You Xu (许优)

You Xu (许优)

⛪About me

Hello, my name is You Xu. I am currently a Senior Research Officer with the School of Computer Science and Electronic Engineering (CSEE), University of Essex, Colchester, UK. I received my Ph.D. degree in information and communication engineering from Huazhong University of Science and Technology in 2025.

At the University of Essex, I am currently working under the supervision of Prof. Zilong Liu. During my Ph.D. study, I was supervised by Prof. Lixia Xiao and IEEE Fellow Prof. Tao Jiang. I was also a Visiting Student Researcher at the University of Macau from December 2021 to March 2022, where I worked with Prof. Shaodan Ma in The State Key Laboratory of Internet of Things for Smart City.

My research interests include signal processing for wireless sensing and communications, with a focus on non-line-of-sight sensing and localization, RF/mmWave imaging, sparse Bayesian inference, parameter estimation, doubly dispersive and wideband channel analysis, affine frequency division multiplexing (AFDM) waveform design, and AFDM-based integrated sensing and communications.

🖥️Research Statement

My research centers on multipath signal processing for wireless sensing and communications. Multipath echoes carry rich environmental information for reconstructing non-line-of-sight (NLOS) targets, while in high-mobility communications they form doubly dispersive channels that new waveforms must address. I use sparse reconstruction, Bayesian inference, and parameter estimation to exploit multipath structure in both regimes, with the long-term goal of developing affine frequency division multiplexing (AFDM)-based integrated sensing and communication systems for complex environments.

  • NLOS Sensing and RF Imaging: Characterize rough-relay-surface scattering and develop compressed-sensing and Bayesian sparse-recovery methods for high-fidelity reconstruction of hidden-target location, velocity, and electromagnetic properties.
  • Multipath Parameter Estimation: Design statistical estimators for joint delay, Doppler, and scattering-parameter extraction under cluttered NLOS conditions.
  • AFDM Waveform and Channel Design: Establish chirp-parameter rules for full diversity in doubly dispersive channels and extend AFDM toward wideband delay-scale channels.
  • AFDM Channel Estimation and ISAC: Develop sparse Bayesian algorithms for joint phase-noise compensation and off-grid channel estimation, while characterizing sensing performance through ambiguity-function and Cramér–Rao-bound analysis.