Collaborative Research:CISE-MSI:DP:CNS:Adaptive Multi-Tiered, Multi-Task Base Station Infrastructure For Communication-Denied Environments

如今，蜂窝网络已经成为卓越的通信技术，主要是由于它们对现代社会的深远影响。5G及更高版本提供了独特的特性，如高传输速率、超可靠的低延迟通信、大规模机器类型通信以及边缘和云计算。然而，这些网络的性能可能容易受到需求波动或由于自然或人为灾害对底层基础设施（即地面基台）造成无法预料的物理破坏的影响。人工智能、控制系统和网络物理系统领域自治的最新进展促进了自主无人机（uav）和自主车辆的利用，以建立临时蜂窝网络。这些网络依赖于飞行基站（FBSs）或车载基站（VBS），在大规模灾害或事件中，tbs要么不可用，要么无法提供所需的覆盖和服务质量（QoS）。除了通信服务，这些自动驾驶汽车还可以提供多种功能，包括快速绘制广阔区域、在危险区域作业、紧急交付和搜救任务。然而，尽管迄今为止在概念、科学和工程方面取得了进步，但FBS和VBS基础设施尚未达到完全成熟。该项目的主要目标是开发一个自适应、多目标、多层和多任务的基础设施，包括空中和车载基站（MTBS）。目标是提高蜂窝系统的覆盖范围和服务质量，同时促进各种服务，包括态势感知、包裹递送和目标跟踪，特别是在可用车辆数量有限的情况下。研究和教育议程围绕三个重点进行：(1)进行基础研究，旨在开发模型和算法工具，用于开发和实施自适应的多层无人机和VBSs集合，以在具有挑战性的环境中提供通信基础设施，例如在灾区；(2)开发MTBS系统的轨迹规划模型，为在少量车辆可用的关键任务中有效利用基站提供现实的解决方案；(3)利用试验台环境对所提模型的性能进行评估。在这个项目中开发的测试平台和开源代码包将允许教育工作者和领域专业人员在学习和培训环境中部署它们。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Nowadays, cellular networks have emerged as the preeminent communication technology, primarily due to their profound impact on modern society. 5G and beyond offer distinctive features, such as high transmission rate, ultra-reliable low-latency communication, massive machine-type communication, and edge and cloud computing. Nevertheless, the performance of these networks can be susceptible to fluctuations in demand or unanticipated physical damage to the underlying infrastructure - i.e., terrestrial base stations (TBSs) - through natural or man-made disasters. Recent advancements in artificial intelligence, control systems, and autonomy within the realm of cyber-physical systems have facilitated the utilization of autonomous unmanned aerial vehicles (UAVs) and autonomous vehicles to establish temporary cellular networks. These networks rely on flying base stations (FBSs) or vehicular base stations (VBS) in large-scale disasters or events where TBSs are either unavailable or unable to provide the required coverage and quality of service (QoS). In addition to their communication services, these autonomous vehicles can offer diverse functionalities, including rapid mapping of expansive areas, operations in hazardous zones, emergency deliveries, and search-and-rescue missions. However, despite the conceptual, scientific, and engineering advancements achieved thus far, the FBS and VBS infrastructures have not yet reached their full maturity.The principal objective of this project is to develop an adaptive, multi-objective, multitier, and multi-task infrastructure consisting of aerial and vehicular base stations (MTBS). The aim is to improve the coverage and QoS of cellular systems while simultaneously facilitating various services, including situational awareness, package delivery, and target tracking, particularly in scenarios where the number of available vehicles is limited. The research and education agenda is framed around three thrusts: (1) performing fundamental research aimed at developing models and algorithmic tools for developing and implementing an adaptive, multi-tiered collection of UAVs and VBSs, to provide communication infrastructure in challenging environments, such as in a disaster zone; (2) developing trajectory-planning models in MTBS systems to deliver a realistic solution for effectively utilizing the base stations in critical missions wherein a small number of vehicles are available; and (3) evaluating the performance of the proposed models using testbed environments. The testbed and open-source code packages developed in this project will allow educators and field professionals to deploy them in both learning and training environments.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.