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NSF

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

Active
Institution
George Mason University, VA
Principal investigator
Parth Pathak
Funding
$500K
Duration
2024–2027
Open portfolio

Moonbase score

Still being scored

Abstract

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.

Research team

  • Parth PathakPI
  • Vijay K ShahFormer PI

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wirelessconnectivitylow-latencyhigh-speedcampusghznetmmwave

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