DocumentCode :
1694812
Title :
Detection Algorithm for V-BLAST System Based on Hybrid Discrete Particle Swarm Optimization
Author :
Dong, Wei ; Li, Jiandong ; Zhu, Mingming ; Chen, Liang
Author_Institution :
State Key Lab. of Integrated Service Networks, Xidian Univ., Xian
fYear :
2008
Firstpage :
196
Lastpage :
200
Abstract :
According, to the new discrete particle swarm optimization (NDPSO) and combining NDPSO with the mutation operator of the genetic algorithm, we proposed a novel hybrid discrete particle swarm optimization detection algorithm for the vertical bell-labs layered space-time (V-BLAST) system. The complexity of the proposed detection algorithm is analyzed. Compared with the maximum likelihood (ML) detection algorithm which has the best BER performance but the highest computational complexity, the proposed detection algorithm is capable of reducing the computational complexity significantly. Simulation results show that the bit error rate (BER) of the proposed algorithm is very close to that of the ML detection algorithm and significantly lower than the other suboptimal detection algorithms. The algorithm is a new method to solve the detection problem in V-BLAST system.
Keywords :
computational complexity; error statistics; genetic algorithms; maximum likelihood detection; particle swarm optimisation; space-time codes; BER performance; V-BLAST system; bit error rate; computational complexity; genetic algorithm; hybrid discrete particle swarm optimization; maximum likelihood detection algorithm; mutation operator; new discrete particle swarm optimization; suboptimal detection algorithms; vertical bell-labs layered space-time system; Algorithm design and analysis; Bit error rate; Computational complexity; Computational modeling; Detection algorithms; Laboratories; Maximum likelihood detection; Particle swarm optimization; Receiving antennas; Transmitting antennas;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems for Communications, 2008. ICCSC 2008. 4th IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-1707-0
Electronic_ISBN :
978-1-4244-1708-7
Type :
conf
DOI :
10.1109/ICCSC.2008.48
Filename :
4536740
Link To Document :
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