Joint Power Control and Time Allocation for UAV-Assisted IoV Networks Over Licensed and Unlicensed Spectrum

• Published in: IEEE internet of things journal Vol. 11; no. 1; p. 1
• Main Authors: Su, Yuhan, Huang, Lianfen, Liwang, Minghui
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Autonomous aerial vehicles; convex optimization; Frequencies; Indexes; Interference; Interference suppression; Internet of Vehicles; Internet of Vehicles (IoV); Optimization; Power control; Resource allocation; Resource management; Roadsides; Unmanned aerial vehicle (UAV); Unmanned aerial vehicles; Wireless fidelity
• ISSN: 2327-4662; 2327-4662
• DOI: 10.1109/JIOT.2023.3291370

Unmanned Aerial Vehicles (UAVs) have attracted massive attentions in Internet of Vehicles (IoV) networks to support the communications among roadside units (RSUs) and IoV users. In UAV-assisted IoV systems, UAVs and RSUs generally work within the same frequency band to improve the system spectral utilization efficiency, limited by the lack of spectrum resources, which, however, can cause mutual interference. To cope with the interference and increase the capacity of UAV-assisted IoV systems, this paper considers to distribute part of the data traffic from the ground IoV system to the unlicensed spectrum. Specifically, we consider a heterogeneous communication scenario, in which a UAV-assisted IoV system and a Wi-Fi system coexist well: the RSUs can properly occupy unlicensed spectrum to increase the capacity of the UAV-assisted IoV system while mitigating interference between the UAVs and RSUs, without affecting the Wi-Fi system's communication performance. We then propose a joint power control and time allocation scheme for the UAV-assisted IoV system over licensed and unlicensed spectrum. Joint optimization method is used to obtain the optimal power and time allocation strategy to maximize the overall system capacity. Simulation results and comprehensive analysis have demonstrated the superior performance of the proposed scheme, as compared to the conventional and state-of-art resource allocation strategies.