High-Efficient Near-Field Channel Characteristics Analysis for Large-Scale MIMO Communication Systems

Large-scale multiple-input multiple-output (MIMO) holds great promise for the fifth-generation (5G) and future communication systems. For near-field scenarios, the spherical wavefront model is commonly utilized to depict the propagation characteristics of large-scale MIMO communication channels. How...

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Bibliographic Details
Published in:IEEE internet of things journal 2025, p.1-1
Main Authors: Jiang, Hao, Shi, Wangqi, Chen, Xiao, Zhu, Qiuming, Chen, Zhen
Format: Article
Language:English
Subjects:
Antenna arrays
Antennas
channel modeling complexity
Channel models
Computational complexity
Computational modeling
Internet of Things
large-scale MIMO
MIMO communication
Near-field communication
Receiving antennas
subarray decomposition
Vectors
Wireless communication
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Summary:Large-scale multiple-input multiple-output (MIMO) holds great promise for the fifth-generation (5G) and future communication systems. For near-field scenarios, the spherical wavefront model is commonly utilized to depict the propagation characteristics of large-scale MIMO communication channels. However, employing this modeling method necessitates the computation of angle and distance parameters for each antenna element, resulting in challenges regarding computational complexity. To solve this problem, we introduce a subarray decomposition scheme with the purpose of dividing the whole large-scale antenna array into several smaller subarrays. This scheme is implemented in the near-field channel modeling for large-scale MIMO communications between the base station (BS) and mobile receiver (MR). Essential channel propagation statistics, such as spatial cross-correlation functions (CCFs), temporal auto-correlation functions (ACFs), frequency correlation functions (CFs), and channel capacities, are derived and discussed. A comprehensive analysis is conducted to investigate the influences of the height of the BS, motion characteristics of the MR, and antenna configurations on the channel statistics. The proposed channel model criterions, such as the modeling precision and computational complexity, are also theoretically compared. Numerical results demonstrate the effectiveness of the presented communication model in obtaining a good tradeoff between modeling precision and computational complexity.
ISSN:2327-4662
2327-4662
DOI:10.1109/JIOT.2024.3496434