Mitigating Phase Errors to Improve Signal Quality in RIS-Assisted Satellite Communications

This research presents an advanced framework designed to enhance the received power in satellite-to-Earth communications by utilizing Reconfigurable Intelligent Surfaces (RIS), with a focus on mitigating phase errors that arise from hardware imperfections associated with RIS systems. A comprehensive analysis of the phase errors arising from these imperfections is conducted, leading to the development of a robust analytical model that quantitatively incorporates these errors into the assessment of received power evaluations. Subsequently, we propose a methodology to selectively exclude RIS elements that are prone to errors, thereby improving the phase alignment of the received signal and enhancing overall system efficiency. While this strategy leads to a marginal decrease in received power, Bayesian Optimization (BO) is employed to optimize the RIS configuration, maintaining the desired power levels and ensuring signal integrity. The research also delves into the complexities introduced by shadowing effects combined with phase errors. To address these compounded challenges, a decision-making framework utilizing targeted BO is introduced to dynamically optimize RIS configurations, enhancing system robustness and performance under adverse operational conditions. Numerical simulations validate the framework's efficacy in adaptively managing RIS elements, ensuring robust signal integrity and improved reception despite variations stemming from environmental and hardware factors. By addressing critical challenges in RIS-augmented satellite communications, this work highlights the transformative potential of adaptive optimization strategies in advancing the reliability and efficiency of next-generation wireless networks.