1 citations · 1 across the 3 of their papers we have counts for
6 papers
Robust Super-Resolution Compressive Sensing: A Two-timescale Alternating MAP Approach
Yufan Zhou, Jingyi Li, Wenkang Xu +1
The problem of super-resolution compressive sensing (SR-CS) is crucial for various wireless sensing and communication applications. Existing methods often suffer from limited resol…
Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems
An Liu, Wenkang Xu, Wei Xu +1
This paper considers a joint scattering environment sensing and data recovery problem in an uplink integrated sensing and communication (ISAC) system. To facilitate joint scatterer…
Exploiting Dynamic Sparsity for Near-Field Spatial Non-Stationary XL-MIMO Channel Tracking
Wenkang Xu, An Liu, Min-jian Zhao +2
This work considers a spatial non-stationary channel tracking problem in broadband extremely large-scale multiple-input-multiple-output (XL-MIMO) systems. In the case of spatial no…
Subspace Constrained Variational Bayesian Inference for Structured Compressive Sensing with a Dynamic Grid
An Liu, Yufan Zhou, Wenkang Xu
We investigate the problem of recovering a structured sparse signal from a linear observation model with an uncertain dynamic grid in the sensing matrix. The state-of-the-art expec…
Joint Visibility Region Detection and Channel Estimation for XL-MIMO Systems via Alternating MAP
Wenkang Xu, An Liu, Min-jian Zhao
We investigate a joint visibility region (VR) detection and channel estimation problem in extremely large-scale multiple-input-multiple-output (XL-MIMO) systems, where near-field p…
Successive Linear Approximation VBI for Joint Sparse Signal Recovery and Dynamic Grid Parameters Estimation
Wenkang Xu, An Liu, Bingpeng Zhou +1
For many practical applications in wireless communications, we need to recover a structured sparse signal from a linear observation model with dynamic grid parameters in the sensin…