RadKey demonstrates through-wall keystroke inference via RF backscatter tag modulation and LLM-guided classifier adaptation using user-independent time-frequency features.
Eexapp: Gnn- based reinforcement learning for radio unit energy opti- mization in 5g o-ran
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DeRAN converts black-box DRL policies into interpretable symbolic representations for O-RAN automation, retaining 78-87% of original performance while adding built-in transparency.
TARMM uses a temporal graph to model RAN dynamics and MARL with action masking for proactive mobility management in 5G O-RAN, reducing tail latency by up to 44% and packet loss by up to 56% on a multi-cell testbed for VR workloads.
citing papers explorer
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RadKey: An LLM-Guided RF Backscatter System for Through-Wall Keystroke Inference
RadKey demonstrates through-wall keystroke inference via RF backscatter tag modulation and LLM-guided classifier adaptation using user-independent time-frequency features.
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Demystifying Deep Reinforcement Learning: A Neuro-Symbolic Framework for Interpretable Open RAN Automation
DeRAN converts black-box DRL policies into interpretable symbolic representations for O-RAN automation, retaining 78-87% of original performance while adding built-in transparency.
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TARMM: Scaling Delay-Critical Edge AI Offloading in 5G O-RAN via Temporal Graph Mobility Management
TARMM uses a temporal graph to model RAN dynamics and MARL with action masking for proactive mobility management in 5G O-RAN, reducing tail latency by up to 44% and packet loss by up to 56% on a multi-cell testbed for VR workloads.