Near or far: On determining the appropriate channel estimation strategy in cross-field communication

TL;DR

This paper introduces a hidden Markov model-based approach to accurately determine whether near- or far-field channel estimation strategies should be used in next-generation wireless systems with ultra-massive MIMO and high-frequency bandwidths.

Contribution

It proposes a novel method using a hidden Markov model to improve the accuracy of selecting the correct channel estimation strategy in cross-field scenarios.

Findings

High success rate in determining the appropriate channel estimation strategy

Effective use of pair-wise power differences for region indicators

Enhanced accuracy over existing methods

Abstract

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.