基于自主车辆运动预测的毫米波链路波束对准
Beam Alignment for Millimetre Wave Links with Motion Prediction of Autonomous Vehicles
摘要：
智能交通系统（ITS）需要超低的端到端延迟和每秒数千兆位的数据传输。毫米波（mmWave）通信可以满足这些要求。然而，互联和自动驾驶车辆（CAV）的移动性增加，需要频繁的波束成形-从而引入增加的开销。本文提出了一种新的波束形成算法，能够实现无开销的波束形成训练。利用CAV传感器数据，通过专用短程通信（DSRC）信标广播，可以估计CAV的位置和运动，并相应地进行波束成形。为了最大限度地减少位置误差，提出了不同的误差分量的分析。通过调整天线波束宽度以适应位置误差，进一步提高了网络性能。我们的算法优于传统的IEEE 802.11ad的方法证明它是一个可行的解决方案，为未来的ITS应用和服务。
英文摘要：
Intelligent Transportation Systems (ITSs) require ultra-low end-to-end delays and multi-gigabit-per-second data transmission. Millimetre Waves (mmWaves) communications can fulfil these requirements. However, the increased mobility of Connected and Autonomous Vehicles (CAVs), requires frequent beamforming - thus introducing increased overhead. In this paper, a new beamforming algorithm is proposed able to achieve overhead-free beamforming training. Leveraging from the CAVs sensory data, broadcast with Dedicated Short Range Communications (DSRC) beacons, the position and the motion of a CAV can be estimated and beamform accordingly. To minimise the position errors, an analysis of the distinct error components was presented. The network performance is further enhanced by adapting the antenna beamwidth with respect to the position error. Our algorithm outperforms the legacy IEEE 802.11ad approach proving it a viable solution for the future ITS applications and services.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
