@article{M5BFCB6F7,
title = "HDRL-Based Cooperative Jamming Method for Secure Battlefield Network",
journal = "The Journal of Korean Institute of Communications and Information Sciences",
year = "2025",
issn = "1226-4717",
doi = "10.7840/kics.2025.50.1.70",
author = "Kakyeom Jeon, Youngil Jeon, Changhun Yu, Junghyun Seo, Bang Chul Jung, Howon Lee",
keywords = "Battlefield network, Electronic warfare, Cooperative jamming, HDRL, SJNR",
abstract = "Effective jamming techniques for communication and control signals are required in modern electronic warfare to counter unmanned aerial vehicles (UAVs) with three-dimensional mobility. In this paper, we propose a hierarchical deep reinforcement learning (HDRL)-based cooperative jamming method using ground jammers (GJs) and UAV jammers (UJs) for battlefield network security. The proposed method aims to maximize the jamming effect on malicious UAVs (MUs) through two types of jammers. In particular, the proposed method reduces the computational complexity of jamming through a hierarchical framework."
}