UAV-Enabled Confidential Data Collection in Wireless Networks
Xiaobo Zhou, Shihao Yan, Min Li, Jun Li, Feng Shu

TL;DR
This paper introduces a UAV-based data collection system that enhances confidentiality by using artificial noise and advanced optimization techniques to maximize secrecy rates in wireless networks.
Contribution
It proposes a novel UAV-enabled confidential data collection framework with joint optimization of artificial noise and transmission parameters, employing convex approximation methods.
Findings
Significant secrecy rate improvements over benchmark schemes.
Effective convex approximation techniques reduce computational complexity.
The proposed method enhances data confidentiality in UAV wireless networks.
Abstract
This work, for the first time, considers confidential data collection in the context of unmanned aerial vehicle (UAV) wireless networks, where the scheduled ground sensor node (SN) intends to transmit confidential information to the UAV without being intercepted by other unscheduled ground SNs. Specifically, a full-duplex (FD) UAV collects data from each scheduled SN on the ground and generates artificial noise (AN) to prevent the scheduled SN's confidential information from being wiretapped by other unscheduled SNs. We first derive the reliability outage probability (ROP) and secrecy outage probability (SOP) of a considered fixed-rate transmission, based on which we formulate an optimization problem that maximizes the minimum average secrecy rate (ASR) subject to some specific constraints. We then transform the formulated optimization problem into a convex problem with the aid of…
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Taxonomy
TopicsUAV Applications and Optimization · Mobile Ad Hoc Networks · Wireless Communication Security Techniques
