• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
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  • Chinese S&T Journal Citation Reports
  • Chinese Science Citation Database
Volume 59 Issue 4
Jul.  2024
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Article Contents
YE Qibin, XIAO Hongyu, TIAN Chen, LIU Ming, FU Yunlin, HU Su. Self-Interference Cancellation Technology of Integrated Sensing and Communications System for Unmanned Aerial Vehicles[J]. Journal of Southwest Jiaotong University, 2024, 59(4): 925-932. doi: 10.3969/j.issn.0258-2724.20230599
Citation: YE Qibin, XIAO Hongyu, TIAN Chen, LIU Ming, FU Yunlin, HU Su. Self-Interference Cancellation Technology of Integrated Sensing and Communications System for Unmanned Aerial Vehicles[J]. Journal of Southwest Jiaotong University, 2024, 59(4): 925-932. doi: 10.3969/j.issn.0258-2724.20230599

Self-Interference Cancellation Technology of Integrated Sensing and Communications System for Unmanned Aerial Vehicles

doi: 10.3969/j.issn.0258-2724.20230599
  • Received Date: 10 Nov 2023
  • Rev Recd Date: 11 Jan 2024
  • Available Online: 23 May 2024
  • Publish Date: 18 Jan 2024
  • In the communication scenario of unmanned aerial vehicles (UAVs), the airborne integrated sensing and communications (ISAC) system is affected by the strong self-interference caused by local signal transmission, which degrades the sensing performance of the system to the target. To solve this issue, a self-interference cancellation technology of the ISAC system based on orthogonal frequency division multiplexing (OFDM) was proposed. Firstly, the echo model of the ISAC system based on OFDM was established, and a self-interference signal was introduced. Then, the channel gain of the self-interference signal was estimated by the least squares algorithm, and the self-interference signal was reconstructed and suppressed by the gain. Finally, the effectiveness of the proposed method was verified by simulation experiments in the communication scenario of UAVs. The results show that the proposed method can suppress the self-interference signal to the noise power level and increase the signal-to-interference plus noise ratio (SINR) of the target echo signal by nearly 10.00 dB, so as to effectively improve the sensing performance of the system.

     

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