Local search multiuser detection


Autoria(s): OLIVEIRA, Leonardo D.; Neto, Fernando Ciriaco Dias; ABRAO, Taufik; Jeszensky, Paul Jean Etienne
Contribuinte(s)

UNIVERSIDADE DE SÃO PAULO

Data(s)

18/10/2012

18/10/2012

2009

Resumo

In 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.

Identificador

AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS, v.63, n.4, p.259-270, 2009

1434-8411

http://producao.usp.br/handle/BDPI/18717

10.1016/j.aeue.2008.01.009

http://dx.doi.org/10.1016/j.aeue.2008.01.009

Idioma(s)

eng

Publicador

ELSEVIER GMBH, URBAN & FISCHER VERLAG

Relação

Aeu-international Journal of Electronics and Communications

Direitos

restrictedAccess

Copyright ELSEVIER GMBH, URBAN & FISCHER VERLAG

Palavras-Chave #Multiuser detection #Particle swarm optimization #Local search #Genetic algorithm #Computational complexity #Engineering, Electrical & Electronic #Telecommunications
Tipo

article

original article

publishedVersion