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

Ahmed Elzanaty; Jiuyu Liu; Anna Guerra; Francesco Guidi; Yi Ma; Rahim Tafazolli

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arXiv · 2310.06604

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

Ahmed Elzanaty·Jiuyu Liu·Anna Guerra·Francesco Guidi·Yi Ma·Rahim Tafazolli

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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.

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Ahmed Elzanaty, Jiuyu Liu, Anna Guerra, Francesco Guidi, Yi Ma, Rahim Tafazolli. 2024-05-19. Near and Far Field Model Mismatch: Implications on 6G Communications, Localization, and Sensing. https://arxiv.org/abs/2310.06604

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