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IEEE Transactions on Wireless Communications
Article . 2006 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
DBLP
Article . 2020
Data sources: DBLP
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Efficient Complex Sphere Decoding for MC-CDMA Systems

Authors: Ricardo Santiago-Mozos; M. Julia Fernández-Getino García;

Efficient Complex Sphere Decoding for MC-CDMA Systems

Abstract

Maximum likelihood (ML) joint detection of multi-carrier code division multiple access (MC-CDMA) systems can be efficiently implemented with a sphere decoding (SD) algorithm. In this paper, we examine the application of complex instead of real SD to detect MC-CDMA, which solves many problems in a more elegant manner and extends SD adaptability to any constellation. We first propose a new complex SD algorithm whose efficiency is based on not requiring an estimate of the initial search radius but selecting the Babai point as the initial sphere radius instead; also, efficient strategies regarding sorting the list of possible lattice points are applied. Indeed, complex SD allows complex matrix operations which are faster than real counterparts in double dimension. Next, a novel lattice representation for the MC-CDMA system is introduced, which allows optimum multiuser detection directly from the received signal. This avoids noise whitening operation, and also despreading and equalization procedures are not required further at the receiver side This work has been partly funded by the Spanish government with national project MACAWI (TEC 2005-07477-c02-02) and project MAMBO (UC3M-TEC-05-027)

Keywords

Multi carrier code division multiple access, Telecomunicaciones, Sphere decoding, Maximum likelihood decoding, Multiuser detection

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selected citations
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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).
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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!
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