal mul- tichannel space-time receivers. The proposed solution is defined in the Bayesian framework and uses the Reversible Jump Markov Chain Monte Carlo (MCMC) method to obtain estimates of the number of scatterers, their directions of arrival and their times of arrival. The developed method is applied to simulated and real measured data to verify the performance of the approach. In this paper, we address the problem of characterizing wireless multipath channels for CDMA receivers which use an array of an- tennas. We assume the propagation channel consists of a discrete number of independent Rayleigh-faded components, each with a distinct direction of arrival and relative delay time. We consider the special case where the noise covariance matrix of the antenna elements is unknown and arbitrarily coloured. Our objective is to estimate the number of scatterers, the corresponding delay times (TOAs), and the directions of arrival (DOAs) of the multipath com- ponents using only the data received from an antenna array in a wideband scenario. This characterization is sufficient for the con- |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1109/ICASSP.2001.940512 | ICASSP '01). 2001 IEEE International Conference |
Keywords | Field | DocType |
Bayes methods,Gaussian noise,Markov processes,Monte Carlo methods,Rayleigh channels,array signal processing,broadband networks,code division multiple access,direction-of-arrival estimation,electromagnetic wave scattering,multipath channels,multiuser channels,radio receivers,Bayesian framework,CDMA,Rayleigh fading,coloured additive Gaussian noise,directions of arrival,multipath channel,noise covariance matrix,optimal multichannel space-time receivers,propagation channel,real measured data,reversible jump MCMC,reversible jump Markov chain Monte Carlo method,scatterers,simulated data,wideband multiple dimensional channels,wireless environment | Wideband,Mathematical optimization,Monte Carlo method,Markov process,Markov chain Monte Carlo,Computer science,Algorithm,Reversible-jump Markov chain Monte Carlo,Jump,Statistics,Code division multiple access,Gaussian noise | Conference |
Volume | ISSN | ISBN |
4 | 1520-6149 | 0-7803-7041-4 |
Citations | PageRank | References |
1 | 0.43 | 5 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jean-Rene Larocque | 1 | 1 | 0.43 |
| James Reilly | 2 | 457 | 43.42 |