43 citations · 66 across the 5 of their papers we have counts for
6 papers
Deep Learning for Wireless Dynamics
Heunchul Lee, Jaeseong Jeong, Zhao Wang
This paper aims to predict radio channel variations over time by deep learning from channel observations without knowledge of the underlying channel dynamics. In next-generation wi…
Fueling the Next Quantum Leap in Cellular Networks: Embracing AI in 5G Evolution towards 6G
Xingqin Lin, Mingzhe Chen, Henrik Rydén +6
Cellular networks, such as 5G systems, are becoming increasingly complex for supporting various deployment scenarios and applications. Embracing artificial intelligence (AI) in 5G…
Multi-agent deep reinforcement learning (MADRL) meets multi-user MIMO systems
Heunchul Lee, Jaeseong Jeong
A multi-agent deep reinforcement learning (MADRL) is a promising approach to challenging problems in wireless environments involving multiple decision-makers (or actors) with high-…
Deep reinforcement learning approach to MIMO precoding problem: Optimality and Robustness
Heunchul Lee, Maksym Girnyk, Jaeseong Jeong
In this paper, we propose a deep reinforcement learning (RL)-based precoding framework that can be used to learn an optimal precoding policy for complex multiple-input multiple-out…
Link Performance Abstraction for Interference-Aware Communications (IAC)
Heunchul Lee, Taeyoon Kim, Wonwoo Park +1
Advanced co-channel interference aware signal detection has drawn research attention during the recent development of Long Term Evolution-Advanced (LTE-A) systems and the interfere…
A Practical Cooperative Multicell MIMO-OFDMA Network Based on Rank Coordination
Bruno Clerckx, Heunchul Lee, Young-Jun Hong +1
An important challenge of wireless networks is to boost the cell edge performance and enable multi-stream transmissions to cell edge users. Interference mitigation techniques relyi…