Erfan Rasti
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    • A User-Centric Energy-Saving Method for Dynamic 5G Heterogeneous Networks Using Deep Reinforcement Learning
  • Projects
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    • A User-Centric Energy-Saving Method for Dynamic 5G Heterogeneous Networks Using Deep Reinforcement Learning
    • Access Point Location Determination in Cell-Free Massive MIMO Networks
    • Access Point Selection techniques in Cell-Free Massive MIMO Networks
    • Ecotourism Recommender System Based on Machine Learning
    • MRI and CT-Scan Image Classification and Clustering using Deep Learning
    • Reconfigurable Intelligent Surface Assisted Multiuser MISO Systems

Reconfigurable Intelligent Surface Assisted Multiuser MISO Systems

Oct 20, 2025 · 1 min read
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In this project, we tune the angle of RIS elements to maximize the total throughput of the network using a deep reinforcement learning model.

Last updated on Oct 20, 2025
Cell-FreeMasssiveMIMO RIS IRS DRL
Erfan Rasti
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Erfan Rasti (he/him)
Communication Engineer
← MRI and CT-Scan Image Classification and Clustering using Deep Learning Oct 20, 2025

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