室内毫米波大规模MIMO信道测量与特性分析

张宇; 张汉青; 杨松江; 张继良; 杨丹; 李黎明

doi:10.11999/JEIT260496

室内毫米波大规模MIMO信道测量与特性分析

doi: 10.11999/JEIT260496 cstr: 32379.14.JEIT260496

1.
东北大学信息科学与工程学院沈阳 110819
2.
浙大宁波理工学院信息科学与工程学院宁波 315100

基金项目: 国家自然科学基金项目(62573096,62401644)，辽宁省兴辽英才计划(XLYC2403116)，浙江省教育厅一般科研项目(Y202352276)

详细信息

作者简介:
张宇：男，硕士生，研究方向为毫米波信道测量

张汉青：男，博士生，研究方向为无线信道建模

杨松江：男，博士后，研究方向为无线信道测量与建模

张继良：男，教授，研究方向为智能无线环境

杨丹：女，教授，研究方向为电磁信号测量

李黎明：男，讲师，研究方向为通信调制技术及信号处理

通讯作者:
张继良　zhangjiliang1@mail.neu.edu.cn

中图分类号: TN929.5
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出版历程
- 收稿日期: 2026-04-23
- 修回日期: 2026-09-28
- 录用日期: 2026-09-28
- 网络出版日期: 2026-10-10

Channel Measurement and Characterization for Indoor Millimeter-Wave Massive MIMO

1.
School of Information Science and Engineering, Northeastern University, Shenyang 110819, China
2.
School of Information Science and Engineering, NingboTech University, Ningbo 315100, China

Funds: National Natural Science Foundation of China(62573096,62401644), LiaoNing Revitalization Talents Program (XLYC2403116), General Scientific Research Project of Department of Education of Zhejiang Province (Y202352276)

摘要

摘要: 为探究毫米波频段在室内复杂环境下的信道传播特性，丰富该频段下大规模MIMO信道实测数据库，该文在典型室内视距与非视距混合场景下开展了中心频率为32 GHz、带宽为16 GHz的超大带宽信道测量与特性分析。实验通过构建16×16虚拟接收阵列，结合矢量网络分析仪扫频测量，得到了多组视距与非视距的信道频率响应，获得了路径损耗、时延功率谱、均方根时延扩展及延迟-波数函数谱，并进一步对比评估了不同测量带宽下多径辅助定位的精度表现。结果表明，在时域特性上，视距信道能量集中于首达径与一次镜面多径分量，而非视距信道转变为由密集多径分量主导，呈现显著的能量长拖尾与较大的时延扩展；在空域特性上，延迟-波数谱验证了阵列的高角度分辨率。针对室内定位应用，16 GHz超大带宽的高时延分辨率能有效解耦密集的相邻多径，显著提升了目标多径参数提取的准确性，其单点定位精度显著优于较小带宽。该工作揭示了复杂室内环境的毫米波传播与多径演化规律，为未来室内通信系统的底层传输设计与高精度定位应用提供了关键的实测支撑。
- 信道测量与特性分析 /
- 毫米波 /
- 大规模MIMO /
- 超大带宽 /
- 室内场景
Abstract: Objective Millimeter-wave (mmWave) bands offer abundant spectrum resources, making them ideal for high-speed indoor transmission and high-precision sensing applications. However, lacking sufficient empirical validation from ultra-wideband measurements, the understanding of how dense multipath components (DMCs) affect channel sparsity and multipath parameter extraction in complex indoor Non-Line-of-Sight (NLOS) environments remains limited. This paper conducts a comprehensive channel measurement and characterization campaign to investigate physical propagation mechanisms and evaluate the indoor positioning potential of ultra-wideband massive MIMO systems. Methods A massive MIMO channel measurement platform is established using a Vector Network Analyzer. The system operates at a center frequency of 32 GHz with a 16 GHz bandwidth. On the receiver side, a precision turntable constructs a 16×16 virtual Uniform Rectangular Array (URA). The measurement campaign covers a typical indoor environment featuring both Line-of-Sight (LOS) and NLOS scenarios. Key channel characteristics, including path loss, power delay profile, delay spread, and delay-wavenumber spectrum, are extracted. Furthermore, a multipath-assisted single-point positioning framework based on virtual anchors is implemented to evaluate localization performance across different measurement bandwidths. Results and Discussions Measurement results reveal significant differences in multipath structures and energy distributions between LOS and NLOS channels. In the time domain, LOS channels exhibit strong spatiotemporal sparsity. Conversely, obstructed NLOS environments are dominated by DMCs due to severe physical blockage and complex multipath effects, resulting in significant energy tails and large delay spreads (Fig. 8, Fig. 10). Spatially, the delay-wavenumber spectrums confirm the high angular resolution for user separation (Fig. 11). Crucially, the comparative positioning experiments across different measured bandwidths demonstrate that the 16 GHz ultra-wideband effectively decouples dense adjacent multipath components, significantly improving the accuracy of multipath parameter extraction. This provides robust virtual anchors for multipath-assisted positioning. The 16 GHz system achieves a low mean positioning error of 0.052 m, showcasing significant robustness and accuracy advantages over the narrower 8 GHz and 4 GHz bandwidths (Table 5). Conclusions This study provides a systematic characterization of indoor mmWave massive MIMO channels. The results identify that channel sparsity is highly scenario-dependent, necessitating the inclusion of DMCs in future NLOS channel modeling. Moreover, the empirical localization analysis confirms that ultra-high spatiotemporal resolution is indispensable for robust indoor multipath extraction and positioning applications, providing a solid experimental foundation for next-generation network design.
- Channel measurement and characteristics, Millimeter-wave /
- Massive MIMO /
- Ultra-wideband /
- Indoor scenario /
- XXX

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图 1 室内信道测量平台

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图 2 虚拟均匀矩形接收阵列示意图

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图 3 直射场景实际测量环境

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图 4 直射场景测量环境平面图

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图 5 直射与非直射混合场景实际测量环境

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图 6 直射与非直射混合场景测量环境平面图

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图 7 收发距离与路径损耗的FI和CI模型拟合结果

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图 8 部分位置的时延功率谱

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图 9 不同场景下多径能量平均相对百分比拟合曲线

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图 10 不同频率下RMS时延扩展的概率分布函数

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图 11 部分位置的垂直、水平波数时延剖面

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表 1 测量平台设备参数

名称	参数
矢量网络分析仪	工作频率：32 GHz，带宽：16 GHz 发射功率：5 dBm 扫描点数：1601 IF带宽：1 kHz
低噪放大器	增益50 dB
射频线	长度5 m，插入损耗15 dB
接收阵列	16×16虚拟阵列，阵列间距3.5 mm

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表 2 LOS情况的FI和CI模型拟合参数

模型	$ \mathrm{PL}({d}_{0}) $	$ \alpha $	PLE	$ \sigma $	$ {A}^{2} $
CI FI	62.54 /	/ 60.96	1.286 1.671	1.07 0.68	0.9033 0.9647

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表 3 NLOS情况的FI和CI模型拟合参数

模型	$ \mathrm{PL}({d}_{0}) $	$ \alpha $	PLE	$ \sigma $	$ {A}^{2} $
CI FI	62.54 /	/ 72.22	2.926 1.472	1.22 0.92	0.0087 0.4383

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表 4 各时延范围相对功率分布

	0-20 ns	20-40 ns	40-60 ns	60-100 ns
Tx1	95.5%	3.1%	0.8%	0.7%
Tx5	69.4%	27.0%	2.7%	3.6%
Tx23	28.3%	18.2%	11.8%	13.0%

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表 5 不同测量带宽下LOS场景联合定位误差统计

统计指标(m)	16GHz	8GHz	4GHz
平均误差	0.052	0.092	0.132
均方根误差	0.055	0.135	0.178

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