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arXiv · 2310.18180

DPSS-based Codebook Design for Near-Field XL-MIMO Channel Estimation

Shicong Liu·Xianghao Yu·Zhen Gao·Derrick Wing Kwan Ng
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Abstract

Future sixth-generation (6G) systems are expected to leverage extremely large-scale multiple-input multiple-output (XL-MIMO) technology, which significantly expands the range of the near-field region. While accurate channel estimation is essential for beamforming and data detection, the unique characteristics of near-field channels pose additional challenges to the effective acquisition of channel state information. In this paper, we propose a novel codebook design, which allows efficient near-field channel estimation with significantly reduced codebook size. Specifically, we consider the eigen-problem based on the near-field electromagnetic wave transmission model. Moreover, we derive the general form of the eigenvectors associated with the near-field channel matrix, revealing their noteworthy connection to the discrete prolate spheroidal sequence (DPSS). Based on the proposed near-field codebook design, we further introduce a two-step channel estimation scheme. Simulation results demonstrate that the proposed codebook design not only achieves superior sparsification performance of near-field channels with a lower leakage effect, but also significantly improves the accuracy in compressive sensing channel estimation.

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Shicong Liu, Xianghao Yu, Zhen Gao, Derrick Wing Kwan Ng. 2023-10-27. DPSS-based Codebook Design for Near-Field XL-MIMO Channel Estimation. https://arxiv.org/abs/2310.18180

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