RayNet: A Full-Stack Programmable Experimental Testbed to Support Research in Extremely Heterogeneous Networks

Abstract

Extremely heterogeneous networks (xHetNets) are emerging as a new paradigm to connect the increasingly diverse wireless devices in both civil and tactical scenarios. In particular, the xHetNets which tightly integrate millimeter-wave (mmWave) and sub-6 GHz radio interfaces have witnessed a prominent growth in recent years. Whereas mmWave wireless links can easily provision ultra-broadband capacity owing to the massive spectrum resources, they suffer from significantly higher attenuation loss, and have to rely on directional, electronically steerable beams to compensate for the pathloss. Such flexible and directional links in turn raise new challenges and opportunities in network architecture, protocols, and security, especially when coupled with the omnidirectional low-frequency links. The exploration of such challenges entails a flexible experimental testbed which allows full control and monitoring across the wireless network stack. Yet no such xHetNet testbed exists that comprises programmable heterogeneous radios and allows experimentation at moderate scale. This DURIP proposal aims to fill the gap by establishing a 20-node xHetNet testbed called RayNet. The testbed comprises a mix of static, UAV-mounted, and ground robot nodes, to emulate a tactical mesh network deployment. Each node integrates a sub-6 GHz software radio and a low-cost but powerful mmWave software radio that the PI recently developed. The mmWave software radio supports up to 256 antenna elements, forming 128 beam patterns with real-time programmability. The software radios enable RayNet to become the first xHetNet testbed with full-stack programmability. RayNet will be used to facilitate 4 ongoing research projects involving 5 PIs in the DoD Center for Networked and Configurable Command, Control and Communications (NC4) along with collaborators in ARL. It will also enable a wide spectrum of DoD-relevant future research topics, ranging from networked command-and-control algorithms, resource allocation and interference management for directional mmWave links, AI-driven dynamic routing and 3D topology adaptation for UAV-based xHetNet, transport layer for aggregation of heterogeneous network paths, all the way up to network security and applications. Through RayNet, the PI team will formulate experiment-centric tasks to attract and train student researchers. The RayNet testbed will be operated continuously for at least 10 years and will be sustained through federal grants and community support. ITAR statement: UCSD intends to perform this work as unclassified, fundamental research as defined by National Security Decision Directive (NSDD) 189 and the Export Control regulations. As such, there should be no limitation on the freedom to publish or handle research results or data, nor restrictions on the citizenship or national origin of those performing the research.

Document Details

Document Type
DoD Grant Award
Publication Date
Sep 01, 2023
Source ID
W911NF2310378

Entities

People

  • Xinyu Zhang

Organizations

  • Army Contracting Command
  • United States Army
  • University of California, San Diego

Tags

Fields of Study

  • Computer science

Readers

  • Computer Networking
  • Government and Public Administration Law.

Technology Areas

  • 5G
  • 5G - Internet of Things
  • AI & ML
  • AI & ML - DoD AI Strategy
  • Autonomy
  • Autonomy - Autonomous System Control
  • Cyber
  • Cyber - Quantum
  • Fully Networked C3
  • Fully Networked C3 - Command and Control
  • Microelectronics
  • Microelectronics - Microelectromechanical Systems