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

被引:0
作者
Xing, Hongbo [1 ]
Zhang, Yuxiang [1 ]
Zhang, Jianhua [1 ]
Xu, Huixin [1 ]
Liu, Guangyi [2 ]
Wang, Qixing [2 ]
机构
[1] Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Beijing 100876, Peoples R China
[2] China Mobile Res Inst, Future Res Lab, Beijing 100053, Peoples R China
基金
美国国家科学基金会; 北京市自然科学基金; 中国国家自然科学基金; 国家重点研发计划;
关键词
Training; Discrete Fourier transforms; Antennas; Channel models; Vectors; Closed-form solutions; Channel estimation; Apertures; Solid modeling; Phased arrays; Near-field; extremely large-scale array (XL-array); wave-number domain; the principle of stationary phase;
D O I
10.1109/TVT.2025.3531041
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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's 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.
引用
收藏
页码:8267 / 8272
页数:6
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