Publications (*corresponding author or co-first authors)

Multi-Agent Reinforcement Learning for a Multichannel Uplink Random Access: Congestion Game Perspective Permalink

Published in 2023 12th International Conference on Awareness Science and Technology (iCAST), 2023

Recommended citation: Yu Zhao, Joohyun Lee, Jun-Bae Seo. "Multi-Agent Reinforcement Learning for a Multichannel Uplink Random Access: Congestion Game Perspective." 2023 12th International Conference on Awareness Science and Technology (iCAST), Taichung, Taiwan, 2023, pp. 156-160.

SOQ: Structural Reinforcement Learning for Constrained Delay Minimization with Channel State Information Permalink

Published in IEEE Internet of Things Journal, 2023

Recommended citation: Yu Zhao, Yeongjin Kim, Joohyun Lee. "SOQ: Structural Reinforcement Learning for Constrained Delay Minimization with Channel State Information." IEEE Internet of Things Journal. Accepted.

Multi-Agent Deep Reinforcement Learning For Cross-Layer Scheduling in Mobile Ad-hoc Networks Permalink

Published in China Communications, 2023

Recommended citation: Xinxing Zheng, Yu Zhao, Joohyun Lee, Wei Chen. "Multi-Agent Deep Reinforcement Learning For Cross-Layer Scheduling in Mobile Ad-hoc Networks." China Communications. vol. 20, no. 8, pp. 78–88, 2023.

NOMA-based Random Access: Multi-Agent Reinforcement Learning Mehtod Permalink

Published in 한국통신학회 학술대회논문집, 2023

Recommended citation: 자오유, 서준배, 이주현. "NOMA기반 랜덤 엑세스: 다중 에이전트 강화 학습 방법으로" 한국통신학회 학술대회논문집. 2023, pp. 140-141.

Multi-Agent Reinforcement Learning for a Random Access Game Permalink

Published in IEEE Transactions on Vehicular Technology, 2022

Recommended citation: Dongwoo Lee, Yu Zhao*, Jun-Bae Seo, Joohyun Lee. "Multi-Agent Reinforcement Learning for a Random Access Game." IEEE Transactions on Vehicular Technology. vol. 71, no. 8, pp. 9119–9124, 2022.

Q-greedyUCB: A new exploration policy to learn resource-efficient scheduling Permalink

Published in China Communications, 2021

Recommended citation: Yu Zhao, Joohyun Lee, Wei Chen. "Q-greedyUCB: A new exploration policy to learn resource-efficient scheduling." China Communications. vol. 18, no. 6, pp. 12–23, 2021.

Reinforcement Learning for Random Access in Multi-cell Networks Permalink

Published in 2021 International Conference on Artificial Intelligence in Information and Communication (ICAIIC), 2021

Recommended citation: Dongwoo Lee, Yu Zhao, Joohyun Lee. "Reinforcement Learning for Random Access in Multi-cell Networks." 2021 International Conference on Artificial Intelligence in Information and Communication (ICAIIC). 2021, pp. 335-338, doi: 10.1109/ICAIIC51459.2021.9415281.

다중 안테나 기술에서의 딥러닝 기반 직교 진폭 변조 디코더 Permalink

Published in 한국통신학회 학술대회논문집, 2021

Recommended citation: 이동우， 자오유， 이주현. "다중 안테나 기술에서의 딥러닝 기반 직교 진폭 변조 디코더" 한국통신학회 학술대회논문집. 2021, pp. 107-108.

A reinforcement learning based low-delay scheduling with adaptive transmission Permalink

Published in 2019 International Conference on Information and Communication Technology Convergence (ICTC), 2019

Recommended citation: Yu Zhao, Joohyun Lee. "A reinforcement learning based low-delay scheduling with adaptive transmission." 2019 International Conference on Information and Communication Technology Convergence (ICTC). 2019, pp. 916-919, doi: 10.1109/ICTC46691.2019.8939680.