A research team at the University of Ottawa has developed an advanced artificial intelligence system designed to autonomously defend wireless networks from jamming attacks, operating much like a digital immune system. This technology can automatically detect and respond to jamming in real time, which could play a critical role in securing Canada's communications infrastructure.
The research, led by uOttawa's Smart Connected Vehicles Innovation Centre and NEXTCON Lab , introduces a dual-agent AI framework that learns to predict interference events and make real-time decisions to maintain essential communications during attacks. The system significantly reduces disruptions to wireless services that Canadians rely on daily, from emergency response to healthcare, transportation, and smart city applications.
Dual AI agents provide real-time network defense
"We developed a system that allows wireless networks to remain reliable even when targeted by jamming attacks," says Professor Burak Kantarci , uOttawa's Research Chair in AI-Enabled Secure Networking for Smart Critical Infrastructures and Director of the Smart Connected Vehicles Innovation Centre. " Our approach, which uses two cooperating AI agents that learn and adapt continuously, allows for real-time prediction and mitigation of jamming threats, ensuring the reliability of critical services. We're moving towards networks that are autonomously self-protecting, a necessity for Canada's security and infrastructure."
The research, conducted between 2023 and 2025, was carried out by PhD student Ghazal Asemian and research associate Dr. Iman Amini (Mohammadreza Amini), alongside a team of graduate researchers specializing in secure, intelligent wireless systems. The project was delivered in collaboration with thinkRF , a Canadian spectrum-intelligence company.
Strengthening Canada's sovereign digital infrastructure
The AI-based system operates within Mobile Edge Computing and O-RAN environments, where two learning agents work cooperatively to recognize jamming patterns and schedule network tasks safely during interference. Through controlled testing scenarios, the system demonstrated robust resilience and rapid response capabilities under various wireless conditions.
"Resilient wireless systems increasingly depend on autonomous, AI-driven detection and response to interference, enabling practical and scalable spectrum intelligence," says Cliff Ellement, Head of AI Solutions and Product Management at thinkRF.
"Jamming attacks can disrupt critical services with little effort," adds Professor Kantarci. "Our research provides a step toward wireless networks that can automatically detect interference and defend themselves. This strengthens Canada's sovereign digital infrastructure and improves the safety and reliability of systems that Canadians increasingly depend on."
This work reflects Professor Kantarci's lab's ongoing commitment to advancing secure digital infrastructure and sovereign spectrum intelligence capabilities in Canada.
The study, titled " Anti-Jamming Task Scheduling in MEC-O-RAN with Hierarchical DRL and Transformer-Based Control ", was published in IEEE Internet of Things Journal .
