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arXiv · 2508.17526

Near-Field Integrated Imaging and Communication in Distributed MIMO Networks

Kangda Zhi·Tianyu Yang·Shuangyang Li·Yi Song·Amir Rezaei·Giuseppe Caire
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Abstract

In this work, we propose a general framework for wireless imaging in distributed MIMO wideband communication systems, considering multi-view non-isotropic targets and near-field propagation effects. For indoor scenarios where the objective is to image small-scale objects with high resolution, we propose a range migration algorithm (RMA)-based scheme using three kinds of array architectures: the full array, boundary array, and distributed boundary array. With non-isotropic near-field channels, we establish the Fourier transformation (FT)-based relationship between the imaging reflectivity and the distributed spatial-domain signals and discuss the corresponding theoretical properties. Next, for outdoor scenarios where the objective is to reconstruct the large-scale three-dimensional (3D) environment with coarse resolution, we propose a sparse Bayesian learning (SBL)-based algorithm to solve the multiple measurement vector (MMV) problem, which further addresses the non-isotropic reflectivity across different subcarriers. Numerical results demonstrate the effectiveness of the proposed algorithms in acquiring high-resolution small objects and accurately reconstructing large-scale environments.

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Kangda Zhi, Tianyu Yang, Shuangyang Li, Yi Song, Amir Rezaei, Giuseppe Caire. 2025-08-24. Near-Field Integrated Imaging and Communication in Distributed MIMO Networks. https://arxiv.org/abs/2508.17526

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