Enhancing Localization and Synchronization Through Neural Networks

This letter improves the interpretability of neural networks (NNs) while designing a low-complexity, yet efficient, joint localization-synchronization method. It focuses on reconfigurable intelligent surface (RIS)-assisted millimeter-wave (mmwave) communication systems. The goal is to achieve jointly accurate localization and synchronization, even under real-world conditions with hardware impairments (HWI). A novel NNs-based method is proposed to counteract HWI with reduced complexity. The mathematical framework for NNs interpretability has been investigated, and a mathematical expression for the mean squared error (MSE) of the solution is analytically derived. Furthermore, the simulation results confirm the reliability of the approach, demonstrating effective performance and validating the accuracy of the MSE derivation across various scenarios.