Robust Localization in OFDM-Based Massive MIMO through Phase Offset Calibration
Abstract
Accurate localization in Orthogonal Frequency Division Multiplexing (OFDM)-based massive Multiple-Input Multiple-Output (MIMO) systems depends critically on phase coherence across subcarriers and antennas. However, practical systems suffer from frequency-dependent and (spatial) antenna-dependent phase offsets, degrading localization accuracy. This paper analytically studies the impact of phase incoherence on localization performance under a static User Equipment (UE) and Line-of-Sight (LoS) scenario. We use two complementary tools. First, we derive the Cram\'er-Rao Lower Bound (CRLB) to quantify the theoretical limits under phase offsets. Then, we develop a Spatial Ambiguity Function (SAF)-based model to characterize ambiguity patterns. Simulation results reveal that spatial phase offsets severely degrade localization performance, while frequency phase offsets have a minor effect in the considered system configuration. To address this, we propose a robust Channel State Information (CSI) calibration framework and validate it using real-world measurements from a practical massive MIMO testbed. The experimental results confirm that the proposed calibration framework significantly improves the localization Root Mean Squared Error (RMSE) from 5 m to 1.2 cm, aligning well with the theoretical predictions.
Keywords
Cite
@article{arxiv.2601.14244,
title = {Robust Localization in OFDM-Based Massive MIMO through Phase Offset Calibration},
author = {Qing Zhang and Adham Sakhnini and Robbert Beerten and Haoqiu Xiong and Zhuangzhuang Cui and Yang Miao and Sofie Pollin},
journal= {arXiv preprint arXiv:2601.14244},
year = {2026}
}
Comments
Accepted to IEEE International Symposium on Joint Communications & Sensing (JC&S) 2026; recipient of the Best Student Paper Award