Mobile Broadband Network Research Group — School of Electrical Engineering, IUST فارسی

MBNRG

Mobile Broadband Network Research Group
What we work on

Research

MBNRG’s work spans the physical and network layers of broadband mobile systems — from antenna arrays and reflecting surfaces to resource allocation, security and aerial networking.

General topics

Keyword cloud

Mobile & CellularOptimizationMIMOCommunications TheoryRISSignal ProcessingIABSWIPTmMIMOWireless5GUAVPhysical LayerCell-FreeSecurityIRSBeamformingDeep Learning
Focus areas

Research directions

Cell-Free Massive MIMO

Distributed access points jointly serve users without traditional cell boundaries. The group works on access-point selection, downlink/uplink power control, integrated access & backhaul (IAB), and deep-reinforcement-learning-based resource allocation for cell-free deployments.

  • A. H. Jazi, S. M. Razavizadeh and T. Svensson, "Integrated Access and Backhaul (IAB) in Cell-Free Massive MIMO Systems," IEEE Access, 2023. [link]
  • 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," IEEE Trans. Green Commun. Netw., 2022. [link]
  • A. Izadi, S. M. Razavizadeh and O. Saatlou, "Power Allocation for Downlink Training in Cell-Free Massive MIMO Networks," IST 2020. [link]

Reconfigurable Intelligent Surfaces (RIS / IRS)

Passive, software-controlled reflecting surfaces that reshape the propagation environment. MBNRG develops secure and 3D/vertical beamforming algorithms, and energy-efficient optimization models for RIS-assisted cognitive-radio, SWIPT and mmWave links.

  • A. Rafieifar, H. Ahmadinejad, S. M. Razavizadeh and J. He, "Secure Beamforming in Multi-User Multi-IRS Millimeter Wave Systems," IEEE Trans. Wireless Commun., 2023. [link]
  • S. F. Zamanian and S. M. Razavizadeh, "3D Beamforming in IRS-assisted Multi-user Cognitive Radio Networks," Physical Communication, 2022. [link]
  • S. F. Zamanian, S. M. Razavizadeh and Q. Wu, "Vertical Beamforming in Intelligent Reflecting Surface-Aided Cognitive Radio Networks," IEEE Wireless Commun. Lett., 2021. [link]
  • M. Parhizgar and S. M. Razavizadeh, "AN-aided Beamforming for IRS-assisted SWIPT Systems," Physical Communication, 2022. [link]
  • A. Rafieifar and S. M. Razavizadeh, "Secrecy Rate Maximization in Multi-IRS mmWave Networks," Physical Communication, 2021. [link]

Integrated Access and Backhaul (IAB)

Using the same spectrum and infrastructure for both wireless access and backhaul to densify networks cost-effectively — extended by the group to cell-free and non-terrestrial architectures.

  • A. H. Jazi, S. M. Razavizadeh and T. Svensson, "Integrated Access and Backhaul (IAB) in Cell-Free Massive MIMO Systems," IEEE Access, 2023. [link]

UAV Wireless Communication Networks

Unmanned aerial vehicles acting as flying base stations or relays. Current work covers trajectory optimization, spectrum sharing, IRS-assisted UAV links and integrated sensing & communication (ISAC) for aerial platforms as part of 6G non-terrestrial networks.

  • Representative publications coming soon — see the Publications page for the group’s full output in this direction.

Physical Layer Security & Jamming

Detecting and defeating smart jammers, and using artificial noise / secrecy-rate optimization to protect massive MIMO, IRS-assisted and NOMA systems against eavesdropping and interference attacks.

  • H. Akhlaghpasand, E. Björnson and S. M. Razavizadeh, "Jamming-Robust Uplink Transmission for Spatially Correlated Massive MIMO Systems," IEEE Trans. Commun., 2020. [link]
  • A. Sheikhi, S. M. Razavizadeh and I. Lee, "A Comparison of TDD and FDD Massive MIMO Systems Against Smart Jamming," IEEE Access, 2020. [link]

5G / 6G, NOMA & IoT Resource Allocation

Sum-rate and energy-efficiency optimization for NOMA, wireless-powered IoT, and channel-aging-aware massive MIMO systems in next-generation cellular networks.

  • S. Khavari, S. Farahmand, S. M. Razavizadeh and I. Lee, "Optimum Solutions for Weighted Sum-Rate of NOMA and TDMA in Wireless Powered IoT Networks," IEEE Internet of Things J., 2023. [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," IEEE Access, 2022. [link]