Yongjun Ahn

According to our database, Yongjun Ahn authored at least 17 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

Role of Sensing and Computer Vision in 6G Wireless Communications.

Seungnyun Kim, Jihoon Moon, Jinhong Kim, Yongjun Ahn, Donghoon Kim, Sunwoo Kim, Kyuhong Shim, Byonghyo Shim

CoRR, 2024

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., October, 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, February, 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

Deep Learning-based Localization Using Spatial Information in the NLoS Scenarios.

Yongjun Ahn, Inkook Keum, Jinwoo Son, Byonghyo Shim

Proceedings of the 14th International Conference on Information and Communication Technology Convergence, 2023

Computer Vision-Aided Proactive Mobility Management for 6G Terahertz Communications.

Yongjun Ahn, Jinhong Kim, Sunwoo Kim, Byonghyo Shim

Proceedings of the IEEE Global Communications Conference, 2023

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

Deep Reinforcement Learning-Based Network Slicing for Beyond 5G.

Kyungjoo Suh, Sunwoo Kim, Yongjun Ahn, Seungnyun Kim, Hyungyu Ju, Byonghyo Shim

IEEE Access, 2022

On the Design Principles for Deep Learning-based Wireless Data Collection and Channel Estimation.

Yongjun Ahn, Jinhong Kim, Byonghyo Shim

Proceedings of the 13th International Conference on Information and Communication Technology Convergence, 2022

Parametric Sparse Channel Estimation Using Long Short-Term Memory for mmWave Massive MIMO Systems.

Jinhong Kim, Yongjun Ahn, Seungnyun Kim, Byonghyo Shim

Proceedings of the IEEE International Conference on Communications, 2022

D-TLoc: Deep Learning-aided Hybrid TDoA/AoA-based Localization.

Jinwoo Son, Inkook Keum, Yongjun Ahn, Byonghyo Shim

Proceedings of the IEEE VTS Asia Pacific Wireless Communications Symposium, 2022

2021

Deep Learning-Based Beamforming for Intelligent Reflecting Surface-Assisted mmWave Systems.

Yongjun Ahn, Byonghyo Shim

Proceedings of the International Conference on Information and Communication Technology Convergence, 2021

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 for Classical Mechanics.

Mugeon Song, Maverick S. H. Oh, Yongjun Ahn, Keun-Young Kim

CoRR, 2020

Deep Neural Network-based Joint Active User Detection and Channel Estimation for mMTC.

Yongjun Ahn, Wonjun Kim, Byonghyo Shim

Proceedings of the 2020 IEEE International Conference on Communications, 2020

2019

Active User Detection of Machine-Type Communications via Dimension Spreading Neural Network.

Wonjun Kim, Guyoung Lim, Yongjun Ahn, Byonghyo Shim

Proceedings of the 2019 IEEE International Conference on Communications, 2019

2016

Analysing driving patterns of electric taxi based on the location of charging station in urban area.

Yongjun Ahn, Chulmin Jun, Hwasoo Yeo

Proceedings of the IEEE International Smart Cities Conference, 2016