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eess.SP2026

Minimizing Energy Consumption based on Waste Factor in Multi-user Multi-relay Systems

Nurullah Sevim, Mostafa Ibrahim, Sabit Ekin +1

The escalating energy demands of modern wireless networks make energy-efficient system design a central challenge for future 6G deployments. Relay-assisted communication has long b…

eess.SY2026

Quantifying the Reality Gap for RL-Based UAV Placement at mmWave and Sub-THz

Abdullateef Almohamad, Mostafa Ibrahim, Sabit Ekin +1

Reinforcement learning (RL) policies for unmanned aerial vehicle (UAV) placement in mmWave and sub-terahertz networks are typically trained on simplified analytical channels. We qu…

cs.AI2026

Bypassing the CSI Bottleneck: MARL-Driven Spatial Control for Reflector Arrays

Hieu Le, Oguz Bedir, Mostafa Ibrahim +2

Reconfigurable Intelligent Surfaces (RIS) are pivotal for next-generation smart radio environments, yet their practical deployment is severely bottlenecked by the intractable compu…

cs.AI2026

Learning to Focus: CSI-Free Hierarchical MARL for Reconfigurable Reflectors

Hieu Le, Mostafa Ibrahim, Oguz Bedir +2

Reconfigurable Intelligent Surfaces (RIS) have the potential to engineer smart radio environments for next-generation millimeter-wave (mmWave) networks. However, the prohibitive co…

cs.LG2026

Learning to Reflect: Hierarchical Multi-Agent Reinforcement Learning for CSI-Free mmWave Beam-Focusing

Hieu Le, Oguz Bedir, Mostafa Ibrahim +2

Reconfigurable Intelligent Surfaces promise to transform wireless environments, yet practical deployment is hindered by the prohibitive overhead of Channel State Information (CSI)…