Vehicle-to-Everything (V2X) communications refers to an intelligent and connected vehicular network where all vehicles and infrastructure systems are interconnected with each other. Data dissemination is playing an increasingly significant role in enhancing the network connectivity and data transmission performance. However, conventional scenarios and protocols cannot satisfy the growing pluralistic and superior quality of services (QoS) requirements of included vehicles. Therefore, in this paper, we propose a novel unmanned aerial vehicle (UAV)-assisted data dissemination protocol with proactive caching at the vehicles and an advanced file sharing strategy for revolutionizing communications. Specifically, in the proactive caching phase, we employ UAVs to act as flying base stations (BSs) for information interactions. Considering the time-variant network topology, we further propose a spatial scheduling (SS) algorithm for the trajectory optimization of each UAV, which can expedite the caching process and boost the system throughput. Then in the file sharing phase, based on the previous caching status, we provide a relay ordering algorithm to enhance the network transmission performance. Numerical results verify that our proposed UAV-assisted data transmission protocol can achieve a desirable system performance in terms of the downloading process, network throughput, and average data delivery delay.
|Original language||English (US)|
|Title of host publication||2019 IEEE Global Communications Conference, GLOBECOM 2019 - Proceedings|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|State||Published - Dec 2019|
|Event||2019 IEEE Global Communications Conference, GLOBECOM 2019 - Waikoloa, United States|
Duration: Dec 9 2019 → Dec 13 2019
|Name||2019 IEEE Global Communications Conference, GLOBECOM 2019 - Proceedings|
|Conference||2019 IEEE Global Communications Conference, GLOBECOM 2019|
|Period||12/9/19 → 12/13/19|
Bibliographical noteFunding Information:
ACKNOWLEDGEMENT This work was in part supported by the Ministry National Key Research and Development Project under Grant 2017YFE0121400, the National Science and Technology Major Project under Grant 2018ZX03001031, the Major Project from Beijing Municipal Science and Technology Commission under Grant Z181100003218007, Shenzhen Fundamental Research Fund under Grant No. JCYJ20170411102217994 and Guangdong province under grant No. 2017ZT07X152, the National Natural Science Foundation of China under Grants 61622101 and 61571020, and the National Science Foundation under Grant CPS-1932413 and ECCS-1935915.
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