An Approximate Wave-Number Domain Expression for Near-Field XL-array Channel

Fuente: arXiv
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Main Authors: Xing, Hongbo, Zhang, Yuxiang, Zhang, Jianhua, Xu, Huixin, Liu, Guangyi, Wang, Qixing
Format: Preprint
Published: 2024
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_version_ 1866917925537972224
author Xing, Hongbo
Zhang, Yuxiang
Zhang, Jianhua
Xu, Huixin
Liu, Guangyi
Wang, Qixing
author_facet Xing, Hongbo
Zhang, Yuxiang
Zhang, Jianhua
Xu, Huixin
Liu, Guangyi
Wang, Qixing
contents As Extremely large-scale array (XL-array) technology advances and carrier frequency rises, the near-field effects in communication are intensifying. In near-field conditions, channels exhibit a diffusion phenomenon in the angular domain, existing research indicates that this phenomenon can be leveraged for efficient parameter estimation and beam training. However, the channel model in angular domain lacks closed-form analysis, making the time complexity of the corresponding algorithm high. To address this issue, this paper analyzes the near-field diffusion effect in the wave-number domain, where the wave-number domain can be viewed as the continuous form of the angular domain. A closed-form approximate wave-number domain expression is proposed, based on the Principle of Stationary Phase. Subsequently, we derive a simplified expression for the case where the user distance is much larger than the array aperture, which is more concise. Subsequently, we verify the accuracy of the proposed approximate expression through simulations and demonstrate its effectiveness using a beam training example. Results indicate that the beam training scheme, improved by the wave-number domain approximation model, can effectively estimate near-field user parameters and perform beam training using far-field DFT codebooks. Moreover, its performance surpasses that of existing DFT codebook-based beam training methods.
format Preprint
id arxiv_https___arxiv_org_abs_2406_11446
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle An Approximate Wave-Number Domain Expression for Near-Field XL-array Channel
Xing, Hongbo
Zhang, Yuxiang
Zhang, Jianhua
Xu, Huixin
Liu, Guangyi
Wang, Qixing
Signal Processing
As Extremely large-scale array (XL-array) technology advances and carrier frequency rises, the near-field effects in communication are intensifying. In near-field conditions, channels exhibit a diffusion phenomenon in the angular domain, existing research indicates that this phenomenon can be leveraged for efficient parameter estimation and beam training. However, the channel model in angular domain lacks closed-form analysis, making the time complexity of the corresponding algorithm high. To address this issue, this paper analyzes the near-field diffusion effect in the wave-number domain, where the wave-number domain can be viewed as the continuous form of the angular domain. A closed-form approximate wave-number domain expression is proposed, based on the Principle of Stationary Phase. Subsequently, we derive a simplified expression for the case where the user distance is much larger than the array aperture, which is more concise. Subsequently, we verify the accuracy of the proposed approximate expression through simulations and demonstrate its effectiveness using a beam training example. Results indicate that the beam training scheme, improved by the wave-number domain approximation model, can effectively estimate near-field user parameters and perform beam training using far-field DFT codebooks. Moreover, its performance surpasses that of existing DFT codebook-based beam training methods.
title An Approximate Wave-Number Domain Expression for Near-Field XL-array Channel
topic Signal Processing
url https://arxiv.org/abs/2406.11446