Guevara Noubir
Northeastern University, MA·Engineering
The radio frequencies that carry wireless signals are a limited resource. Demand for them is soaring from massive Internet of Things (IoT) networks, autonomous cars, robots and augmented reality.
- Fields
Engineering
Computer Science
- Topics
spectrum sharing
wireless security
wireless communications
- Grants
- 1 known grant, through Sep 2028
What they work on
- Analyze threats to spectrum sharing from adversaries who use software-defined radios and machine learning to evade detection, including colluding transmitters.
- Develop radio-frequency machine learning models that sense and classify radio emissions in real time amid collisions and interference, using multiple-antenna signals.
- Create techniques to locate and attribute misbehaving devices despite mimicry and collusion, with built-in privacy guarantees that prevent unlawful tracking of users.
- Design algorithms that tolerate misbehaving devices, building on RF machine learning models for beamforming and interference nulling, and test them in an anechoic chamber and on the Colosseum and POWDER testbeds.
More about the research
Radios are also increasingly built in software. Software-defined radios (SDRs) are now small, cheap and flexible. That flexibility helps engineers share spectrum more efficiently, but it also makes it easier for devices to break the rules or launch attacks on reliability, privacy and security. This project develops ways to prevent, detect, locate and identify misbehaving wireless devices while protecting the privacy of ordinary users.
Why it matters
As wireless demand outgrows the available spectrum, regulators and network operators need ways to enforce sharing rules. This work could help detect and locate interfering or malicious radios without enabling unlawful tracking of users, supporting more reliable networks for IoT devices, autonomous vehicles and other wireless applications. The open datasets and tools could also help other researchers.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Negar Reiskarimian
Massachusetts Institute of Technology, MA·Engineering
Demonstrate a low-power software-defined radio chip that resists harmonic interference, using a fully passive harmonic-reject mixer and a compact clocking scheme with sub-milliwatt static power.
Neal Patwari
Washington University in St Louis, MO·Engineering
Develop RF watermarks that embed random pseudonyms in wireless signals so that passive radio receivers, such as radio telescopes, can identify any interfering transmitter.
Vuk Marojevic
Mississippi State University, MS·Engineering
Build a passive microwave radiometer flown on a drone on the AERPAW testbed to collect the first large active/passive radio coexistence dataset with ground-truth information.
The school
Northeastern University: 27 labs on PI Pages, $347M a year on research, 251 research doctorates a year.
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