超大规模MIMO阵列可视区域空间分布数据集

高锐锋; 苗艳春; 陈颖; 王珏; 张军; 韩瑜; 金石

doi:10.11999/JEIT231273

超大规模MIMO阵列可视区域空间分布数据集

doi: 10.11999/JEIT231273 cstr: 32379.14.JEIT231273

高锐锋¹,
苗艳春¹,
陈颖²,
王珏^2, ,,
张军³,
韩瑜⁴,
金石⁴

1.
南通大学交通学院南通 226019
2.
南通大学信息科学技术学院南通 226019
3.
南京邮电大学通信与信息工程学院南京 210042
4.
东南大学移动通信国家重点实验室南京 210096

基金项目: 国家自然科学基金 (62171240, 62001254)；江苏省高校自然科学基金 (22KJB510039)

详细信息

作者简介:
高锐锋：男，副教授，研究方向为无线通信、智能信息处理等

苗艳春：女，硕士生，研究方向为智能通信

陈颖：女，硕士生，研究方向为智能通信

王珏：男，副教授，研究方向为MIMO 系统及超大规模 MIMO 系统等

张军：男，教授，研究方向为大规模MIMO、人工智能通信等

韩瑜：女，副研究员，研究方向为超大规模MIMO、可见区域等

金石：男，教授，研究方向为6G移动通信理论与关键技术研究等

通讯作者:
王珏　wangjue@ntu.edu.cn

中图分类号: TN929.5
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出版历程
- 收稿日期: 2023-11-17
- 修回日期: 2024-04-30
- 网络出版日期: 2024-05-15
- 刊出日期: 2024-08-30

Visibility Region Spatial Distribution Dataset for XL-MIMO Arrays

1.
School of Transportation, Nantong University, Nantong 226019, China
2.
School of Information Science and Technology, Nantong University, Nantong 226019, China
3.
School of Communications and Information Engineering, Nanjing University of Post and Telecommunications, Nanjing 210042, China
4.
National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China

Funds: The National Natural Science Foundation of China (62171240, 62001254), The Natural Science Foundation of Jiangsu Provincial Universities (22KJB510039)

摘要

摘要: 可视区域(VR)信息可用于降低超大规模多输入多输出(XL-MIMO)系统传输设计复杂度，但现有理论分析与传输设计多基于简化的VR统计分布模型。为评估分析XL-MIMO在实际物理传播场景中的性能，该文公开了XL-MIMO阵列VR空间分布数据集，其由环境参数设置、射线追踪仿真、天线场强数据预处理和VR判定准则等步骤构建。该数据集针对典型城区无线传播场景，建立了用户位置采样与场强数据、VR数据之间的关联，总数据条目数量达上亿级。进一步对其中VR形态、VR分布进行了可视化展示与分析，并以基于VR的XL-MIMO用户接入协议为例，利用该数据集对其在真实传播场景中的性能进行了仿真，为该数据集的应用提供了典型样例。
- 超大规模MIMO /
- 可视区域 /
- 射线追踪 /
- 能量集中度 /
- 子阵列
Abstract: The Visibility Region (VR) information can be used to reduce the complexity in transmission design of EXtremely Large-scale massive Multiple-Input Multiple-Output (XL-MIMO) systems. Existing theoretical analysis and transmission design are mostly based on simplified VR models. In order to evaluate and analyze the performance of XL-MIMO in realistic propagation scenarios, this paper discloses a VR spatial distribution dataset for XL-MIMO systems, which is constructed by steps including environmental parameter setting, ray tracing simulation, field strength data preprocessing and VR determination. For typical urban scenarios, the dataset establishes the connections between user locations, field strength data, and VR data, with a total number of hundreds of millions of data entries. Furthermore, the VR distribution is visualized and analyzed, and a VR-based XL-MIMO user access protocol is taken as an example usecase, with its performance being evaluated with the proposed VR dataset.
- Extremely large-scale massive Multiple-Input Multiple-Output (MIMO) /
- Visibility region /
- Ray tracing /
- Energy concentration /
- Subarrays

HTML全文

图 1 VRD构建整体流程图

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图 2 实际3维城区场景以及采用射线追踪技术仿真得到的部分天线场强数据图

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图 3 所选用户位置示例

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图 4 两站点天线场强图

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图 5 site2不同VR判定准则下的VR示意图

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图 6 site2能量集中度80%时两种准则下的VR天线/子阵列数量分布图

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图 7 site2不同VR判定准则下的VR分布图

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图 8 两种随机接入协议的接入性能在所公布VRD下的仿真比较

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表 1 仿真参数设置

参数	参数设置
站点位置	场景内最高建筑物表面，site1: 150 m, site2: 50 m
天线类型及详细参数	每个站点200根天线(10×20)，天线间距3 m，全向天线，频率4800 MHz，发送功率1 W
天线序号	site1: 011～210，site2: 20011～20210
场强空间分辨率	1 m
用户高度	高度统一为1.5 m
传播模型	智能射线追踪

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1 天线能量集中度VR判定算法

输入：用户位置j天线场强数据$ {d_j}\left[ i \right] $，其中i表示天线标号；能量集中度P；初始化VR集合S_j为空；天线总数N_t
输出：用户j的VR集合S_j
1 计算用户j所在位置的场强和：${F^j} = \sum\nolimits_{i = 1}^{{N_{\mathrm{t}}}} {{d_j}\left[ i \right]} $；
2 用户j所能接收到的天线阵列上P (%)的能量，即阈值：${F^{j,P}} = {F^j} \times P$；
3 对数组$ {d_j}\left[ i \right] $按场强降序排序，生成新的2维数组${d'_j}\left[ {i,k} \right]$，其中i表示重新排序后的索引，k表示排序前天线的标号；
4 for (int t=0; t<=N_t; t++)
5 　${{\mathrm{sum}}} = {\text{sum}} + {d'_j}\left[ {i,k} \right]$；
6 　天线k加入集合S_j；
7 　if ${{\mathrm{sum}}} > {F^{j,P}}$
8 　　Break；
9 返回VR S_j。

下载: 导出CSV

表 2 数据集汇总表

数据集类型		数据集名称	数据集含义	数据量
天线场强空间分布数据集		Antenna_site1	site1天线场强信息	60071000
天线场强空间分布数据集		Antenna_site2	site2天线场强信息	60071000
VRD	基于天线能量集中度的VRD	S1_Antenna_user_80	site1下能量集中度80%的用户位置-天线VR构成信息	7702400
		S2_Antenna_user_80	site2下能量集中度80%的用户位置-天线VR构成信息	3515400
		S1_Antenna_VR	site1峰值下天线VR分布	464
		S2_Antenna_VR	site2峰值下天线VR分布	279
	基于子阵列能量集中度的VRD	Antenna_subarray	天线-子阵列映射数据集	400
		S1_user_sub_power_80	site1下能量集中度80%的用户位置-子阵列VR构成信息	547280
		S2_user_sub_power_80	site2下能量集中度80%的用户位置-子阵列VR构成信息	725660
		S1_Subarray_VR	site1峰值下子阵列VR分布	27353
		S2_Subarray_VR	site2峰值下子阵列VR分布	36284

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