Dual Identities Enabled Low-Latency Visual Networking for UAV Emergency Communication

TL;DR

This paper introduces a novel DPI-Mapping approach for UAV visual networking that enables low-latency emergency communication by matching dual domain identities without beacon exchange, improving speed and reducing disturbance.

Contribution

The paper presents the first DPI-Mapping solution that matches UAV identities from dual domains using feature similarity and bio-inspired algorithms for rapid visual communication.

Findings

Reduces EC latency significantly compared to traditional methods.

Improves accuracy of identity matching through Kalman filtering.

Decreases disturbing messages without lowering hit rate.

Abstract

The Unmanned Aerial Vehicle (UAV) swarm networks will play a crucial role in the B5G/6G network thanks to its appealing features, such as wide coverage and on-demand deployment. Emergency communication (EC) is essential to promptly inform UAVs of potential danger to avoid accidents, whereas the conventional communication-only feedback-based methods, which separate the digital and physical identities (DPI), bring intolerable latency and disturb the unintended receivers. In this paper, we present a novel DPI-Mapping solution to match the identities (IDs) of UAVs from dual domains for visual networking, which is the first solution that enables UAVs to communicate promptly with what they see without the tedious exchange of beacons. The IDs are distinguished dynamically by defining feature similarity, and the asymmetric IDs from different domains are matched via the proposed bio-inspired matching algorithm. We also consider Kalman filtering to combine the IDs and predict the states for accurate mapping. Experiment results show that the DPI-Mapping reduces individual inaccuracy of features and significantly outperforms the conventional broadcast-based and feedback-based methods in EC latency. Furthermore, it also reduces the disturbing messages without sacrificing the hit rate.