Extremely large-scale massive MIMO (XL-MIMO) is a promising technique for future 6G communications. The sharp increase of BS antennas leads to the unaffordable channel estimation overhead. Existing low-overhead channel estimation schemes are based on the far-field or near-field channel model. However, the far-field or near-field channel model mismatches the practical XL-MIMO channel feature, where some scatters are in the far-field region while others may locate in the near-field region, i.e., hybrid-field channel. Thus, existing far-field and near-field channel estimation schemes cannot be directly used to accurately estimate the hybrid-field XL-MIMO channel. To solve this problem, we propose an efficient hybrid-field channel estimation scheme by accurately modeling the XL-MIMO channel. Specifically, we firstly reveal the hybrid-field channel feature of the XL-MIMO channel. Then, we propose a hybrid-field channel model to capture this feature, which contains both the far-field and near-field path components. Finally, we propose a hybrid-field channel estimation scheme, where the far-field and near-field path components are respectively estimated. Simulation results show the proposed scheme performs better than existing schemes.

中文翻译：

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超大规模大规模 MIMO 的信道估计：远场、近场还是混合场？

超大规模大规模 MIMO (XL-MIMO) 是未来 6G 通信的一项很有前途的技术。BS天线的急剧增加导致难以承受的信道估计开销。现有的低开销信道估计方案基于远场或近场信道模型。然而，远场或近场信道模型与实际的 XL-MIMO 信道特征不匹配，其中一些散射位于远场区域而其他可能位于近场区域，即混合场信道。因此，现有的远场和近场信道估计方案不能直接用于精确估计混合场XL-MIMO信道。为了解决这个问题，我们通过对 XL-MIMO 信道进行精确建模，提出了一种有效的混合场信道估计方案。具体来说，我们首先揭示了 XL-MIMO 信道的混合场信道特性。然后，我们提出了一个混合场通道模型来捕捉这个特征，其中包含远场和近场路径分量。最后，我们提出了一种混合场信道估计方案，其中分别估计远场和近场路径分量。仿真结果表明，该方案的性能优于现有方案。