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

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arxiv 2310.06604 v2 pith:BEF3LX6Q submitted 2023-10-10 eess.SP cs.ITmath.IT

classification eess.SPcs.ITmath.IT
keywords modelsperformancelocalizationmismatchsensingaccuracycommunicationimplications
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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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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Impact of Model Mismatch on DOA Estimation with MUSIC: Near-Field and Far-Field

    eess.SP 2025-02 conditional novelty 4.0 of 10

    Using the far-field model in the near-field under-estimates MUSIC DOA errors, while near-field MUSIC estimates range accurately only below the Fraunhofer distance.

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