Near and Far Field Model Mismatch: Implications on 6G Communications, Localization, and Sensing

TL;DR

This paper examines how the mismatch between near-field and far-field models in 6G systems affects performance in communication, localization, and sensing, highlighting the importance of model choice for system design.

Contribution

It provides a detailed analysis of NF and FF model mismatches in 6G, offering insights into their impact on system performance and guiding design choices.

Findings

Model mismatch degrades localization accuracy

Communication efficiency is affected by NF/FF disparity

Numerical analysis confirms performance impacts

Abstract

The upcoming 6G technology is expected to operate in near-field (NF) radiating conditions thanks to high-frequency and electrically large antenna arrays. Although several studies have already addressed this possibility, it is worth noting that NF models introduce higher complexity, the justification for which is not always evident in terms of performance improvements. This article investigates the implications of the mismatch between NF and far-field (FF) models concerning communication, localization, and sensing systems. Such disparity can lead to a degradation of performance metrics such as sensing and localization accuracy and communication efficiency. By exploring the effects of mismatches between NF and FF models, this study seeks to revolve around the challenges faced by system designers, offering insights about the balance between model accuracy and achievable performance. Finally, we conduct a numerical performance analysis to verify the impact of the mismatch between NF and FF models.