Name
Abstract | ||
|---|---|---|
In this paper, we explore the significance of second- and higher-order statistics learning in communication systems. The final goal in spread-spectrum communication systems is to receive a signal of interest completely free from interference caused by other concurrent signals. To achieve this end, we exploit the structure of the interference by designing second-order statistics detectors, such as the minimum square error, in conjunction with higher-order statistics (HOS) techniques, such as the blind source separation (BSS). This hybrid higher-order statistics (HyHOS) approach enables us to alleviate BSS algorithms of one of their main problems, that is, their sensitiveness to high levels of noise. In addition, we benefit from remarkable properties of BSS in learning such as fast learning (superefficiency) and independence of the initial settings of the problem (equivariance). We successfully applied the results of this approach to the design of multiuser detectors in code-division multiple access channels. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/TSMCC.2004.833299 | IEEE Transactions on Systems, Man, and Cybernetics, Part C |
Keywords | Field | DocType |
spread-spectrum communication system,bss algorithm,higher-order statistic,hybrid higher-order statistic,communication system,code-division multiple access channel,second-order statistics detector,fast learning,concurrent signal,blind source separation,multiuser detection,unsupervised learning,code division multiple access,independent component analysis,spread spectrum communication,indexing terms | Computer science,Multiuser detection,Communications system,Unsupervised learning,Artificial intelligence,Order statistic,Blind signal separation,Computer engineering,Spread spectrum,Higher-order statistics,Speech recognition,Code division multiple access,Machine learning | Journal |
Volume | Issue | ISSN |
34 | 4 | 1094-6977 |
Citations | PageRank | References |
4 | 0.46 | 26 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Antonio J. Caamaño | 1 | 82 | 12.07 |
| Rafael Boloix-Tortosa | 2 | 42 | 7.20 |
| J. Ramos | 3 | 4 | 0.46 |
| J. J. Murillo-Fuentes | 4 | 20 | 3.56 |