Performance Evaluation of Array Calibration for Angle-of-Arrival-Based 5G Positioning

Future wireless networks will be uniquely equipped to offer precise positioning solutions, not least due to the continuously growing antenna aperture. However, in practice, hardware impairments can lead to a severe degradation of the localization accuracy. For the particular case of angle of arrival (AoA)-based positioning, the true antenna array phase response may diverge considerably from the ideal one, thereby negatively influencing AoA estimation without countermeasures. To address this issue, in this work we investigate antenna array response calibration and evaluate its impact on positioning accuracy leveraging an experimental 5G positioning setup. In our approach, we first make use of exponential smoothing to enable proper unwrapping of the arrays’ phase responses, which we then approximate applying weighted least squares (WLS) and Theil-Sen regression to real measurement data. Moreover, we account for the uneven distribution of the samples used for calibration by weighting them according to their estimated density. Results in a real-world environment demonstrate that our approach achieves a median 2D positioning error of 0.26 m, representing an improvement of roughly 40% over the non-calibrated baseline.