The use of ultra-massive multiple-input multiple-output and high-frequency large bandwidth systems is likely in the next-generation wireless communication systems. In such systems, the user moves between near- and far-field regions, and consequently, the channel estimation will need to be carried out in the cross-field scenario. Channel estimation strategies have been proposed for both near- and far-fields, but in the cross-field problem, the first step is to determine whether the near- or far-field is applicable so that an appropriate channel estimation strategy can be employed. In this work, we propose using a hidden Markov model over an ensemble of region estimates to enhance the accuracy of selecting the actual region. The region indicators are calculated using the pair-wise power differences between received signals across the subarrays within an array-of-subarrays architecture. Numerical results show that the proposed method achieves a high success rate in determining the appropriate channel estimation strategy.

翻译：在下一代无线通信系统中，超大规模多输入多输出和高频大带宽系统的应用将成为可能。在此类系统中，用户将在近场与远场区域间移动，因此信道估计需在跨场场景下进行。针对近场和远场均已提出相应的信道估计策略，但在跨场问题中，首要步骤是判定适用近场还是远场模型，以便采用合适的信道估计策略。本研究提出在区域估计集合上应用隐马尔可夫模型，以提高实际区域选择的准确性。区域指示器通过子阵列架构内各子阵列间接收信号的两两功率差计算得出。数值结果表明，所提方法在确定合适信道估计策略方面具有较高的成功率。