UAV-Enabled Covert Communication in LAWN: From Typical Application to Efficient and Novel Trajectory Design Method

IEEE Communications Magazine, vol. 64, pp. 196–203

Abstract

Owing to the flexible and rapid deployment capabilities, low altitude wireless network (LAWN) is gaining widespread adoption across diverse areas. Unmanned aerial vehicle (UAV), characterized by high mobility, is emerging as a pivotal component of LAWN. However, the open nature of UAV air to ground (A2G) channels render the communications highly vulnerable to illegal detection, posing a critical covert issue. This inherent vulnerability highlights the need for UAV-enabled covert communication, which aims to hide the existence of wireless transmission from illegal wardens and has attracted significant research attentions. In this article, we provide a comprehensive overview of UAV-enabled covert communication in LAWN. We first introduce typical applications and analyze emerging techniques in this domain. Subsequently, we focus on the core challenges of trajectory design, where we present two novel trajectory design methods, the successive-hover-and-fly (SHF) structure that reduces design complexity by reformulating the continuous trajectory into finite hovering points, and the artificial potential field (APF) method that, for the first time, yields a closed-form globally optimal trajectory solution. Numerical results demonstrate that these novel methods achieve near-optimal covert performance with significantly lower complexity compared to benchmark. Finally, several open directions and the challenges are discussed.

Authors 6

1. Peng Wu

   Wuhan University

   Affiliation as printed

   Electronic Information School, Wuhan University

2. Yuxi Huang

   Wuhan University

   Affiliation as printed

   Electronic Information School, Wuhan University

3. Xiaopeng Yuan Aachen Chair of Information Theory and Data Analytics

   RWTH Aachen University

   Affiliation as printed

   Chair of Information Theory and Data Analytics, RWTH Aachen University

4. Wei Gao

   Wuhan University

   Affiliation as printed

   Electronic Information School, Wuhan University

5. Yulin Hu

   Wuhan University

   Affiliation as printed

   Electronic Information School, Wuhan University

6. Anke Schmeink Aachen Chair of Information Theory and Data Analytics

   RWTH Aachen University

   Affiliation as printed

   Chair of Information Theory and Data Analytics, RWTH Aachen University