7 papers
ORAN-DEFEND: Subspace Detection and Sanitization of Backdoor DRL xApps in Open RAN
Md Raihan Uddin, Fatemeh Lotfi, Tolunay Seyfi +1
Open Radio Access Networks (O-RAN) increasingly delegate near-real-time control to deep reinforcement learning (DRL) xApps obtained from third-party vendors, creating a new supply-…
SAMPLe: SAM-based Optimizer for Prompt Learning in VLMs
Hossein Rajoli, Fatemeh Lotfi, Niloufar Alipour Talemi +3
Pre-trained Vision-Language Models (VLMs) like CLIP have proven highly effective as foundation models for various downstream applications. However, prompt learning in VLMs encounte…
Meta Hierarchical Reinforcement Learning for Scalable Resource Management in O-RAN
Fatemeh Lotfi, Fatemeh Afghah
The increasing complexity of modern applications demands wireless networks capable of real time adaptability and efficient resource management. The Open Radio Access Network (O-RAN…
Task Specific Sharpness Aware O-RAN Resource Management using Multi Agent Reinforcement Learning
Fatemeh Lotfi, Hossein Rajoli, Fatemeh Afghah
Next-generation networks utilize the Open Radio Access Network (O-RAN) architecture to enable dynamic resource management, facilitated by the RAN Intelligent Controller (RIC). Whil…
ORAN-GUIDE: RAG-Driven Prompt Learning for LLM-Augmented Reinforcement Learning in O-RAN Network Slicing
Fatemeh Lotfi, Hossein Rajoli, Fatemeh Afghah
Advanced wireless networks must support highly dynamic and heterogeneous service demands. Open Radio Access Network (O-RAN) architecture enables this flexibility by adopting modula…
Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing
Fatemeh Lotfi, Hossein Rajoli, Fatemeh Afghah
Modern wireless networks must adapt to dynamic conditions while efficiently managing diverse service demands. Traditional deep reinforcement learning (DRL) struggles in these envir…