In-vivo MIMO Channel Characteristics Analysis and Modeling Based on Skin-fat Model at Terahertz Frequency
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摘要: 为探究太赫兹(THz)频段体内多输入多输出(MIMO)通信系统的传输特性，该文在0.8～1.2 THz下构建了精确的皮肤-脂肪模型，对皮肤-脂肪模型中垂直方向和水平方向的链路进行全波电磁仿真，分析太赫兹体内信道特性，建立路径损耗模型。首先，结合太赫兹频段人体组织的介电特性和人体皮肤的解剖学结构构建皮肤-脂肪模型。其次，对比分析了3条链路的路径损耗和阴影衰落，提出带有等效吸收因子的太赫兹体内路径损耗模型。最后，对3条链路的莱斯K因子、均方根时延扩展、MIMO容量进行分析。仿真分析表明，带有等效吸收因子的太赫兹体内路径损耗模型可以更准确地描述加长距离垂直链路2的路径损耗，发射端在体表可以增强MIMO容量。该文的工作可以为太赫兹体内通信系统的设计和优化提供参考。Abstract: To investigate transmission characteristics of in-vivo Mmultiple Input Multiple Output (MIMO) communication systems at TeraHertz (THz) frequency, a precise skin-fat model is constructed at 0.8～1.2 THz. Full wave electromagnetic simulations are conducted on the vertical and horizontal links in the skin-fat model, the characteristics of terahertz in-vivo channel are analyzed, and a terahertz in-vivo path loss model is established. Firstly, the skin-fat model is constructed based on the dielectric properties of human tissue at terahertz frequency and the anatomical structure of human skin. Secondly, the path loss and shadow fading of the three links are compared and analyzed, and a terahertz in-vivo path loss model with equivalent absorption factor is proposed. Finally, the Rice K factor, the root mean square delay extension, and the MIMO capacity of the three links are analyzed. The results demonstrate that the terahertz in-vivo path loss model with equivalent absorption factor can more accurately describe the path loss of extended distance in vertical link 2, on-body transmitter can provide enhancement in MIMO capacity. This work can give an insight into the design and optimization of THz in-vivo communication systems.
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表 2 水和血液的双德拜模型
$ {\varepsilon _s} $ $ {\varepsilon _2} $ $ {\varepsilon _\infty } $ $ {\tau _1} $ (ps) $ {\tau _2} $ (ps) 水 78.8 6.6 4.1 10.6 0.18 血液 130.0 3.8 2.1 14.4 0.10 
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表 3 路径损耗模型的拟合参数
CI 模型 FI模型 CIF模型 ABG模型 PLE RMSE $ \alpha $ $ \beta $ RMSE PLE b RMSE $ \alpha $ $ \beta $ $ \gamma $ RMSE 垂直链路1 6.15 4.52 38.70 3.40 2.42 6.29 0.29 5.89 3.35 4.91 5.10 4.48 垂直链路2 5.35 5.49 17.28 4.91 5.60 5.51 0.66 5.36 4.72 –51.14 10.38 5.39 水平链路 6.48 4.93 37.92 3.87 3.17 6.90 1.08 5.77 4.98 –95.96 18.23 5.25
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表 4 3条链路修正的路径损耗模型的拟合参数
修正的FI模型 修正的ABG模型 $ {\mu _{{\text{abs}}}} $ $ \alpha $ RMSE $ {\mu _{{\text{abs}}}} $ $ \beta $ $ \gamma $ RMSE 垂直链路1 $ 5.242 \times {10^{ - 3}} $ 47.02 2.611 $ 6.604 \times {10^{{{ - }}3}} $ 11.59 5.10 4.52 垂直链路2 $ 1.236 \times {10^{ - 2}} $ 32.62 4.741 $ 1.129 \times {10^{{{ - }}2}} $ –36.55 10.38 4.83 水平链路 $ 8.879 \times {10^{{{ - }}3}} $ 47.39 3.259 $ 1.407 \times {10^{{{ - }}2}} $ –80.81 18.23 5.38
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