Securing V2I Backscattering from Eavesdropper
Ruotong Zhao, Deepak Mishra, Aruna Seneviratne

TL;DR
This paper introduces a secure V2I backscattering framework that optimizes multiple parameters to maximize secrecy rate against eavesdroppers, enhancing vehicular communication security and efficiency.
Contribution
It presents a novel joint optimization approach for reflection, power, and trajectory in V2I backscattering to improve security against eavesdroppers.
Findings
Proposed an alternating optimization algorithm with fast convergence.
Achieved over 4.7 times higher secrecy rate compared to benchmarks.
Demonstrated the effectiveness of the framework through simulations.
Abstract
As our cities become more intelligent and more connected with new technologies like 6G, improving communication between vehicles and infrastructure is essential while reducing energy consumption. This study proposes a secure framework for vehicle-to-infrastructure (V2I) backscattering near an eavesdropping vehicle to maximize the sum secrecy rate of V2I backscatter communication over multiple coherence slots. This sustainable framework aims to jointly optimize the reflection coefficients at the backscattering vehicle, carrier emitter power, and artificial noise at the infrastructure, along with the target vehicle's linear trajectory in the presence of an eavesdropping vehicle in the parallel lane. To achieve this optimization, we separated the problem into three parts: backscattering coefficient, power allocation, and trajectory design problems. We respectively adopted parallel…
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Taxonomy
TopicsBiometric Identification and Security · Face recognition and analysis
