01Load balancing
Put capacity where it is needed.
I examine how reinforcement learning can optimize cell association and resource allocation when demand shifts and network observations are uncertain.
RESEARCH DIRECTION 02
Intelligent Radio
Access Networks.
Research background
My research in Artificial Intelligence for Radio Access Networks (AIRAN) focuses on using reinforcement learning and intelligent control to make wireless networks a little better at making decisions on their own. This work began with my undergraduate thesis at Iran University of Science and Technology (IUST), supervised by Dr. Hossein Soleimani, where I studied deep reinforcement learning for QoS-aware load balancing in 5G cellular networks under user mobility and uncertain channel conditions. Since then, my work has expanded into AI based coverage optimization, resource management, mobility, and multi-agent wireless systems. The broader goal is simple: help 5G and future 6G networks adapt to changing conditions without needing a human to babysit every decision.
Research focus
02Mobility management
Adapt to movement without losing stability.
I study policies that anticipate handovers and changing network pressure while balancing service quality, efficiency, and continuity.