1 citations · 1 across the 4 of their papers we have counts for
4 papers
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…
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…
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…
Learning Emergent Random Access Protocol for LEO Satellite Networks
Ju-Hyung Lee, Hyowoon Seo, Jihong Park +2
A mega-constellation of low-altitude earth orbit (LEO) satellites (SATs) are envisaged to provide a global coverage SAT network in beyond fifth-generation (5G) cellular systems. LE…