RIS Beam Calibration for ISAC Systems: Modeling and Performance Analysis

TL;DR

This paper develops and analyzes realistic beam models for RIS-assisted ISAC systems, proposing calibration algorithms to improve localization accuracy by addressing practical hardware non-idealities.

Contribution

It introduces three comprehensive beam models considering real-world non-idealities and develops calibration algorithms to enhance localization performance in RIS-based ISAC systems.

Findings

Models accurately reconstruct measured beam patterns

Calibration algorithms effectively estimate model parameters

Realistic modeling improves localization accuracy

Abstract

High-accuracy localization is a key enabler for integrated sensing and communication (ISAC), playing an essential role in various applications such as autonomous driving. Antenna arrays and reconfigurable intelligent surface (RIS) are incorporated into these systems to achieve high angular resolution, assisting in the localization process. However, array and RIS beam patterns in practice often deviate from the idealized models used for algorithm design, leading to significant degradation in positioning accuracy. This mismatch highlights the need for beam calibration to bridge the gap between theoretical models and real-world hardware behavior. In this paper, we present and analyze three beam models considering several key non-idealities such as mutual coupling, non-ideal codebook, and measurement uncertainties. Based on the models, we then develop calibration algorithms to estimate the model parameters that can be used for future localization tasks. This work evaluates the effectiveness of the beam models and the calibration algorithms using both theoretical bounds and real-world beam pattern data from an RIS prototype. The simulation results show that the model incorporating combined impacts can accurately reconstruct measured beam patterns. This highlights the necessity of realistic beam modeling and calibration to achieve high-accuracy localization.