Modeling and Analysis of OFDM-based 5G/6G Localization under Hardware Impairments

TL;DR

This paper models hardware impairments in mmWave 5G/6G systems and analyzes their impact on localization accuracy and communication performance, highlighting the importance of considering HWIs at high frequencies.

Contribution

It provides a comprehensive modeling and analysis framework for HWIs in mmWave MIMO systems, assessing their effects on localization and communication performance.

Findings

Different HWIs cause varying degradation in angle and delay estimation.

Certain impairments significantly worsen symbol error rate.

Modeling reveals dominant impairment factors affecting localization accuracy.

Abstract

Localization is envisioned as a key enabler to satisfy the requirements of communication and context-aware services in the fifth/sixth generation (5G/6G) communication systems. User localization can be achieved based on delay and angle estimation using uplink/downlink pilot signals. However, hardware impairments (HWIs) (such as phase noise and mutual coupling) distort the signals at both the transmitter and receiver sides and thus affect the localization performance. While this impact can be ignored at lower frequencies with less severe HWIs, and less stringent localization requirements, modeling and analysis efforts are needed for high-frequency bands to assess degradation in localization accuracy due to HWIs. In this work, we model various types of impairments for a mmWave multiple-input-multiple-output communication system and conduct a misspecified Cram\'er-Rao bound analysis to evaluate HWI-induced performance losses in terms of angle/delay estimation and the resulting 3D position/orientation estimation error. We also investigate the effect of individual and overall HWIs on communication in terms of symbol error rate (SER). Our extensive simulation results demonstrate that each type of HWI leads to a different level of degradation in angle and delay estimation performance, and the prominent impairment factors on delay estimation will have a dominant negative effect on SER.