Resource allocation and path planning for RSMA-enabled UAV-VLC networks considering UAV jitter

Area of Science:

• Wireless Communication
• Optical Communication
• Robotics

Background:

• Unmanned Aerial Vehicle (UAV)-assisted Visible Light Communication (VLC) is crucial for night-time applications.
• Limited UAV payload and high communication quality demands present significant challenges.
• Existing methods struggle to balance energy efficiency and transmission rates in dynamic UAV-VLC environments.

Purpose of the Study:

• To propose a novel rate-splitting multiple access (RSMA)-enabled UAV-VLC network model.
• To address challenges posed by jittering effects and imperfect channel state information (CSI).
• To optimize the network for minimal energy consumption and maximal transmission rate.

Main Methods:

• A multi-objective optimization problem was formulated and decomposed into path planning and power allocation sub-problems.
• Path planning utilized a hover point fine-tuning algorithm and simulated annealing (SA) for trajectory optimization.
• Power allocation employed linear fractional programming (LFP) and successive convex approximation (SCA) to ensure convexity.

Main Results:

• The proposed algorithms effectively optimized UAV trajectory and power allocation.
• The RSMA-enabled network demonstrated improved performance under considered constraints.
• Simulation results validated the proposed approach's effectiveness in balancing energy and rate.

Conclusions:

• The developed RSMA-enabled UAV-VLC framework effectively tackles communication quality and energy efficiency challenges.
• The integrated approach of path planning and power allocation provides a robust solution for UAV communication systems.
• This research offers a significant advancement in optimizing aerial communication networks for diverse applications.