activity
20182022
most citedEuclidean Matchings in Ultra-Dense Networks

10 citations · 28 across the 10 of their papers we have counts for

collaborators

14 papers

eess.SP2022

MmWave Mapping and SLAM for 5G and Beyond

Yu Ge, Ossi Kaltiokallio, Hyowon Kim +5

Device localization and radar-like mapping are at the heart of integrated sensing and communication, enabling not only new services and applications, but can also improve communica…

eess.SP2022

PMBM-based SLAM Filters in 5G mmWave Vehicular Networks

Hyowon Kim, Karl Granström, Lennart Svensson +2

Radio-based vehicular simultaneous localization and mapping (SLAM) aims to localize vehicles while mapping the landmarks in the environment. We propose a sequence of three Poisson…

eess.SP2021

A Computationally Efficient EK-PMBM Filter for Bistatic mmWave Radio SLAM

Yu Ge, Ossi Kaltiokallio, Hyowon Kim +6

Millimeter wave (mmWave) signals are useful for simultaneous localization and mapping (SLAM), due to their inherent geometric connection to the propagation environment and the prop…

cs.LG20212 cited

Personalized Federated Learning over non-IID Data for Indoor Localization

Peng Wu, Tales Imbiriba, Junha Park +2

Localization and tracking of objects using data-driven methods is a popular topic due to the complexity in characterizing the physics of wireless channel propagation models. In the…

eess.SP20212 cited

Atomic Norm Minimization-based Low-Overhead Channel Estimation for RIS-aided MIMO Systems

Hyeonjin Chung, Sunwoo Kim

Large beam training overhead has been considered as one of main issues in the channel estimation for reconfigurable intelligent surface (RIS)-aided systems. In this paper, we propo…

eess.SP2021

Cooperative mmWave PHD-SLAM with Moving Scatterers

Hyowon Kim, Jaebok Lee, Yu Ge +3

Using the multiple-model (MM) probability hypothesis density (PHD) filter, millimeter wave (mmWave) radio simultaneous localization and mapping (SLAM) in vehicular scenarios is sus…