Efficient Resource Allocation for Backhaul-Aware Unmanned Air Vehicles-to-Everything (U2X)

Area of Science:

• Telecommunications Engineering
• Network Resource Management
• Aerial Robotics

Background:

• Unmanned Aerial Vehicles (UAVs) offer enhanced coverage and connectivity in telecommunications.
• Layer-based UAV deployment improves inter-entity communication.
• Limited research addresses resource allocation for layered UAV-to-everything (U2X) systems.

Purpose of the Study:

• To address the critical issue of resource allocation in layered UAV networks for U2X.
• To determine optimal data transfer strategies among UAVs for energy conservation and successful resource allocation.
• To enhance the efficiency of backhaul-aware U2X communications.

Main Methods:

• Development of a resource allocation strategy based on mutual-agreement reward theory.
• Utilization of Minkowski distance as a key metric for decision-making.
• Performance evaluation through extensive Monte-Carlo simulations.

Main Results:

• The proposed method effectively optimizes resource allocation in layered UAV networks.
• Demonstrated significant energy conservation through optimal transfer decisions.
• Increased the overall probability of successful resource allocation for U2X.

Conclusions:

• The mutual-agreement based reward theory with Minkowski distance provides an efficient solution for U2X resource allocation.
• Layered UAV deployment combined with optimized resource management enhances telecommunication capabilities.
• This research paves the way for more efficient and sustainable UAV-enabled communication systems.