5 papers · 1 filter
A Multi-Agent System for 5G Throughput Prediction in Multi-Operator Urban Environments
Muhammad Kabeer, Rosdiadee Nordin, Nadiva Nuriftitah +1
Throughput prediction is foundational for artificial intelligence-driven 6G resource orchestration. Conventional monolithic machine learning models struggle to generalize across di…
A Safety-Constrained Reinforcement Learning Framework for Reliable Wireless Autonomy
Abdikarim Mohamed Ibrahim, Rosdiadee Nordin
Artificial intelligence (AI) and reinforcement learning (RL) have shown significant promise in wireless systems, enabling dynamic spectrum allocation, traffic management, and large…
URLLC for 6G Enabled Industry 5.0: A Taxonomy of Architectures, Cross Layer Techniques, and Time Critical Applications
Abdikarim Mohamed Ibrahim, Rosdiadee Nordin, Yahya S. M. Khamayseh +2
The evolution from Industry 4.0 to Industry 5.0 introduces stringent requirements for ultra reliable low latency communication (URLLC) to support human centric, intelligent, and re…
Sequence-Based Deep Learning for Handover Optimization in Dense Urban Cellular Network
Muhammad Kabeer, Rosdiadee Nordin, Mehran Behjati +1
Efficient handover management remains a critical challenge in dense urban cellular networks, where high cell density, user mobility, and diverse service demands increase the likeli…
An Urban Multi-Operator QoE-Aware Dataset for Cellular Networks in Dense Environments
Muhammad Kabeer, Rosdiadee Nordin, Mehran Behjati +1
Urban cellular networks face complex performance challenges due to high infrastructure density, varied user mobility, and diverse service demands. While several datasets address ne…