654 citations · 1.9k across the 149 of their papers we have counts for
25 papers · 2 filters
Diffusion-Prior Split Gibbs Sampling for Synthetic Aperture Radar Imaging under Incomplete Measurements
Hefei Gao, Tianyao Huang, Letian Guo +2
Synthetic aperture radar (SAR) imaging plays a critical role in all-weather, day-and-night remote sensing, yet reconstruction is often challenged by noise, undersampling, and compl…
Ultra-Massive MIMO with Orthogonal Chirp Division Multiplexing for Near-Field Sensing and Communication Integration
Ziwei Wan, Zhen Gao, Fabien Heliot +6
This paper integrates the emerging ultra-massive multiple-input multiple-output (UM-MIMO) technique with orthogonal chirp division multiplexing (OCDM) waveform to tackle the challe…
mSQUID: Model-Based Leanred Modulo Recovery at Low Sampling Rates
Yhonatan Kvich, Rotem Arie, Hana Hasan +2
Modulo sampling enables acquisition of signals with unlimited dynamic range by folding the input into a bounded interval prior to sampling, thus eliminating the risk of signal clip…
Leaky Wave Antennas for Next Generation Wireless Applications in sub-THz Frequencies: Current Status and Research Challenges
Natalie Lang, Atsutse K. Kludze, Nir Shlezinger +4
The ever-growing demand for ultra-high data rates, massive connectivity, and joint communication-sensing capabilities in future wireless networks is driving research into sub-terah…
pDANSE: Particle-based Data-driven Nonlinear State Estimation from Nonlinear Measurements
Anubhab Ghosh, Yonina C. Eldar, Saikat Chatterjee
We consider the problem of designing a data-driven nonlinear state estimation (DANSE) method that uses (noisy) nonlinear measurements of a process whose underlying state transition…
Bayesian Signal Separation via Plug-and-Play Diffusion-Within-Gibbs Sampling
Yi Zhang, Rui Guo, Yonina C. Eldar
We propose a posterior sampling algorithm for the problem of estimating multiple independent source signals from their noisy superposition. The proposed algorithm is a combination…