Analysing driving patterns of electric taxi based on the location of charging station in urban area. - Yongjun Ahn; Chulmin Jun; Hwasoo Yeo (ISC2, 2016)

Active User Detection of Machine-Type Communications via Dimension Spreading Neural Network. - Wonjun Kim; Guyoung Lim; Yongjun Ahn; Byonghyo Shim (ICC, 2019)

Deep Neural Network-based Joint Active User Detection and Channel Estimation for mMTC. - Yongjun Ahn; Wonjun Kim; Byonghyo Shim (ICC, 2020)

Deep Learning for Classical Mechanics. - Mugeon Song; Maverick S. H. Oh; Yongjun Ahn; Keun-Young Kim (CoRR, 2020)

Deep Neural Network-Based Active User Detection for Grant-Free NOMA Systems. - Wonjun Kim; Yongjun Ahn; Byonghyo Shim (IEEE Trans. Commun., 2020)

Deep Learning-Based Beamforming for Intelligent Reflecting Surface-Assisted mmWave Systems. - Yongjun Ahn; Byonghyo Shim (ICTC, 2021)

D-TLoc: Deep Learning-aided Hybrid TDoA/AoA-based Localization. - Jinwoo Son; Inkook Keum; Yongjun Ahn; Byonghyo Shim (APWCS, 2022)

Parametric Sparse Channel Estimation Using Long Short-Term Memory for mmWave Massive MIMO Systems. - Jinhong Kim; Yongjun Ahn; Seungnyun Kim; Byonghyo Shim (ICC, 2022)

On the Design Principles for Deep Learning-based Wireless Data Collection and Channel Estimation. - Yongjun Ahn; Jinhong Kim; Byonghyo Shim (ICTC, 2022)

Deep Reinforcement Learning-Based Network Slicing for Beyond 5G. - Kyungjoo Suh; Sunwoo Kim 004; Yongjun Ahn; Seungnyun Kim; Hyungyu Ju; Byonghyo Shim (IEEE Access, 2022)

Active User Detection and Channel Estimation for Massive Machine-Type Communication: Deep Learning Approach. - Yongjun Ahn; Wonjun Kim; Byonghyo Shim (IEEE Internet Things J., 2022)

Computer Vision-Aided Proactive Mobility Management for 6G Terahertz Communications. - Yongjun Ahn; Jinhong Kim; Sunwoo Kim 004; Byonghyo Shim (GLOBECOM, 2023)

Deep Learning-based Localization Using Spatial Information in the NLoS Scenarios. - Yongjun Ahn; Inkook Keum; Jinwoo Son; Byonghyo Shim (ICTC, 2023)

Massive Data Generation for Deep Learning-Aided Wireless Systems Using Meta Learning and Generative Adversarial Network. - Jinhong Kim; Yongjun Ahn; Byonghyo Shim (IEEE Trans. Veh. Technol., 2023)

Towards deep learning-aided wireless channel estimation and channel state information feedback for 6G. - Wonjun Kim; Yongjun Ahn; Jinhong Kim; Byonghyo Shim (J. Commun. Networks, 2023)

Toward Intelligent Millimeter and Terahertz Communication for 6G: Computer Vision-Aided Beamforming. - Yongjun Ahn; Jinhong Kim; Seungnyun Kim; Kyuhong Shim; Jiyoung Kim; Sangtae Kim; Byonghyo Shim (IEEE Wirel. Commun., 2023)

Computer Vision-Aided Beamforming for 6G Wireless Communications: Dataset and Training Perspective. - Sunwoo Kim 001; Yongjun Ahn; Byonghyo Shim (ICC, 2024)

VOMTC: Vision Objects for Millimeter and Terahertz Communications. - Sunwoo Kim; Yongjun Ahn; Daeyoung Park; Byonghyo Shim (CoRR, 2024)

Sensing and Computer Vision-Aided Mobility Management for 6G Millimeter and Terahertz Communication Systems. - Yongjun Ahn; Jinhong Kim; Seungnyun Kim; Sunwoo Kim 004; Byonghyo Shim (IEEE Trans. Commun., 2024)

Role of Sensing and Computer Vision in 6G Wireless Communications. - Seungnyun Kim; Jihoon Moon; Jinhong Kim; Yongjun Ahn; Donghoon Kim; Sunwoo Kim 004; Kyuhong Shim; Byonghyo Shim (IEEE Wirel. Commun., 2024)

Deep Learning-Aided Parametric Sparse Channel Estimation for Terahertz Massive MIMO Systems. - Jinhong Kim; Yongjun Ahn; Seungnyun Kim; Byonghyo Shim (IEEE Trans. Cogn. Commun. Netw., 2024)

VOMTC: Vision Objects for Millimeter and Terahertz Communications. - Sunwoo Kim 004; Yongjun Ahn; Daeyoung Park; Byonghyo Shim (IEEE Trans. Cogn. Commun. Netw., 2025)

Transformer-Aided Mobile Positioning for 6G Ultra-Dense Networks. - Hyung Joon Cho; Yongjun Ahn; Byonghyo Shim (IEEE Trans. Veh. Technol., 2025)