Practical Challenge and Solution for IRS-Aided Indoor Localization System

Intelligent reflecting surfaces (IRS) is a novel integrated sensing and communication technology that can manipulate the propagation of wireless signals. However, existing IRS-based sensing systems require directional antennas for signal transmission, incompatible with commercial WiFi devices. This paper proposes an IRS-aided localization system using omnidirectional antennas and reveals two critical challenges in practical deployment. First, the accurate distance between the IRS and the transmitter is needed for IRS codebook design, but practice measurements invariably introduce centimeter-level bias, which seriously affects localization accuracy. We derive a linear relationship between measurement bias and localization error for calibration. Second, only relative IRS phase change under different bias voltages can be measurable, not the absolute phase offset, introducing an unknown fixed phase offset in reflections. We solve this challenge by eliminating the signals that are not related to the IRS. Experiments validate the proposed calibration techniques, proving that our system achieves high-precision passive localization.