CC* Integration-Small: M2- NET: An Integrated Access and Backhaul Millimeter-wave Wireless Network for Campus Connectivity and Research

乔治梅森大学是一所多元化的公共研究机构，拥有4万多名学生。该大学的计算组合涵盖了广泛的项目，从沉浸式AR/VR和农业基因组学到视觉、地理定位、公共安全、数字孪生技术和无人机计划。该项目被称为M2-NET（梅森毫米波无线网络），其重点是实现其西校区的高速，强大的连接，西校区是一个潜在的研究和教育中心。该项目将设计、部署和评估多跳毫米波（mmWave）无线基础设施，该基础设施不仅将作为众多研究和开发项目的研究平台，还将使西校区的无线连接成为可能。M2-NET将建立一个独一无二的大型户外毫米波网络和传感基础设施，包括未经许可的毫米波60千兆赫多跳回程、毫米波和6千兆赫以下WiFi接入、开源的6千兆赫以下蜂窝RAN、软件无线电和毫米波雷达传感器。凭借其提供高速低延迟连接、无处不在的传感和端到端协议集成的能力，M2-NET将支持梅森大学不同部门和中心的十多个跨学科研究项目（如沉浸式内容交付、加强毫米波网络的网络安全以及作为第一响应者的无人机）。M2-NET将通过新颖的基于机器学习的传播模型进行部署，该模型专门用于以最小的测量开销建立可靠的毫米波链路，同时采用高吞吐量低延迟拓扑设计，可以提供具有可重构性和敏捷性的有线连接。该基础设施将产生大量无线数据集，这些数据集将与全球研究界公开共享。M2-NET将作为评估和测试毫米波回程网络的范例平台，用于大规模农村/城郊网络部署，以及解决数字鸿沟的潜力。代码库、文档和其他材料将由M2-NET团队维护。项目网站（https://nextgwirelesslab.org/m2-net）将整合与m2-net相关的信息，包括数据集、可用代码、文档和其他相关资源。通过社区生态系统和后续项目，项目存储库/网站维护计划在初始项目时间表之后的几年内进行。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。

George Mason University (Mason) is a diverse public research institution with over 40,000 students. The university's computing portfolio encompasses a wide spectrum of projects, from immersive AR/VR and agro-genomics to vision, geolocation, public safety, digital twin technology, and drone initiatives. The focus of this project, referred to as M2-NET (Mason Millimeter-wave wireless NETwork), is to enable high-speed, robust connectivity to its west campus which is a potential epicenter for research and education. The project will design, deploy, and evaluate a multi-hop millimeter-wave (mmWave) wireless infrastructure that will serve not only as a research platform for a multitude of research and development projects but will also enable wireless connectivity in the west campus. M2-NET will build a one-of-its-kind large-scale, outdoor mmWave networking and sensing infrastructure that will include unlicensed mmWave 60 GHz multi-hop backhaul, mmWave and sub-6 GHz WiFi access, open-source sub-6 GHz cellular RAN, software radios and mmWave radar sensors. With its capability to provide high-speed low-latency connectivity, ubiquitous sensing, and end-to-end protocol integration, M2-NET will support over a dozen interdisciplinary research projects (such as immersive content delivery, hardening cybersecurity for mmWave networks and drones as first responders) across different departments and centers at Mason. M2-NET will be deployed through novel machine learning based propagation models specifically developed for establishing reliable mmWave links with minimal measurement overhead, along with a high-throughput low-latency topology design that can provide wire-like connectivity with reconfigurability and agility. The infrastructure will result in numerous wireless datasets which will be openly shared with the global research community. M2-NET will serve as the exemplar platform for the evaluation and testing of mmWave backhaul networks for large-scale rural/sub-urban networking deployments, and the potential of addressing the digital divide. The code repositories, documentation, and other material will be maintained by the M2-NET team. The project website (https://nextgwirelesslab.org/m2-net) will consolidate the M2-NET-related information, including the datasets, available code, documentation, and other related resources. The project repository/website maintenance is planned for several years beyond the initial project timeline through the community ecosystem and follow-up projects.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.