12 papers
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…
IoT-Driven Building Energy Management Systems (BEMS) for Net Zero Energy Buildings: Concept, Integration and Future Directions
Haizum Hanim Ab Halim, Dalila Alias, Akmal Zaini Arsad +3
Construction and operating of buildings is one of the major contributors to global greenhouse emissions. With the inefficient usage of energy due to human behavior and manual opera…
Large Artificial Intelligence Model Guided Deep Reinforcement Learning for Resource Allocation in Non Terrestrial Networks
Abdikarim Mohamed Ibrahim, Rosdiadee Nordin
Large AI Model (LAM) have been proposed to applications of Non-Terrestrial Networks (NTN), that offer better performance with its great generalization and reduced task specific tra…
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…
Geometry-Aware LoRaWAN Gateway Placement in Dense Urban Cities Using Digital Twins
Abdikarim Mohamed Ibrahim, Rosdiadee Nordin
LoRaWAN deployments rely on rough range estimates or simplified propagation models to decide where to place/mount gateways. As a result, operators have limited visibility into how…
Digital Twin for Ultra-Reliable & Low-Latency 6G Wireless Communications in Dense Urban City
Abdikarim Mohamed Ibrahim, Rosdiadee Nordin
High-frequency deployments in dense cities are difficult to plan because coverage, interference, and service reliability depend sensitively on local morphology. This paper develops…