Name
Title | ||
|---|---|---|
Compressed Sensing Bayes Risk Minimization for Under-Determined Systems via Sphere Detection |
Abstract | ||
|---|---|---|
The application of Compresses Sensing is a promising physical layer technology for the joint activity and data detection of signals. Detecting the activity pattern correctly has severe impact on the system performance and is therefore of major concern. In contrast to previous work, in this paper we optimize joint activity and data detection in under-determined systems by minimizing the Bayes-Risk for erroneous activity detection. We formulate a new Compressed Sensing Bayes-Risk detector which directly allows to influence error rates at the activity detection dynamically by a parameter that can be controlled at higher layers. We derive the detector for a general linear system and show that our detector outperforms classical Compressed Sensing approaches by investigating an overloaded CDMA system. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/VTCSpring.2013.6692486 | Vehicular Technology Conference |
Keywords | DocType | Volume |
Bayes methods,code division multiple access,compressed sensing,risk management,signal detection,CDMA system,compressed sensing Bayes risk minimization,error rates,joint signal activity pattern detection,joint signal data detection,physical layer technology,sparse signal detection,sphere detection,under-determined systems | Conference | abs/1404.0965 |
ISSN | Citations | PageRank |
1550-2252 | 4 | 0.46 |
References | Authors | |
4 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fabian Monsees | 1 | 29 | 4.44 |
| Carsten Bockelmann | 2 | 279 | 24.67 |
| Dirk Wübben | 3 | 361 | 36.45 |
| Armin Dekorsy | 4 | 513 | 57.91 |