DocumentCode
2363571
Title
Quantum genetic algorithm based signal detection scheme for MIMO-OFDM system
Author
Li, Fei ; Wang, Wei
Author_Institution
Inst. of Signal Process. & Transm., Nanjing Univ. of Posts & Telecommun., Nanjing, China
Volume
1
fYear
2010
fDate
June 29 2010-July 1 2010
Firstpage
298
Lastpage
301
Abstract
Quantum Genetic Algorithm (QGA) is based on the concept and principles of quantum computing, such as quantum bit and superposition of states. Instead of binary, numeric, or symbolic representation, QGA uses a Q-bit, defined as the smallest unit of information, for the probabilistic representation and a Q-bit individual as a string of Q-bits. A Q-gate is introduced as a variation operator to drive the individuals toward better solutions. A novel signal detector based on QGA for MIMO-OFDM system is proposed. An analysis is given to the theoretical basis and practical performance of the proposed detector. The simulation results show that the proposed detector has more powerful properties in bit error rate than conventional Genetic Algorithm (GA) based detector and Vertical Bell Layered Space Time (VBLAST) algorithm based detector. The performance of the proposed detector is closer to optimal, compared with the other detectors. The results demonstrated the effectiveness and the applicability of QGA in signal detection for MIMO-OFDM system.
Keywords
MIMO communication; OFDM modulation; genetic algorithms; quantum communication; signal detection; MIMO-OFDM system; VBLAST algorithm; quantum computing; quantum genetic algorithm; signal detection; symbolic representation; vertical bell layered space time algorithm; Detectors; Multiplexing; Multi-Input Multi-Output; Orthogonal Frequency Division Multiplexing; Quantum Genetic Algorithm; Signal Detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Communication Systems, Networks and Applications (ICCSNA), 2010 Second International Conference on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-7475-2
Type
conf
DOI
10.1109/ICCSNA.2010.5588723
Filename
5588723
Link To Document