activity
20232025
most citedIntegrating Pre-Trained Language Model with Physical Layer Communications

1 citations · 2 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2025

PEARL: Peer-Enhanced Adaptive Radio via On-Device LLM

Ju-Hyung Lee, Yanqing Lu, Klaus Doppler

We present PEARL (Peer-Enhanced Adaptive Radio via On-Device LLM), a framework for cooperative cross-layer optimization in device-to-device (D2D) communication. Building on our pre…

cs.IT2025

AutoBS: Autonomous Base Station Deployment with Reinforcement Learning and Digital Network Twins

Ju-Hyung Lee, Andreas F. Molisch

This paper introduces AutoBS, a reinforcement learning (RL)-based framework for optimal base station (BS) deployment in 6G radio access networks (RAN). AutoBS leverages the Proxima…

cs.IT2024

Generative vs. Predictive Models in Massive MIMO Channel Prediction

Ju-Hyung Lee, Joohan Lee, Andreas F. Molisch

Massive MIMO (mMIMO) systems are essential for 5G/6G networks to meet high throughput and reliability demands, with machine learning (ML)-based techniques, particularly autoencoder…

cs.NI2024

Interference-Aware Emergent Random Access Protocol for Downlink LEO Satellite Networks

Chang-Yong Lim, Jihong Park, Jinho Choi +3

In this article, we propose a multi-agent deep reinforcement learning (MADRL) framework to train a multiple access protocol for downlink low earth orbit (LEO) satellite networks. B…

cs.IT2024★ 1 cited

Integrating Pre-Trained Language Model with Physical Layer Communications

Ju-Hyung Lee, Dong-Ho Lee, Joohan Lee +1

The burgeoning field of on-device AI communication, where devices exchange information directly through embedded foundation models, such as language models (LMs), requires robust,…

cs.IT2023

A Scalable and Generalizable Pathloss Map Prediction

Ju-Hyung Lee, Andreas F. Molisch

Large-scale channel prediction, i.e., estimation of the pathloss from geographical/morphological/building maps, is an essential component of wireless network planning. Ray tracing…

cs.IT2023★ 1 cited

Handover Protocol Learning for LEO Satellite Networks: Access Delay and Collision Minimization

Ju-Hyung Lee, Chanyoung Park, Soohyun Park +1

This study presents a novel deep reinforcement learning (DRL)-based handover (HO) protocol, called DHO, specifically designed to address the persistent challenge of long propagatio…