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Multiuser Detection With an Unknown Number of Users
George Washington University, Washington, USA.ORCID iD: 0000-0002-7599-4367
2005 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 53, no 2, 724-728 p.Article in journal (Refereed) Published
Abstract [en]

This correspondence studies the problem of separating a signal of interest from co-channel interference for the situation when the number of co-channel users and their channels are unknown. We devise a novel approach to this problem based on a trained statistical mixture model. Numerical results illustrate that the new method can outperform conventional training-based multiuser detection.

Place, publisher, year, edition, pages
2005. Vol. 53, no 2, 724-728 p.
Keyword [en]
Bayesian information criterion, maximum a posteriori detection, maximum likelihood detection, model order estimation, multiuser detection, soft information
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-77019DOI: 10.1109/TSP.2004.840728OAI: oai:DiVA.org:liu-77019DiVA: diva2:524430
Available from: 2012-05-02 Created: 2012-05-02 Last updated: 2017-12-07Bibliographically approved

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Larsson, Erik G.

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