Connected Automated Vehicles (CAV) is a promising application for connected vehicles. However, in the automatic driving scenario, the sensor blind area will lead to serious security risks, and the existing vehicle-to-vehicle technology is difficult to break through the sensor blind area and ensure the reliability of the perceptual information. To overcome these problems, based on Integrated sensing and communication (ISAC) technology, it is feasible to treat infrastructure as a means to extend the sensing range. The base station transmits a number of beams, including a sensing beam and a communication beam. The sensing beam is responsible for sensing the target in the sensing blind area, and the communication beam is responsible for transmitting the sensed information to the CAV. However, there may be interference in the transmission process. In this paper, the beamforming algorithm of communication beam and sensing beam is designed to reduce the interference, and the communication signal-to-noise ratio (SINR) at the autonomous vehicle and the sensing signal-to-noise ratio (SNR) returned at the base station are guaranteed.

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ISAC Beamforming in Connected Autonomous Vehicles

  • Jian Zhang,
  • Chenguang He,
  • Weixiao Meng,
  • Yuchuan Ma

摘要

Connected Automated Vehicles (CAV) is a promising application for connected vehicles. However, in the automatic driving scenario, the sensor blind area will lead to serious security risks, and the existing vehicle-to-vehicle technology is difficult to break through the sensor blind area and ensure the reliability of the perceptual information. To overcome these problems, based on Integrated sensing and communication (ISAC) technology, it is feasible to treat infrastructure as a means to extend the sensing range. The base station transmits a number of beams, including a sensing beam and a communication beam. The sensing beam is responsible for sensing the target in the sensing blind area, and the communication beam is responsible for transmitting the sensed information to the CAV. However, there may be interference in the transmission process. In this paper, the beamforming algorithm of communication beam and sensing beam is designed to reduce the interference, and the communication signal-to-noise ratio (SINR) at the autonomous vehicle and the sensing signal-to-noise ratio (SNR) returned at the base station are guaranteed.