11 papers
Learned Neighbor Trust for Collaborative Deployment in Model-Agnostic Decentralized Learning
Michael Lanier, Luise Ge, Sastry Kompella +1
Many decentralized distillation methods are designed around training-time coordination, yet deploy each node in isolation even when more capable neighbors remain available at infer…
How to Discover Knowledge for FutureG: Contextual RAG and LLM Prompting for O-RAN
Nathan Conger, Nathan Scollar, Kemal Davaslioglu +2
We present a retrieval-augmented question answering framework for 5G/6G networks, where the Open Radio Access Network (O-RAN) has become central to disaggregated, virtualized, and…
Coordinated Anti-Jamming Resilience in Swarm Networks via Multi-Agent Reinforcement Learning
Bahman Abolhassani, Tugba Erpek, Kemal Davaslioglu +2
Reactive jammers pose a severe security threat to robotic-swarm networks by selectively disrupting inter-agent communications and undermining formation integrity and mission succes…
Targeted Attacks and Defenses for Distributed Federated Learning in Vehicular Networks
Utku Demir, Tugba Erpek, Yalin E. Sagduyu +2
In emerging networked systems, mobile edge devices such as ground vehicles and unmanned aerial system (UAS) swarms collectively aggregate vast amounts of data to make machine learn…
How to Combat Reactive and Dynamic Jamming Attacks with Reinforcement Learning
Yalin E. Sagduyu, Tugba Erpek, Kemal Davaslioglu +1
This paper studies the problem of mitigating reactive jamming, where a jammer adopts a dynamic policy of selecting channels and sensing thresholds to detect and jam ongoing transmi…
MULTI-SCOUT: Multistatic Integrated Sensing and Communications in 5G and Beyond for Moving Target Detection, Positioning, and Tracking
Yalin E. Sagduyu, Kemal Davaslioglu, Tugba Erpek +3
This paper presents a complete signal-processing chain for multistatic integrated sensing and communications (ISAC) using 5G Positioning Reference Signal (PRS). We consider a distr…