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Special Issue Information

Dear Colleagues,

The success of the MDPI Drones Special Issue “UAV-Assisted Intelligent Vehicular Networks” led us to propose this second edition, for which we are pleased to invite you to submit original contributions.

We are on the cusp of a new era of intelligent transportation. As a key enabler for intelligent transportation systems (ITSs), vehicular networks encompass a broad range of information technologies, including vehicle-to-everything (V2X), mobile edge computing (MEC), cloud computing, and blockchain. Although vehicular networks offer an improved performance with advanced services, the explosive growth of communication devices and the rising demand for many emerging services will bring new communication challenges to vehicular networks. It is anticipated that the communication systems integrated with unmanned aerial vehicles (UAVs) will satisfy these requirements in next-generation vehicular networks. Due to their high flexible mobility, UAV-assisted vehicular networks will bring far-reaching and transformative benefits, with significantly enhanced reliability and security, extremely high data rates, massive and hyper-fast wireless access, and much smarter, longer, and greener three-dimensional (3D) communications coverage.

This Special Issue will focus on (but not be limited to) the following topics:

Protocol design and analysis for UAV-assisted V2X;
Resource management and mobility management;
Energy harvesting and management for UAV-assisted V2X;
Non-orthogonal multiple access (NOMA)-enhanced UAV-assisted vehicular networks;
UAV-assisted vehicular network applications and services;
V2X communications in 5G and beyond;
UAV-assisted vehicular networks based on artificial intelligence (AI);
Sensors for vehicular technologies;
Terminal intelligence;
Security- and privacy-preserving schemes for UAV-assisted vehicular networks;
Channel measurement and modeling for UAV-assisted vehicular networks

Dr. Dawei Wang
Prof. Dr. Ruonan Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Drones is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Related Special Issue

Published Papers (1 paper)

Research

15 pages, 2066 KiB

Open AccessArticle

Post-Disaster Emergency Communications Enhanced by Drones and Non-Orthogonal Multiple Access: Three-Dimensional Deployment Optimization and Spectrum Allocation

by Linyang Li, Lijun Zhu, Fanghui Huang, Dawei Wang, Xin Li, Tong Wu and Yixin He

Drones 2024, 8(2), 63; https://doi.org/10.3390/drones8020063 - 13 Feb 2024

Viewed by 1248

Abstract

Integrating the relaying drone and non-orthogonal multiple access (NOMA) technique into post-disaster emergency communications (PDEComs) is a promising way to accomplish efficient network recovery. Motivated by the above, by optimizing the drone three-dimensional (3D) deployment optimization and spectrum allocation, this paper investigates a quality of service (QoS)-driven sum rate maximization problem for drone-and-NOMA-enhanced PDEComs that aims to improve the data rate of cell edge users (CEUs). Due to the non-deterministic polynomial (NP)-hard characteristics, we first decouple the formulated problem. Next, we obtain the optimal 3D deployment with the aid of a long short-term memory (LSTM)-based recurrent neural network (RNN). Then, we transform the spectrum allocation problem into an optimal matching issue, based on which the Hungarian algorithm is employed to solve it. Finally, the simulation results show that the presented scheme has a significant performance improvement in the sum rate compared with the state-of-the-art works and benchmark scheme. For instance, by adopting the NOMA technique, the sum rate can be increased by 9.72% and the needs of CEUs can be satisfied by enabling the relaying drone. Additionally, the convergence, complexity, and performance gap caused by iterative optimization are discussed and analyzed. Full article

(This article belongs to the Special Issue UAV-Assisted Intelligent Vehicular Networks 2nd Edition)

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