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- Cheema, M. A., et al.
(author)
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A Drone-Aided Blockchain-Based Smart Vehicular Network
- 2021
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In: IEEE transactions on intelligent transportation systems (Print). - : Institute of Electrical and Electronics Engineers Inc.. - 1524-9050 .- 1558-0016. ; 22:7, s. 4160-4170
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Journal article (peer-reviewed)abstract
- The staggering growth of the number of vehicles worldwide has become a critical challenge resulting in tragic incidents, environment pollution, congestion, etc. Therefore, one of the promising approaches is to design a smart vehicular system as it is beneficial to drive safely. Present vehicular system lacks data reliability, security, and easy deployment. Motivated by these issues, this paper addresses a drone-enabled intelligent vehicular system, which is secure, easy to deploy and reliable in quality. Nevertheless, an increase in the number of operating drones in the communication networks makes them more vulnerable towards the cyber-attacks, which can completely sabotage the communication infrastructure. To tackle these problems, we propose a blockchain-based registration and authentication system for the entities such as drones, smart vehicles (SVs) and roadside units (RSUs). This paper is mainly focused on the blockchain-based secure system design and the optimal placement of drones to improve the spectral efficiency of the overall network. In particular, we investigate the association of RSUs with the drones by considering multiple communication-related factors such as available bandwidth, maximum number of links a drone can support, and backhaul limitations. We show that the proposed model can easily be overlaid on the current vehicular network reaping benefits of secure and reliable communications. © 2000-2011 IEEE.
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| 2. |
- Shehzad, M. K., et al.
(author)
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Backhaul-Aware Intelligent Positioning of UAVs and Association of Terrestrial Base Stations for Fronthaul Connectivity
- 2021
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In: IEEE Transactions on Network Science and Engineering. - : IEEE Computer Society. - 2327-4697.
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Journal article (peer-reviewed)abstract
- The mushroom growth of cellular users requires novel advancements in the existing cellular infrastructure. One way to handle such tremendous increase is to densely deploy terrestrial small-cell base stations (TSBSs) with careful management of smart backhaul/fronthaul networks. Nevertheless, terrestrial backhaul hubs significantly suffer from dense fading environment and are difficult to install in a typical urban environment. Therefore, this paper considers the idea of replacing terrestrial backhaul network with an aerial network consisting of unmanned aerial vehicles (UAVs) to provide the fronthaul connectivity between the TSBSs and the ground core-network. To this end, we focus on the joint positioning of UAVs and association of TSBSs such that the sum-rate of the overall system is maximized. In particular, the association problem of TSBSs with UAVs is formulated under communication-related constraints, i.e., bandwidth, number of connections to a UAV, power limit, interference threshold, UAV heights, and backhaul data rate. To meet this joint objective, we take advantage of genetic algorithm (GA) due to the offline nature of our optimization problem. The performance of the proposed scheme is evaluated using the unsupervised learning-based k-means clustering algorithm. We observe that the proposed scheme is highly effective to satisfy the requirements of smart fronthaul networks. IEEE
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