Trajectories and Resource Management of Flying Base Stations for C-V2X

Area of Science:

• Computer Science
• Electrical Engineering
• Telecommunications

Background:

• Vehicular communication networks face challenges with incomplete device penetration and demanding application requirements.
• Existing cellular networks are not optimized for the dynamic and unpredictable nature of vehicular traffic.
• Unmanned Aerial Vehicles (UAVs) offer a flexible platform for mobile base stations to augment network coverage.

Purpose of the Study:

• To propose and evaluate an integrated aerial-terrestrial network architecture for Cellular-Vehicle-to-Anything (C-V2X) applications.
• To investigate the use of UAVs equipped with C-V2X capabilities for extended sensing applications.
• To design a UAV trajectory optimization strategy that considers radio resource (RR) assignment.

Main Methods:

• Developed a hybrid network model combining terrestrial infrastructure with a UAV-based mobile base station.
• Proposed a UAV trajectory design algorithm that optimizes for radio resource allocation.
• Conducted simulations in a realistic vehicular scenario, varying RR availability and the number of active vehicles.

Main Results:

• The integrated aerial-terrestrial system demonstrated significant gains in network throughput.
• A notable increase in the percentage of served users was observed with the UAV's presence.
• Performance improvements were quantified against a baseline scenario without UAV integration.

Conclusions:

• Integrating UAVs as mobile base stations effectively enhances C-V2X communication capabilities.
• The proposed trajectory design and RR assignment strategy improve system performance.
• UAVs provide a viable solution to address connectivity gaps and traffic variability in vehicular networks.