在移动代理的互联网中进行定位：一种线性方法
Localization in internets of mobile agents: A linear approach
AI总结：
本文提出一种分布式定位方法，用于5G环境中的移动设备定位，通过局部测量和计算实现线性解，避免传统集中式方案的高密度锚点部署需求。
摘要：
第五代网络提供更高的带宽和更快的数据速率，将连接大量静态和移动设备、传感器、代理、用户、机器和车辆，支持物联网和实时动态移动网络。定位和位置感知将变得越来越重要，有助于部署新服务并显著提高5G系统性能。许多目前讨论的5G定位解决方案是集中式的，通常需要同时直接视线（LoS）到部署的接入节点或锚点，这又需要高密度的锚点部署。但这些LoS和集中式定位解决方案在用户和设备数量无限增长时可能变得难以管理。作为集中式解决方案的替代，本文讨论了在5G启用的物联网环境中分布式定位，其中许多低功耗设备、用户或代理能够自身定位，而无需全局或LoS访问锚点。尽管定位本质上是非线性问题（通过三角测量或三角化求解圆方程），我们讨论了一种协作的线性分布式迭代解，仅需每个代理的局部测量、通信和计算。线性通过重新参数化代理位置，基于局部邻域几何的重心坐标表示，可能通过涉及相对局部代理距离测量的某些凯莱-梅纳定理来计算。
英文摘要：
Fifth generation~(5G) networks providing much higher bandwidth and faster data rates will allow connecting vast number of static and mobile devices, sensors, agents, users, machines, and vehicles, supporting Internet-of-Things (IoT), real-time dynamic networks of mobile things. Positioning and location awareness will become increasingly important, enabling deployment of new services and contributing to significantly improving the overall performance of the 5G~system. Many of the currently talked about solutions to positioning in~5G are centralized, mostly requiring direct line-of-sight (LoS) to deployed access nodes or anchors at the same time, which in turn requires high-density deployments of anchors. But these LoS and centralized positioning solutions may become unwieldy as the number of users and devices continues to grow without limit in sight. As an alternative to the centralized solutions, this paper discusses distributed localization in a 5G enabled IoT environment where many low power devices, users, or agents are to locate themselves without global or LoS access to anchors. Even though positioning is essentially a non-linear problem (solving circle equations by trilateration or triangulation), we discuss a cooperative \textit{linear} distributed iterative solution with only local measurements, communication and computation needed at each agent. Linearity is obtained by reparametrization of the agent location through barycentric coordinate representations based on local neighborhood geometry that may be computed in terms of certain Cayley-Menger determinants involving relative local inter-agent distance measurements.
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。
