dc.creatorOLIVEIRA, Leonardo D.
dc.creatorNeto, Fernando Ciriaco Dias
dc.creatorABRAO, Taufik
dc.creatorJeszensky, Paul Jean Etienne
dc.date.accessioned2012-10-19T01:46:58Z
dc.date.accessioned2018-07-04T14:51:54Z
dc.date.available2012-10-19T01:46:58Z
dc.date.available2018-07-04T14:51:54Z
dc.date.created2012-10-19T01:46:58Z
dc.date.issued2009
dc.identifierAEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS, v.63, n.4, p.259-270, 2009
dc.identifier1434-8411
dc.identifierhttp://producao.usp.br/handle/BDPI/18717
dc.identifier10.1016/j.aeue.2008.01.009
dc.identifierhttp://dx.doi.org/10.1016/j.aeue.2008.01.009
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1615509
dc.description.abstractIn this work, a wide analysis of local search multiuser detection (LS-MUD) for direct sequence/code division multiple access (DS/CDMA) systems under multipath channels is carried out considering the performance-complexity trade-off. It is verified the robustness of the LS-MUD to variations in loading, E(b)/N(0), near-far effect, number of fingers of the Rake receiver and errors in the channel coefficients estimates. A compared analysis of the bit error rate (BER) and complexity trade-off is accomplished among LS, genetic algorithm (GA) and particle swarm optimization (PSO). Based on the deterministic behavior of the LS algorithm, it is also proposed simplifications over the cost function calculation, obtaining more efficient algorithms (simplified and combined LS-MUD versions) and creating new perspectives for the MUD implementation. The computational complexity is expressed in terms of the number of operations in order to converge. Our conclusion pointed out that the simplified LS (s-LS) method is always more efficient, independent of the system conditions, achieving a better performance with a lower complexity than the others heuristics detectors. Associated to this, the deterministic strategy and absence of input parameters made the s-LS algorithm the most appropriate for the MUD problem. (C) 2008 Elsevier GmbH. All rights reserved.
dc.languageeng
dc.publisherELSEVIER GMBH, URBAN & FISCHER VERLAG
dc.relationAeu-international Journal of Electronics and Communications
dc.rightsCopyright ELSEVIER GMBH, URBAN & FISCHER VERLAG
dc.rightsrestrictedAccess
dc.subjectMultiuser detection
dc.subjectParticle swarm optimization
dc.subjectLocal search
dc.subjectGenetic algorithm
dc.subjectComputational complexity
dc.titleLocal search multiuser detection
dc.typeArtículos de revistas


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