Skip to main content
  • Research Article
  • Open access
  • Published:

Soft-In Soft-Output Detection in the Presence of Parametric Uncertainty via the Bayesian EM Algorithm

Abstract

We investigate the application of the Bayesian expectation-maximization (BEM) technique to the design of soft-in soft-out (SISO) detection algorithms for wireless communication systems operating over channels affected by parametric uncertainty. First, the BEM algorithm is described in detail and its relationship with the well-known expectation-maximization (EM) technique is explained. Then, some of its applications are illustrated. In particular, the problems of SISO detection of spread spectrum, single-carrier and multicarrier space-time block coded signals are analyzed. Numerical results show that BEM-based detectors perform closely to the maximum likelihood (ML) receivers endowed with perfect channel state information as long as channel variations are not too fast.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to AS Gallo.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and permissions

About this article

Cite this article

Gallo, A., Vitetta, G. Soft-In Soft-Output Detection in the Presence of Parametric Uncertainty via the Bayesian EM Algorithm. J Wireless Com Network 2005, 201802 (2005). https://doi.org/10.1155/WCN.2005.100

Download citation

  • Received:

  • Revised:

  • Published:

  • DOI: https://doi.org/10.1155/WCN.2005.100

Keywords