154 citations · 234 across the 15 of their papers we have counts for
15 papers
System-Level Evaluation of LEO Satellite Communications Under Service-Driven Traffic Dynamics
Miyeon Lee, Dong-Hyun Jung, Sucheol Kim +2
As low Earth orbit (LEO) satellite communications take shape on a global scale, system-level evaluation has become essential for a rigorous understanding of their performance chara…
Hybrid Federated Learning for Noise-Robust Training
Yongjun Kim, Hyeongjun Park, Hwanjin Kim +1
Federated learning (FL) and federated distillation (FD) are distributed learning paradigms that train UE models with enhanced privacy, each offering different trade-offs between no…
Downlink Channel Estimation for mmWave Systems with Impulsive Interference
Kwonyeol Park, Gyoseung Lee, Hyeongtaek Lee +2
In this paper, we investigate a channel estimation problem in a downlink millimeter-wave (mmWave) multiple-input multiple-output (MIMO) system, which suffers from impulsive interfe…
Analysis of Beam Misalignment Effect in Inter-Satellite FSO Links
Minje Kim, Hongjae Nam, Beomsoo Ko +4
Free-space optical (FSO) communication has emerged as a promising technology for inter-satellite links (ISLs) due to its high data rate, low power consumption, and reduced interfer…
Machine Learning for Future Wireless Communications: Channel Prediction Perspectives
Hwanjin Kim, Junil Choi, David J. Love
Precise channel state knowledge is crucial in future wireless communication systems, which drives the need for accurate channel prediction without additional pilot overhead. While…
Meta-Learning-Based People Counting and Localization Models Employing CSI from Commodity WiFi NICs
Jihoon Cha, Hwanjin Kim, Junil Choi
In this paper, we consider people counting and localization systems exploiting channel state information (CSI) measured from commodity WiFi network interface cards (NICs). While CS…
Spatial-Division ISAC: A Practical Waveform Design Strategy via Null-Space Superimposition
Byunghyun Lee, Hwanjin Kim, David J. Love +1
Integrated sensing and communications (ISAC) is a key enabler of new applications, such as precision agriculture, extended reality (XR), and digital twins, for 6G wireless systems.…
Machine Learning-based Channel Prediction in Wideband Massive MIMO Systems with Small Overhead for Online Training
Beomsoo Ko, Hwanjin Kim, Minje Kim +1
Channel prediction compensates for outdated channel state information in multiple-input multiple-output (MIMO) systems. Machine learning (ML) techniques have recently been implemen…
Massive MIMO Channel Prediction Via Meta-Learning and Deep Denoising: Is a Small Dataset Enough?
Hwanjin Kim, Junil Choi, David J. Love
Accurate channel knowledge is critical in massive multiple-input multiple-output (MIMO), which motivates the use of channel prediction. Machine learning techniques for channel pred…
Massive MIMO Channel Prediction Using Machine Learning: Power of Domain Transformation
Beomsoo Ko, Hwanjin Kim, Junil Choi
To compensate the loss from outdated channel state information in wideband massive multiple-input multipleoutput (MIMO) systems, channel prediction can be performed by leveraging t…
Complete Power Reallocation for MU-MIMO under Per-Antenna Power Constraint
Sucheol Kim, Hyeongtaek Lee, Hwanjin Kim +2
This paper proposes a beamforming method under a per-antenna power constraint (PAPC). Although many beamformer designs with the PAPC need to solve complex optimization problems, th…
Downlink Channel Reconstruction for Spatial Multiplexing in Massive MIMO Systems
Hyeongtaek Lee, Hyuckjin Choi, Hwanjin Kim +4
To get channel state information (CSI) at a base station (BS), most of researches on massive multiple-input multiple-output (MIMO) systems consider time division duplexing (TDD) to…
Massive MIMO Channel Prediction: Kalman Filtering vs. Machine Learning
Hwanjin Kim, Sucheol Kim, Hyeongtaek Lee +3
This paper focuses on channel prediction techniques for massive multiple-input multiple-output (MIMO) systems. Previous channel predictors are based on theoretical channel models,…
Channel Estimation for Spatially/Temporally Correlated Massive MIMO Systems with One-Bit ADCs
Hwanjin Kim, Junil Choi
This paper considers the channel estimation problem for massive multiple-input multiple-output (MIMO) systems that use one-bit analog-to-digital converters (ADCs). Previous channel…
Channel Estimation for One-Bit Massive MIMO Systems Exploiting Spatio-Temporal Correlations
Hwanjin Kim, Junil Choi
Massive multiple-input multiple-output (MIMO) can improve the overall system performance significantly. Massive MIMO systems, however, may require a large number of radio frequency…