Gaussian Processes for Digital Communications

Author

Pérez-Cruz, Fernando ; Murillo-Fuentes, Juan José

Author_Institution

Gatsby Comput. Neurosci. Unit, Univ. Coll. London

Volume

5

fYear

2006

fDate

14-19 May 2006

Abstract

We present Gaussian processes (GPs) for digital communications. GPs can be used to construct analytical nonlinear regression functions, which can be suitable for digital communications in which linear solutions under perform. GPs can be cast as nonlinear MMSE and its hyperparameters can be easily learnt by maximum likelihood. We present some experimental results regarding multi-user detection in CDMA systems and show the GPs outperform linear and nonlinear state-of-the-art solutions

Keywords

Gaussian processes; code division multiple access; digital communication; least mean squares methods; multiuser detection; regression analysis; CDMA systems; Gaussian processes; digital communications; multiuser detection; nonlinear MMSE; nonlinear regression functions; Biological neural networks; Communication systems; Covariance matrix; Digital communication; Gaussian processes; Maximum likelihood detection; Maximum likelihood estimation; Multiaccess communication; Multiuser detection; Support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on

Conference_Location

Toulouse

ISSN

1520-6149

Print_ISBN

1-4244-0469-X

Type

conf

DOI

10.1109/ICASSP.2006.1661392

Filename

1661392