Hybrid Spherical- and Planar-Wave Channel Modeling and Estimation for Terahertz Integrated UM-MIMO and IRS Systems

Integrated ultra-massive multiple-input multiple-output (UM-MIMO) and intelligent reflecting surface (IRS) systems are promising for 6G and beyond Terahertz (0.1-10 THz) communications, to effectively bypass the barriers of limited coverage and line-of-sight blockage. However, excessive dimensions o...

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Bibliographic Details
Published in:IEEE transactions on wireless communications 2023-12, Vol.22 (12), p.1-1
Main Authors: Chen, Yuhang, Li, Renwang, Han, Chong, Sun, Shu, Tao, Meixia
Format: Article
Language:English
Subjects:
Algorithms
Channel estimation
Channel modeling
Channel models
Estimation
Far fields
Line of sight communication
MIMO communication
Multiplexing
Near fields
Pulse width modulation
Space division multiplexing
Spatial multiplexing gain
Spherical waves
Terahertz integrated ultra-massive multiple-input-multiple-output (UM-MIMO) and intelligent reflecting surface (IRS) systems
Wireless communication
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Summary:Integrated ultra-massive multiple-input multiple-output (UM-MIMO) and intelligent reflecting surface (IRS) systems are promising for 6G and beyond Terahertz (0.1-10 THz) communications, to effectively bypass the barriers of limited coverage and line-of-sight blockage. However, excessive dimensions of UM-MIMO and IRS enlarge the near-field region, while strong THz channel sparsity in the far-field is detrimental to spatial multiplexing. Moreover, channel estimation (CE) requires recovering the large-scale channel from severely compressed observations due to limited RF-chains. To tackle these challenges, a hybrid spherical- and planar-wave channel model (HSPM) is introduced for the cascaded channel of the integrated system. The spatial multiplexing gains under near-field and far-field regions are analyzed, which are found to be limited by the segmented channel with a lower rank. Furthermore, a compressive sensing-based CE framework is developed, including a sparse channel representation method, a separate-side estimation (SSE) and a dictionary-shrinkage estimation (DSE) algorithms. Numerical results verify the effectiveness of the HSPM, the capacity of which is only 5 × 10 -4 bits/s/Hz deviated from that obtained by the ground-truth spherical-wave-model, with 256 elements. While the SSE achieves improved accuracy for CE than benchmark algorithms, the DSE is more attractive in noisy environments, with 1 dB lower normalized-mean-square error than SSE.
ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2023.3273221