Title: Joint Radar-Communication Waveform Designs Using Signals from Multiplexed Users
報告人：陳雲飛教授
報告時間：2023年8月9日 11:00
報告地點：紫金山實驗室報告廳2
Abstract:
Joint radar-communication designs are exploited in applications where radar and communications systems share the same frequency band or when both radar sensing and information communication functions are required in the same system. Finding a waveform that is suitable for both radar and communication is challenging due to the difference between radar and communication operations. In this paper, we propose a new method of designing dual-functional waveforms for both radar and communication using signals from multiplexed communications users. Specifically, signals from different communications users multiplexed in the time, code or frequency domains across different data bits are linearly combined to generate an overall radar waveform. Three typical radar waveforms are considered. The coefficients of the linear combination are optimized to minimize the mean squared error with or without a constraint on the signal-to-noise ratio (SNR) for the communications signals. Numerical results show that the optimization without SNR constraint can almost perfectly approximate the radar waveform in all the cases considered, giving good dual-functional waveforms for both radar and communication. Also, among different multiplexing techniques, time division multiple access is the best option to approximate the radar waveform, followed by code division multiple access and orthogonal frequency division multiple access.
Biography:
Yunfei Chen obtained his Bachelor’s and Master’s degrees from Shanghai Jiaotong University in China in 1998 and 2001, respectively. He obtained his PhD degree from the University of Alberta in Canada in 2006. He is currently a Professor in the Department of Engineering at the Durham University in the UK. His main research interests include wireless system design and analysis, UAV communications, joint radar-communications, energy harvesting communications, physical layer security, and machine learning for communications. He served as editor for the IEEE Transactions on Communications, IEEE Wireless Communications Letters and IEEE Communications Letters, as well as guest editors for special issues in various IEEE and non-IEEE journals. He was awarded exemplary reviewer for the IEEE Transactions on Communications, IEEE Communications Letters and IEEE Wireless Communications Letters between 2015 and 2017. He won the Best Paper awards from the IEEE ICCC 2016, VTC-Spring 2017, ICNC 2018, WOCC2019 and WCSP2019. He has co-authored more than 300 peer-reviewed journal papers and 100 conference papers, 5 book chapters and one monograph. He was listed as Highly Cited Researcher by Clarivate in 2020, 2021 and 2022, and he currently has 13000+ Google citations with an h-index of 54.
