Dr. S. Mohammad Razavizadeh - IUST

S. Mohammad Razavizadeh
Associate Professor
School of Electrical Engineering

Iran University of Science & Technology (IUST)

    Email: smrazavi AWT IMAGE iust.ac.ir  Phone: +98 21 7322 5736
  Research interests:
  • Mobile and Cellular Communication Systems
  • Wireless Networks (physical layer)
  • Signal Processing for Wireless Communications
  • Reconfigurable Intelligent Surfaces
  • Massive MIMO Systems
  • Wireless Energy Transfer

 Research Group:

  • Mobile Broadband Networks Research Group (MBNRG)


  • MIMO Systems
  • Advanced topics in wireless communications
  • Convex Optimization
  • Convex Optimization for Wireless Communications
  • Analog Communications Systems (Communication systems I)
  • Signals and Systems

 Selected  journal  papers: 
  • N. Ghiasi, S. Mashhadi, S. Farahmand, S. M. Razavizadeh, and I. Lee, "Energy Efficient AP Selection for Cell-Free Massive MIMO Systems: Deep Reinforcement Learning Approach", in IEEE Transactions on Green Communications and Networking, 2022.  (link)
  • M. Parhizgar and S. M. Razavizadeh, "AN-aided beamforming for IRS-assisted SWIPT systems", in Physical Communication, 2022. (link)
  • A. Mahmoudi, B. Abolhassani, S. M. Razavizadeh, and H. H. Nguyen, "User Clustering and Resource Allocation in Hybrid NOMA-OMA Systems Under Nakagami-m Fading", in IEEE Access, 2022 (link)
  • S. Fatemeh Zamanian, M. H. Kahaei, S. M. Razavizadeh, T. Svensson "Attacking Massive MIMO Cognitive Radio Networks by Optimized Jamming", IEEE Open Journal of the Communications Society, 2021 (link)
  • A. Rafieifar, S. M. Razavizadeh, "Secrecy Rate Maximization in Multi-IRS Millimeter Wave Networks", Elsevier Physical Communication, 2021.   (link)
  • S.F. Zamanian, S. M. Razavizadeh, Q. Wu "Vertical Beamforming in Intelligent Reflecting Surface-Aided Cognitive Radio Networks", IEEE Wireless Communications Letters, 2021.   (link)
  • H. Soltanizadeh, S. Farahmand S. M. Razavizadeh, "Coordinated versus uncoordinated channel tracking for high-rate internet of things in multiuser massive MIMO: Algorithms and performance", Elsevier Signal Processing, 2021.   (link)
  • S. Mashhadi, N. Ghiasi, S. Farahmand, S. M. Razavizadeh, "Deep Reinforcement Learning Based Adaptive Modulation With Outdated CSI", IEEE Communications Letters, 2021.   (link)
Visit the website of the MBNRG to learn more (link)

School of Electrical Engineering, Iran University of Science & Technology (IUST)
Narmak, Tehran 16846-13114, Iran
Fax: +98 21 7322 5777 (Dep.)

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