Adaptive Blind Multiuser Detection over Flat Fast Fading Channels Using Particle Filtering
<p>We propose a method for blind multiuser detection (MUD) in synchronous systems over flat and fast Rayleigh fading channels. We adopt an autoregressive-moving-average (ARMA) process to model the temporal correlation of the channels. Based on the ARMA process, we propose a novel time-observat...
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
SpringerOpen
2005-01-01
|
Series: | EURASIP Journal on Wireless Communications and Networking |
Subjects: | |
Online Access: | http://dx.doi.org/10.1155/WCN.2005.130 |
id |
doaj-ba6cffdb77124f1da4f1ad55f3f11d09 |
---|---|
record_format |
Article |
spelling |
doaj-ba6cffdb77124f1da4f1ad55f3f11d092020-11-24T23:07:49ZengSpringerOpenEURASIP Journal on Wireless Communications and Networking1687-14721687-14992005-01-0120052130140Adaptive Blind Multiuser Detection over Flat Fast Fading Channels Using Particle FilteringHuang YufeiZhang Jianqiu (Michelle)Luna Isabel TiendaDjurić Petar M.Padillo Diego Pablo Ruiz<p>We propose a method for blind multiuser detection (MUD) in synchronous systems over flat and fast Rayleigh fading channels. We adopt an autoregressive-moving-average (ARMA) process to model the temporal correlation of the channels. Based on the ARMA process, we propose a novel time-observation state-space model (TOSSM) that describes the dynamics of the addressed multiuser system. The TOSSM allows an MUD with natural blending of low-complexity particle filtering (PF) and mixture Kalman filtering (for channel estimation). We further propose to use a more efficient PF algorithm known as the stochastic <math alttext="$M$"><mi>M</mi> </math> -algorithm (SMA), which, although having lower complexity than the generic PF implementation, maintains comparable performance.</p> http://dx.doi.org/10.1155/WCN.2005.130multiuser detectiontime-observation state-space modelfading channel estimationparticle filteringmixture Kalman filter |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Huang Yufei Zhang Jianqiu (Michelle) Luna Isabel Tienda Djurić Petar M. Padillo Diego Pablo Ruiz |
spellingShingle |
Huang Yufei Zhang Jianqiu (Michelle) Luna Isabel Tienda Djurić Petar M. Padillo Diego Pablo Ruiz Adaptive Blind Multiuser Detection over Flat Fast Fading Channels Using Particle Filtering EURASIP Journal on Wireless Communications and Networking multiuser detection time-observation state-space model fading channel estimation particle filtering mixture Kalman filter |
author_facet |
Huang Yufei Zhang Jianqiu (Michelle) Luna Isabel Tienda Djurić Petar M. Padillo Diego Pablo Ruiz |
author_sort |
Huang Yufei |
title |
Adaptive Blind Multiuser Detection over Flat Fast Fading Channels Using Particle Filtering |
title_short |
Adaptive Blind Multiuser Detection over Flat Fast Fading Channels Using Particle Filtering |
title_full |
Adaptive Blind Multiuser Detection over Flat Fast Fading Channels Using Particle Filtering |
title_fullStr |
Adaptive Blind Multiuser Detection over Flat Fast Fading Channels Using Particle Filtering |
title_full_unstemmed |
Adaptive Blind Multiuser Detection over Flat Fast Fading Channels Using Particle Filtering |
title_sort |
adaptive blind multiuser detection over flat fast fading channels using particle filtering |
publisher |
SpringerOpen |
series |
EURASIP Journal on Wireless Communications and Networking |
issn |
1687-1472 1687-1499 |
publishDate |
2005-01-01 |
description |
<p>We propose a method for blind multiuser detection (MUD) in synchronous systems over flat and fast Rayleigh fading channels. We adopt an autoregressive-moving-average (ARMA) process to model the temporal correlation of the channels. Based on the ARMA process, we propose a novel time-observation state-space model (TOSSM) that describes the dynamics of the addressed multiuser system. The TOSSM allows an MUD with natural blending of low-complexity particle filtering (PF) and mixture Kalman filtering (for channel estimation). We further propose to use a more efficient PF algorithm known as the stochastic <math alttext="$M$"><mi>M</mi> </math> -algorithm (SMA), which, although having lower complexity than the generic PF implementation, maintains comparable performance.</p> |
topic |
multiuser detection time-observation state-space model fading channel estimation particle filtering mixture Kalman filter |
url |
http://dx.doi.org/10.1155/WCN.2005.130 |
work_keys_str_mv |
AT huangyufei adaptiveblindmultiuserdetectionoverflatfastfadingchannelsusingparticlefiltering AT zhangjianqiumichelle adaptiveblindmultiuserdetectionoverflatfastfadingchannelsusingparticlefiltering AT lunaisabeltienda adaptiveblindmultiuserdetectionoverflatfastfadingchannelsusingparticlefiltering AT djuri263petarm adaptiveblindmultiuserdetectionoverflatfastfadingchannelsusingparticlefiltering AT padillodiegopabloruiz adaptiveblindmultiuserdetectionoverflatfastfadingchannelsusingparticlefiltering |
_version_ |
1725616867180019712 |