5 papers
Structured Masked Diffusion for Joint Multiuser Decoding
Taekyun Lee, Jiyoung Yun, Jeffrey G. Andrews +1
In joint multiuser decoding, a receiver recovers a set of messages from a single noisy aggregate of many simultaneous transmissions. Classical decoders rely on rule-based mechanism…
Channel Geometry Preserving Generative Models for CSI Feedback in MU-MIMO
Juseong Park, Taekyun Lee, Foad Sohrabi +1
Under limited feedback, channel state information (CSI) reconstruction for multiuser multiple-input multiple-output (MU-MIMO) precoding is challenging, since the precoder should pr…
DiffLoc: Diffusion Model-Based High-Precision Positioning for 6G Networks
Taekyun Lee, Tommaso Balercia, Heasung Kim +2
This paper introduces a novel framework for high-accuracy outdoor user equipment (UE) positioning that applies a conditional generative diffusion model directly to high-dimensional…
Generating High Dimensional User-Specific Wireless Channels using Diffusion Models
Taekyun Lee, Juseong Park, Hyeji Kim +1
Deep neural network (DNN)-based algorithms are emerging as an important tool for many physical and MAC layer functions in future wireless communication systems, including for large…
Self-Nomination: Deep Learning for Decentralized CSI Feedback Reduction in MU-MIMO Systems
Juseong Park, Foad Sohrabi, Jinfeng Du +1
This paper introduces a novel deep learning-based user-side feedback reduction framework, termed self-nomination. The goal of self-nomination is to reduce the number of users (UEs)…