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Independent component analysis for blind multiuser detections

Authors: A. Kuh; null Xiaohong Gong;

Independent component analysis for blind multiuser detections

Abstract

We apply a novel signal processing method based on independent component analysis (ICA) to blind multiuser receivers. ICA is well suited for blind multiuser detection problems as the criterion used to separate signals is a mutual information minimization principle which attempts to separate independent signals from mixed signals. When the cross-correlations between signature sequences are large, ICA has a better performance than decorrelating receivers and linear MMSE receivers.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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