Hwanjin Kim

Hwanjin Kim

KAIST

H-index: 5

Asia-South Korea

About Hwanjin Kim

Hwanjin Kim, With an exceptional h-index of 5 and a recent h-index of 5 (since 2020), a distinguished researcher at KAIST, specializes in the field of Wireless Communications, Machine Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Method and device for channel estimation in wireless communication system supporting MIMO

Robust Over-the-Air Federated Learning

Device for estimating channel in wireless communication system

Electronic device for predicting channel in mimo communication system and method of predicting the same

Apparatus and method for reconstructing downlink channel in wireless communication system

Device and method for controlling beamformer in wireless communication system

Multi-User Beamforming under Per-Antenna Power Constraint

Massive MIMO channel prediction via meta-learning and deep denoising: Is a small dataset enough?

Hwanjin Kim Information

University

Position

___

Citations(all)

124

Citations(since 2020)

124

Cited By

20

hIndex(all)

5

hIndex(since 2020)

5

i10Index(all)

3

i10Index(since 2020)

3

Email

University Profile Page

Google Scholar

Hwanjin Kim Skills & Research Interests

Wireless Communications

Machine Learning

Top articles of Hwanjin Kim

Method and device for channel estimation in wireless communication system supporting MIMO

2024/3/19

Robust Over-the-Air Federated Learning

2024/3/13

Hwanjin Kim
Hwanjin Kim

H-Index: 4

Device for estimating channel in wireless communication system

2024/3/7

Electronic device for predicting channel in mimo communication system and method of predicting the same

2024/2/8

Apparatus and method for reconstructing downlink channel in wireless communication system

2023/12/26

Device and method for controlling beamformer in wireless communication system

2023/10/19

Multi-User Beamforming under Per-Antenna Power Constraint

2023/10/11

Massive MIMO channel prediction via meta-learning and deep denoising: Is a small dataset enough?

IEEE Transactions on Wireless Communications

2023/5/3

Hwanjin Kim
Hwanjin Kim

H-Index: 4

Junil Choi
Junil Choi

H-Index: 26

Complete power reallocation for MU-MISO under per-antenna power constraint

IEEE Transactions on Communications

2023/1/30

Massive MIMO channel prediction using machine learning: Power of domain transformation

arXiv preprint arXiv:2208.04545

2022/8/9

Hwanjin Kim
Hwanjin Kim

H-Index: 4

Junil Choi
Junil Choi

H-Index: 26

Machine Learning-Based Channel Prediction Exploiting Frequency Correlation in Massive MIMO Wideband Systems

2021/10/20

Hwanjin Kim
Hwanjin Kim

H-Index: 4

Junil Choi
Junil Choi

H-Index: 26

Downlink Channel Reconstruction for Massive MIMO Spatial Multiplexing

2021/6/14

Downlink channel reconstruction for spatial multiplexing in massive MIMO systems

IEEE Transactions on Wireless Communications

2021/4/16

Massive MIMO channel prediction: Machine learning versus Kalman filtering

2020/12/7

Massive MIMO channel prediction: Kalman filtering vs. machine learning

IEEE Transactions on Communications

2020/9/30

Method and apparatus for estimating channel in multiple-input multiple-output communication systems exploiting temporal correlations

2020/1/7

See List of Professors in Hwanjin Kim University(KAIST)

Co-Authors

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