This paper introduces a system model called pilot-aided simultaneous communication and localisation (PASCAL) and illustrates its performance in the presence of practical gain and phase imperfections. Specifically, we consider the scenario where multiple single-antenna unmanned aerial vehicles (UAVs) transmit data packets to a multi-antenna base station (BS) that has the dual responsibility of detecting communication signals and localising UAVs using their pilot symbols. Two forms of receiver signal processing approaches are adopted, including disjoint localisation and communication by using maximum likelihood estimation and multiple signal classification (MUSIC), as well as joint localisation and data detection achieved by the newly proposed algorithms. To evaluate the asymptotic localisation performance in the presence of gain-phase imperfections, the Cram\'er-Rao lower bound (CRLB) is derived, while for evaluating the communication's performance, the average sum data rate (SDR) for all the UAVs is derived in closed-form. It is shown that these derived expressions concur with simulations. The results reveal that while the proposed PASCAL system can be sensitive to gain-phase imperfections, it remains to be a powerful and efficient means to achieve reliable simultaneous localisation and communications.

翻译：本文提出了一种称为导频辅助同步通信与定位(PASCAL)的系统模型，并阐述了其在实际增益与相位非理想条件下的性能表现。具体而言，我们考虑多架单天线无人机向多天线基站传输数据包的场景，该基站需同时承担通信信号检测与利用导频符号进行无人机定位的双重任务。研究采用两种接收机信号处理方案：包括基于最大似然估计与多重信号分类(MUSIC)的分离式定位通信方案，以及通过新提出算法实现的联合定位与数据检测方案。为评估存在增益-相位非理想性时的渐近定位性能，本文推导了克拉美-罗下界；针对通信性能评估，则以闭合形式推导了所有无人机的平均总数据速率。研究表明，这些推导表达式与仿真结果高度吻合。结果显示，尽管所提出的PASCAL系统对增益-相位非理想性较为敏感，其仍然是实现可靠同步定位与通信的强大且高效的技术手段。