101 citations · 301 across the 44 of their papers we have counts for
6 papers · 1 filter
Grid-Supervised Flow Refinement for Wireless Localization
Taekyun Lee, Tommaso Balercia, Heasung Kim +2
This paper introduces FlowLoc, a framework for high-accuracy user equipment positioning from channel state information observed at multiple base stations. The input is a magnitude…
Fine-Tuning Masked Diffusion for Provable Self-Correction
Jaeyeon Kim, Seunggeun Kim, Taekyun Lee +4
A natural desideratum for generative models is self-correction--detecting and revising low-quality tokens at inference. While Masked Diffusion Models (MDMs) have emerged as a promi…
Deep-OFDM: Neural Modulation for High Mobility
S. Ashwin Hebbar, Sravan Kumar Ankireddy, Harshithanjani Athi +3
Orthogonal Frequency Division Multiplexing (OFDM) is the dominant waveform in modern wireless systems, but suffers performance degradation in high-mobility environments due to Dopp…
Residual Diffusion Models for Variable-Rate Joint Source Channel Coding of MIMO CSI
Sravan Kumar Ankireddy, Heasung Kim, Joonyoung Cho +1
Despite significant advancements in deep learning based CSI compression, some key limitations remain unaddressed. Current approaches predominantly treat CSI compression as a source…
Generative Diffusion Model-based Compression of MIMO CSI
Heasung Kim, Taekyun Lee, Hyeji Kim +6
While neural lossy compression techniques have markedly advanced the efficiency of Channel State Information (CSI) compression and reconstruction for feedback in MIMO communication…
Efficient Weighted Sampling via Score-based Generative Models
Heasung Kim, Taekyun Lee, Hyeji Kim +1
Weighted sampling -- sampling from a probability density function (PDF) proportional to the product of a base PDF and a weight function -- is a fundamental technique with wide-rang…