Joint Phase-Shift Design and Power Control for Near- and Far-Field Communications in Extremely Large RIS-Aided UAV Networks

This article investigates the integration of drone (aka UAV)-assisted networks with a reconfigurable intelligent surface (RIS) to enhance energy efficiency in near- and far-field communication scenarios. The coexistence of near-field and far-field communications introduces unique challenges in ensuring efficient resource allocation, managing interference, and meeting quality of service requirements for users. Primary users in the near-field areas have stronger signal links, while secondary users and primary far-field users face increased path loss and interference, necessitating sophisticated optimization strategies to balance their performance. To address these challenges, we propose a joint optimization framework for transmission power allocation and RIS phase-shift design. The framework aims to maximise energy efficiency while maintaining reliable communication for all user groups, leveraging the complementary characteristics of UAV and RIS technologies. The low-complexity optimization approach is developed, leveraging advanced successive convex approximation techniques and iterative algorithms. The framework consists of the Dinkelbach algorithm for the outer loop and a combination of linear and convex optimization algorithms for the inner loop. Linear programming is employed to handle the large number of variables, such as phase-reflecting coefficients, while convex programming is used to optimize power allocation in UAVs, with convergence guaranteed. Simulation results reveal significant energy efficiency gains compared to baseline methods, demonstrating the effectiveness of the proposed framework in managing the coexistence of near- and far-field communications. The findings underscore the importance of energy-efficient design in enabling scalable and sustainable UAV-assisted networks, offering valuable insights for the development of high-performance next-generation communication systems.