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Multi-objective optimization for UWB antenna array by APSO algorithm

Author

Listed:
  • Wei Chien

    (Ningde Normal University)

  • Chien-Ching Chiu

    (Tamkang University)

  • Yu-Ting Cheng

    (Tamkang University)

  • Shu-Han Liao

    (Institute for Information Industry)

  • Horng-Shiou Yen

    (Tamkang University)

Abstract

In this paper, a uniform circular antenna array (UCAA) combining genetic algorithm (GA) or asynchronous particle swarm (APSO) for finding out global maximum of multi-objective function in indoor ultra-wideband (UWB) communication system is proposed. The algorithm is used to synthesize the radiation pattern of the directional UCAA to reduce the bit error rate (BER), to increase received energy and channel capacity in indoor UWB communication system. Using the impulse response of multipath channel, the BER of the synthesized antenna pattern on binary antipodal-pulse amplitude modulation system can be calculated. Based on topography of the antenna and the shooting and bouncing ray/image techniques, the synthesized problem can be reformulated into a multi-objective optimization problem which would be solved by the GA and APSO. Numerical results show that the fitness value and convergence speed by APSO is better than those by GA. The results also show that for multi-objective problem APSO compared to GA can reduce the BER substantially. Moreover, APSO can get better results for both line-of-sight and non line-of-sight cases.

Suggested Citation

  • Wei Chien & Chien-Ching Chiu & Yu-Ting Cheng & Shu-Han Liao & Horng-Shiou Yen, 2017. "Multi-objective optimization for UWB antenna array by APSO algorithm," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 64(4), pages 649-660, April.
    • Handle: RePEc:spr:telsys:v:64:y:2017:i:4:d:10.1007_s11235-016-0197-8
    DOI: 10.1007/s11235-016-0197-8
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