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Convolutional encoding effects on conventional multiuser decoding algorithm in imperfect decoding conditions

Authors: Simona V. Halunga; Ioana M. Marcu; Octavian Fratu; Dragos N. Vizireanu;

Convolutional encoding effects on conventional multiuser decoding algorithm in imperfect decoding conditions

Abstract

The present work aims to illustrate the improvement that turbo encoding / decoding algorithms can bring to a multiuser detection system, evaluated in terms of Bit Error Rate (BER). Extended simulations have been performed for conventional multiuser detection algorithms and are still under study for other algorithms, like the optimal, the MMSE and the classical MMSE ones. Simulations have been performed in both optimal conditions and imperfect ones, like non-equal power of users and non- zero correlations between them and for different number of users. Several interesting conclusions have been highlighted with respect to parameters influence on overall system performances.

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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!
1
Average
Average
Average
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