This paper considers the problem of downlink localization and user equipments (UEs) tracking with an adaptive procedure for a range of distances. We provide the base station (BS) with two signaling schemes and the UEs with two localization algorithms, assuming far-field (FF) and near-field (NF) conditions, respectively. The proposed schemes employ different beam-sweep patterns, where their compatibility depends on the UE range. Consequently, the FF-NF distinction transcends the traditional definition. Our proposed NF scheme requires beam-focusing on specific spots and more transmissions are required to sweep the area. Instead, the FF scheme assumes distant UEs, and fewer beams are sufficient. We derive a low-complexity algorithm that exploits the FF channel model and highlight its practical benefits and the limitations. Also, we propose an iterative adaptive procedure, where the signaling scheme is depends on the expected accuracy-complexity trade-off. Multiple iterations introduce a tracking application, where the formed trajectory dictates the validity of our assumptions. Moreover, the range from the BS, where the FF signaling scheme can be successfully employed, is investigated. We show that the conventional Fraunhofer distance is not sufficient for adaptive localization and tracking algorithms in the mixed NF and FF environment.

翻译：本文研究了在距离变化条件下，采用自适应过程进行下行链路定位和用户设备（UE）跟踪的问题。我们分别为基站（BS）提供了两种信令方案，并为UE提供了两种定位算法，分别假设远场（FF）和近场（NF）条件。所提方案采用不同的波束扫描模式，其兼容性取决于UE的距离范围。因此，FF与NF的区分超越了传统定义。我们提出的NF方案需要将波束聚焦于特定位置，且需要更多传输次数以完成区域扫描；而FF方案则假设UE距离较远，所需波束数量较少。我们推导了一种利用FF信道模型的低复杂度算法，并突出了其实用优势与局限性。此外，我们提出了一种迭代自适应过程，其中信令方案取决于预期的精度-复杂度权衡。多次迭代引入了跟踪应用场景，所形成的轨迹决定了我们假设的有效性。同时，我们研究了能够成功应用FF信令方案的BS距离范围。结果表明，在混合NF与FF环境中，传统的夫琅禾费距离不足以支持自适应定位与跟踪算法。