无人机传感与通信集成网络波束形成与轨迹联合设计

Ying Ju, Yulong Tu, Tongxing Zheng, Lei Liu, Qingqi Pei, Arpit Bhardwaj, K. Yu
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引用次数: 0

摘要

无人机辅助网络因其给无线通信带来的高灵活性和高可靠性而备受关注。本文设计了一种无人机辅助网络的集成传感与通信(ISAC)方案,实现了通信与传感的互惠互利,即无人机在飞行过程中探测多个地面目标,同时与大量地面用户通信。在信噪比(SINR)、发射功率和飞行速度约束下,共同优化了无人机的波束形成和轨迹,以实现高波束增益。为了解决公式化的多元非凸优化问题,提出了一种基于黎曼共轭梯度(RCG)的交替优化算法。数值结果表明,该方法在保证通信质量的前提下,有效地提高了传感性能,且计算复杂度低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Joint design of beamforming and trajectory for integrated sensing and communication drone networks
Drone-aided network has drawn a significant attention due to the high flexibility and reliability it can bring to the wireless communications. In this paper, we design an integrated sensing and communication (ISAC) scheme for a drone-aided network to achieve mutual benefit of communication and sensing, where the drone detects several ground targets while communicating with a large number of ground users during the flight. We jointly optimize the beamforming and trajectory of the drone for achieving high beam gain subject to the signal to interference plus noise ratio (SINR), the transmit power and the flight speed constraints. To solve the formulated multivariate non-convex optimization problem, we propose an alternating optimization algorithm based on the Riemannian conjugate gradient (RCG). Numerical results show that the proposed method can effectively improve the sensing performance while ensuring the communication quality, and has a low computational complexity.
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