MIMO-OFDM ISAC: From Parameter Estimation to Waveform and Resource Allocation Design 

About this Topic:

Integrated sensing and communication (ISAC) is emerging as a key technology for 6G and future wireless networks, enabling communication systems to support high-throughput data transmission while simultaneously extracting sensing information from the surrounding environment. Among various candidate waveforms and architectures, multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) is particularly attractive because of its compatibility with modern cellular systems, flexible time-frequency structure, and potential to support high-resolution sensing using existing communication infrastructure.

This webinar will present recent advances in MIMO-OFDM ISAC, with a focus on four representative studies covering parameter estimation, beamforming, waveform design, and resource allocation. Starting from two major OFDM sensing approaches—reciprocal filtering and matched filtering—the talk will discuss joint angle-range-velocity estimation, compressive-sensing-aided efficient ISAC design, range-Doppler sidelobe suppression through symbol-level waveform design, and sensing-oriented adaptive time-frequency resource allocation. Together, these studies show how MIMO-OFDM ISAC can improve sensing accuracy, communication efficiency, sidelobe control, and resource utilization under practical system constraints.

About the Presenters:

Zichao Xiao received the B.S. degree in electronics and information engineering and the M.S. degree in information and communication engineering from Dalian University of Technology, Dalian, China, in 2021 and 2024, respectively. He is currently pursuing the Ph.D. degree in computer science and computer engineering at University of Luxembourg, Esch-sur-Alzette, Luxembourg. 

His current research interests are focused on signal processing, integrated sensing and communication, and reconfigurable intelligent surfaces. 

Mr. Xiao was on the Finalist of IEEE RadarConf’25 Student Paper Award.

Rang Liu (M'24) received the B.S. degree in electronic information engineering from Dalian University of Technology, Dalian, China, in 2018, and the Ph.D. degree from the School of Information and Communication Engineering, Dalian University of Technology, in 2023. 

She is currently a Humboldt Postdoctoral Research Fellow with the Institute for Digital Communications, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany. From September 2023 to March 2026, she was a Postdoctoral Scholar with the Nhu Department of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, CA, USA. Her research interests include optimization and signal processing for wireless communication systems, with emphasis on integrated sensing and communications (ISAC), reconfigurable intelligent surfaces (RIS), and massive MIMO. 

Dr. Liu received the National Scholarship in 2020 and 2022, the Outstanding Doctoral Dissertation Award from the China Education Society of Electronics (CESE) in 2023, and the Exemplary Reviewer Certificate from IEEE Wireless Communications Letters in 2024. She was included in the Stanford/Elsevier World’s Top 2% Scientists list in 2024 and 2025. She has organized special sessions at IEEE SAM and IEEE ICASSP and served as a Technical Program Committee member for several flagship international conferences. More information is available at https://rangliu0706.github.io.