• 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