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A fractional Fourier transform–based channel estimation algorithm in single-carrier direct sequence code division multiple access underwater acoustic communication system

Author

Listed:
  • Lin Zhou
  • Qingsheng Zhao
  • Shukai Chi
  • Yanlong Li
  • Lanjun Liu
  • Qianxiang Yu

Abstract

Due to the complexity and variability of the underwater acoustic channel, the communication signal is affected by multi-path, time delay, and Doppler frequency shift. Based on the advantageous characteristics of fractional Fourier transform on chirp signal processing, a fractional Fourier transform–based algorithm using combined linear frequency–modulated signal is proposed, which can estimate parameters of underwater acoustic channel and has a better performance than the existing methods. To distinguish multi-user in underwater acoustic communication system, a single-carrier direct sequence code division multiple access communication system combined with the fractional Fourier transform–based algorithm is proposed. Thus, a preliminary study on underwater multi-target identification is carried out. The simulation and experimental results show that the fractional Fourier transform–based algorithm is simple and effective, and the energy can be focused at the “best†fractional order, which can directly determine the multi-path number and complete the channel estimation. The proposed single-carrier direct sequence code division multiple access communication system has good performance on bit error rate when we use corresponding spreading code to distinguish multi-user.

Suggested Citation

  • Lin Zhou & Qingsheng Zhao & Shukai Chi & Yanlong Li & Lanjun Liu & Qianxiang Yu, 2019. "A fractional Fourier transform–based channel estimation algorithm in single-carrier direct sequence code division multiple access underwater acoustic communication system," International Journal of Distributed Sensor Networks, , vol. 15(1), pages 15501477198, January.
  • Handle: RePEc:sae:intdis:v:15:y:2019:i:1:p:1550147719826001
    DOI: 10.1177/1550147719826001
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