Atefeh Rezaei – About me

Research Engineer and Ph.D. Candidate at TU Berlin, specializing in the intersection of next-generation wireless systems and intelligent sensing. This spans 6G and ISAC system design, mmWave and high-mobility communications, sensing-assisted beam management and tracking, channel prediction, and radar signal processing. I'm also active in emerging areas such as intelligent reflecting surfaces (IRS), UAV-assisted networks, resource allocation under finite blocklength constraints, and machine learning for wireless systems. I have authored peer-reviewed publications in IEEE journals and conferences, with high citation scores, a best paper award, and a travel grant. I am also an active member of the research community, regularly reviewing for leading IEEE venues including IEEE TMC, IEEE TVT, IEEE TWC, IEEE ICC, IEEE VNC, and IEEE GLOBECOM.

Research Interests and Background

My research focuses on the design, optimization, and performance analysis of next-generation wireless communication and sensing systems, with particular emphasis on:

• 6G Wireless Communications and Integrated Sensing and Communication (ISAC): development of reliable and energy-efficient communication–sensing frameworks for high-mobility and mmWave environments.
• Digital Signal Processing (DSP): signal analysis, estimation, detection, filtering, and processing techniques for wireless communication and sensing systems.
• Radar Signal Processing and Sensing: target detection, localization, and tracking using advanced signal processing and estimation techniques, including MUSIC, matched filtering, and extended Kalman filtering.
• mmWave and High-Mobility Wireless Systems: sensing-assisted beam management and tracking, channel estimation and prediction, and robust communication strategies under rapidly time-varying channel conditions.
• UAV-Assisted Non-Terrestrial Networks: trajectory design, resource allocation, and joint communication-sensing optimization for integrated terrestrial-non-terrestrial networks.
• Optimization and Resource Allocation: development of optimization-based algorithms for wireless networks, with emphasis on energy efficiency, resource management, and finite blocklength communications.

My research is grounded in a combination of wireless communications, statistical signal processing, radar systems, mathematical optimization, resource allocation, and machine learning. I leverage these foundations to develop analytical models, optimization frameworks, and simulation-based solutions for complex communication and sensing systems.

Professional Experience

• Research Engineer, TU Berlin (2022–present)
  Research on 6G, ISAC, and high-mobility mmWave systems, including sensing-assisted beam tracking, radar-based target tracking, and UAV-assisted wireless networks; contributor to XG-RIC, 6G-RIC, and RADCOM.
• Researcher, Tarbiat Modares University (2019–2022)
  Research on 5G technologies, including MIMO, NOMA, IoT, and IRS-assisted communications, with a focus on optimization and energy-efficient resource allocation.
• Research Consultant, Iran Telecom Research Center (2017–2018)
  Conducted research and technical analysis on 5G network architectures and resource allocation strategies.
• Designer and Developer, University Robotics Group (2011–2013)
  Contributed to the design and development of tracked robotic platforms for university research projects.

Awards & Recognition

• Best Paper Award, IEEE WPMC
• Travel Grant, IEEE VTC
• Academic Distinction: Ranked among the top-performing Communications Engineering B.Sc. students at the university.

Academic Service

• Peer reviewer for leading IEEE journals and conferences, including TMC, TVT, TWC, ICC, VNC, VTC, and GLOBECOM.

Atefeh Rezaei – Journals

1. A. Khalili, A. Rezaei, D. Xu, F. Dressler, R. Schober, "Efficient UAV hovering, resource allocation, and trajectory design for ISAC with limited backhaul capacity," IEEE Trans. on Wireless Commun., vol. 23, no. 11, pp. 17635–17650, Nov. 2024.
2. J. Jalali, A. Khalili, A. Rezaei, R. Berkvens, M. Weyn, and J. Famaey, "IRS-Based Energy Efficiency and Admission Control Maximization for IoT Users With Short Packet Lengths," IEEE Transactions on Vehicular Technology, vol. 72, no. 9, pp. 12379-12384, Jun. 2023.
3. A. Rezaei, A. Khalili, J. Jalali, H. Shafiei, Q. Wu, "Energy-efficient resource allocation and antenna selection for IRS-assisted multicell downlink networks," IEEE Wireless Commun. Letters, vol. 11, no. 6, pp. 1229–1233, Jun. 2022.
4. A. Rezaei, P. Azmi, N.M. Yamchi, M.R. Javan, H. Yanikomeroglu, "Robust resource allocation for cooperative MISO-NOMA-based heterogeneous networks," IEEE Trans. on Commun., vol. 69, no. 6, pp. 3864–3878, Jun. 2021.

Manuscripts in preparation / under review, 2026:

• A. Rezaei, V. Jamali, F. Dressler, "Toward Enhanced Accuracy and Reliability of Sensing-Assisted Beam Tracking Frameworks in High-Mobility mmWave Networks," under review (IEEE TVT), 2026.
• A. Rezaei, A. Khalili, F. Dressler, R. Schober, "A Novel Pulse Radar Framework for ISAC-FD-enabled URLLC Systems," under review (IEEE TVT), 2026.

Atefeh Rezaei – Conferences

1. A. Rezaei, M. Carl, F. Dressler, "Mobility-Aware Interference-Coupled ISAC for Energy-Efficient Multi-Vehicle Tracking," MSWiM 2026, Paris, France, Oct. 26–30, 2026. [link]
2. A. Khalili, A. Rezaei, D. Xu, R. Schober, "Energy-aware resource allocation and trajectory design for UAV-enabled ISAC," IEEE GLOBECOM 2023.
3. A. Rezaei, A. Khalili, F. Dressler, "Resource allocation for UAV-assisted industrial IoT user with finite blocklength," IEEE VTC-Fall 2023.
4. J. Jalali, A. Khalili, A. Rezaei, J. Famaey, W. Saad, "Power-efficient Antenna Switching and Beamforming Design for Multi-User SWIPT with Non-Linear Energy Harvesting," IEEE CCNC 2023.
5. A. Nouruzi, A. Rezaei, A. Khalili, N. Mokari, E.A. Jorswieck, H. Yanikomeroglu, "Smart Resource Allocation Model via Artificial Intelligence in Software-Defined 6G Networks," IEEE ICC 2023.
6. J. Jalali, A. Khalili, A. Rezaei, J. Famaey, "Is Active IRS Useful for mmWave Wireless Networks or Not?" IEEE ICNC 2023.
7. J. Jalali, A. Rezaei, A. Khalili, J. Famaey, "Power-efficient Joint Resource Allocation and Decoding Error Probability for Multiuser Downlink MISO with Finite Block Length Codes," IEEE WPMC 2022.
8. A. Rezaei, N. Mokari, P. Azmi, "Robust resource allocation in cloud-RAN network based on CoMP technology," IST 2016.

Technical Reports:

• M. Moltafet, A. Rezaei, N. Mokari, M. R. Javan, H. Saeedi, H. Pishro-Nik, "Joint Dynamic Pricing and Radio Resource Allocation Framework for IoT Services," arXiv, cs.IT, 1903.02928, March 2019.
• A. Nouruzi, A. Rezaei, A. Khalili, N. Mokari, M. R. Javan, E. A. Jorswieck, H. Yanikomeroglu, "Toward a Smart Resource Allocation Policy via Artificial Intelligence in 6G Networks: Centralized or Decentralized?," arXiv, eess.SP, 2202.09093, February 2022.

Atefeh Rezaei – Book Chapters and Academic Theses

1. A. Rezaei, Ph.D. Dissertation (in progress), Electrical Engineering, TU Berlin, Germany, 2022–present.
2. A. Rezaei, Master's thesis, Electrical Engineering, Tarbiat Modares University, Tehran, Iran.

Atefeh Rezaei – Posters

Poster presentations at conferences and workshops.

Atefeh Rezaei – Courses

Teaching Assistant Experience

• Fundamental of Telecommunication Systems
• Signals and Systems

Atefeh Rezaei – Members

Members

• Mathis Carl
  Research area: Optimized V2I Framework for Mobile Target Tracking via Integrated Sensing and Communication