Channel Model Mismatch Analysis for XL-MIMO Systems from a Localization Perspective

TL;DR

This paper analyzes how model mismatches like non-stationarity, spherical wave effects, and beam squint impact localization accuracy in XL-MIMO systems, using the MCRB to quantify errors caused by simplified models.

Contribution

It introduces a framework using the MCRB to evaluate the impact of various channel model impairments on localization performance in XL-MIMO systems.

Findings

SNS has minimal impact on localization accuracy

SWM significantly affects performance at short distances

BSE becomes more critical at large distances

Abstract

Radio localization is applied in high-frequency (e.g., mmWave and THz) systems to support communication and to provide location-based services without extra infrastructure. {For solving localization problems, a simplified, stationary, narrowband far-field channel model is widely used due to its compact formulation.} However, with increased array size in extra-large MIMO systems and increased bandwidth at upper mmWave bands, the effect of channel spatial non-stationarity (SNS), spherical wave model (SWM), and beam squint effect (BSE) cannot be ignored. In this case, localization performance will be affected when an inaccurate channel model deviating from the true model is adopted. In this work, we employ the MCRB (misspecified Cram\'er-Rao lower bound) to lower bound the localization error using a simplified mismatched model while the observed data is governed by a more complex true model. The simulation results show that among all the model impairments, the SNS has the least contribution, the SWM dominates when the distance is small compared to the array size, and the BSE has a more significant effect when the distance is much larger than the array size.