DocumentCode :
3321203
Title :
Genetic algorithm implementation of multi-user detection in SDMA-OFDM systems
Author :
Alansi, Mohammed ; Elshafiey, Ibrahim ; Al-Sanie, A.
Author_Institution :
Electr. Eng. Dept., King Saud Univ., Riyadh, Saudi Arabia
fYear :
2011
fDate :
14-17 Dec. 2011
Firstpage :
316
Lastpage :
320
Abstract :
Number of supported users in the orthogonal frequency division multiplexing (OFDM) systems can be increased considerably using powerful multi-user detector (MUD) combined with space division multiple access (SDMA) techniques. This paper presents the results of implementing MUD in SDMA-OFDM systems based on an advanced genetic-algorithm (GA) optimization tool. The hardware implementation is performed using Field Programmable Gate array (FPGA) devices which allow the real time performance of the proposed tool. Results show that the GA scheme enhances the performance and provides BER near to that attained using maximum likelihood (ML) detector at considerably lower computation complexity. Investigation of the GA population size is presented and FPGA implementation is described based on the shared memory approach.
Keywords :
OFDM modulation; computational complexity; error statistics; field programmable gate arrays; genetic algorithms; maximum likelihood detection; multiuser detection; space division multiple access; BER; FPGA devices; MUD; SDMA-OFDM systems; advanced genetic-algorithm optimization tool; computational complexity; field programmable gate array; maximum likelihood detector; multiuser detection; orthogonal frequency division multiplexing system; shared memory approach; space division multiple access techniques; Arrays; Bandwidth; Genetic algorithms; Multiaccess communication; Multiuser detection; OFDM; FPGA; Genetic Algorithms; Multi-User Detection; SDMA; Shared Memory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing and Information Technology (ISSPIT), 2011 IEEE International Symposium on
Conference_Location :
Bilbao
Print_ISBN :
978-1-4673-0752-9
Electronic_ISBN :
978-1-4673-0751-2
Type :
conf
DOI :
10.1109/ISSPIT.2011.6151580
Filename :
6151580
Link To Document :
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