Data Aggregation in UAV-Aided Random Access for Internet of Vehicles
Lin Bai, Jiexun Liu, Jiaxing Wang, Rui Han, Jinho Choi
Abstract
Recently, the Internet of Vehicles (IoV) has been employed as an enabling technology for smart transportation, which can be further enhanced by integrating space–air–ground-integrated networks (SAGIN). Since the data packets of vehicular user equipments (VUEs) are generally short, random access is usually considered for VUEs to connect to the network. However, collisions caused by the multiple VUEs initiating random access simultaneously are inevitable. To relieve the performance degradation by collisions, data aggregation can be carried out in IoV, where aggregated packets can be relayed to a base station. In this article, we first propose an aggregators-aided random access scheme for IoV, where unmanned aerial vehicles (UAVs), as one of the key components in SAGIN, are deployed as data aggregators to help transmissions of VUEs. Then, a semi-Markov chain is used to analyze the average number of aggregated packets, and the metric of the average data to overhead ratio (ADOR) is presented to evaluate the efficiency of aggregation. Finally, the altitude of UAVs and the duration of data aggregation are optimized to maximize ADOR. By numerical simulations, the accuracy of the analysis as well as the effectiveness of the proposed scheme are validated.