标题： 基于CP-OFDM的多目标场景中长程感知与通信集成研究 显示英文标题

标题： Integrated Long-range Sensing and Communications in Multi Target Scenarios using CP-OFDM

摘要： 6G通信系统通过利用正交频分复用（OFDM）通信信号实现感知功能，承诺提供感知能力。然而，OFDM系统固有的循环前缀限制了感知范围，需要补偿技术来检测小而远的目标，例如无人机。 在本文中，我们表明最先进的相干补偿方法在涉及多个目标的场景中失败，导致雷达图像中的噪声基底增加。 我们的贡献包括一种新的多目标相干补偿算法和用于评估多目标性能的广义信干噪比。我们的算法在长距离上实现了与经典OFDM雷达处理相同的检测性能，但仅需3.6%的射频资源。 这使得在具有传统通信网络的多目标场景中能够高效地进行长距离感知。 显示英文摘要

摘要： 6G communication systems promise to deliver sensing capabilities by utilizing the orthogonal frequency division multiplexing (OFDM) communication signal for sensing. However, the cyclic prefix inherent in OFDM systems limits the sensing range, necessitating compensation techniques to detect small, distant targets like drones. In this paper, we show that state-of-the-art coherent compensation methods fail in scenarios involving multiple targets, resulting in an increased noise floor in the radar image. Our contributions include a novel multi target coherent compensation algorithm and a generalized signal-to-interference-and-noise ratio for multiple targets to evaluate the performance. Our algorithm achieves the same detection performance at long distances requiring only 3.6% of the radio resources compared to classical OFDM radar processing. This enables resource efficient sensing at long distances in multi target scenarios with legacy communications-only networks.