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20182026
most citedMassive MIMO Channel Prediction: Kalman Filtering vs. Machine Learning

154 citations · 234 across the 15 of their papers we have counts for

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12 papers · 1 filter

cs.IT2025

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…

cs.IT2025

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…

cs.IT2025

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…

cs.IT2025★ 1 cited

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…

cs.IT2024

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Channel prediction compensates for outdated channel state information in multiple-input multiple-output (MIMO) systems.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…

cs.IT2022★ 36 cited

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…

cs.IT2022★ 2 cited

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To compensate the loss from outdated channel state information in wideband massive multiple-input multipleoutput (MIMO) systems, channel prediction can be performed by leveraging t…

cs.IT2021

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…

cs.IT2021★ 18 cited

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…

cs.IT2020★ 154 cited

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,…

cs.IT2019★ 4 cited

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…

cs.IT2018★ 19 cited

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…