基于射线追踪路径损耗模型的煤矿巷道基站选址方法

王逸飞; 王怡雯; 许议丹; 黄晓俊

doi:10.13272/j.issn.1671-251x.2024080073

基于射线追踪路径损耗模型的煤矿巷道基站选址方法

王逸飞^{1, 2,},
王怡雯^{1, 2},
许议丹^{1, 2},
黄晓俊^{1, 2, ,}

1.
西安科技大学通信与信息工程学院，陕西西安　710054
2.
智慧矿山先进通信技术陕西省高校工程研究中心，陕西西安　710054

基金项目: 陕西省重点研发计划项目（2022GD-TSLD-64）。

详细信息

作者简介:
王逸飞（1998—），男，甘肃定西人，硕士研究生，主要研究方向为电磁传播分析，E-mail：2022488933@qq.com

通讯作者:
黄晓俊（1983—），男，新疆伊宁人，教授，博士，主要研究方向为新一代矿井通信技术，E-mail: hxj@xust.edu.cn。

中图分类号: TD655
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出版历程
- 收稿日期: 2024-08-25
- 修回日期: 2024-11-21
- 网络出版日期: 2024-10-31
- 刊出日期: 2024-11-24

Coal mine roadway base station site selection method based on ray-tracing path loss model

WANG Yifei^{1, 2,},
WANG Yiwen^{1, 2},
XU Yidan^{1, 2},
HUANG Xiaojun^{1, 2, ,}

1.
College of Communication and Information Engineering, Xi′an University of Science and Technology, Xi′an 710054, China
2.
Shaanxi Provincial University Engineering Research Center of Advanced Communication Technology for Smart Mines, Xi′an 710054, China

摘要

摘要:
煤矿巷道狭长且多分支的结构特征导致5G信号难以实现全面覆盖，巷道内的高路径损耗导致无线信号传输受限，因此需要对煤矿巷道基站进行选址规划。现有方法大多通过最大化视距区域的覆盖范围实现基站选址，忽略了非视距区域的基站选址问题。针对该问题，提出了一种基于射线追踪路径损耗模型的煤矿巷道基站选址方法。基于射线追踪路径损耗模型确定矩形断面巷道中基站的覆盖半径；构建了巷道数字高程模型，在此基础上确定了基站位置优化问题的目标函数，通过最小化基站数量和位置优化达到最佳覆盖率；采用遗传算法对基站位置进行优化选择，从而确定基站最优位置。仿真结果表明，使用14个基站的选址方案时，网络覆盖率为91.2%，与数值计算结果的误差仅为2.4%。煤矿巷道实测结果表明，信号接收功率略低于模拟结果，−80 dBm的信号强度可提供200 m的覆盖半径，验证了射线追踪路径损耗模型的有效性。
- 矿井通信 /
- 射线追踪法 /
- 路径损耗模型 /
- 基站选址 /
- 覆盖半径 /
- 数字高程模型 /
- 遗传算法
Abstract:
The narrow and branched structure of coal mine roadways makes it difficult for 5G signals to achieve full coverage, and the high path loss within the roadways limits wireless signal transmission. Therefore, site selection planning for coal mine roadway base stations is necessary. Existing methods typically focus on maximizing the coverage of visual range, neglecting the site selection problem in non-visual range. To address this issue, a coal mine roadway base station site selection method based on the ray-tracing path loss model is proposed. The coverage radius of base stations in rectangular cross-section roadways was determined using the ray-tracing path loss model. A digital elevation model of the roadway was constructed, and based on this, the objective function for base station location optimization was defined. The optimal coverage rate was achieved by minimizing the number of base stations and optimizing their locations. A genetic algorithm was employed to optimize the base station locations, thereby determining the optimal positions. Simulation results showed that with a site selection plan using 14 base stations, the network coverage rate was 91.2%, with an error of only 2.4% compared to numerical calculation results. Field measurement results in the coal mine roadway showed that the received signal power was slightly lower than the simulated results, but a signal strength of −80 dBm provided a coverage radius of 200 m, validating the effectiveness of the ray-tracing path loss model.
- mine communication /
- ray-tracing method /
- path loss model /
- base station site selection /
- coverage radius /
- digital elevation model /
- genetic algorithm

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图 1 镜像法原理

Figure 1. Principle of mirror method

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图 2 水平剖面射线分布及天线的H面和V面

Figure 2. Horizontal cross-section ray distribution and H-plane and V-plane of antenna

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图 3 接收功率

Figure 3. Received power

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图 4 视距模型和非视距模型

Figure 4. Visual range and non-visual range models

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图 5 巷道数字高程模型

Figure 5. Digital elevation model of roadway

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图 6 覆盖热图

Figure 6. Coverage heatmap

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图 7 基站选址问题计算过程

Figure 7. Calculation process of base station site selection

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图 8 遗传算法流程

Figure 8. Genetic algorithm flow

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图 9 二维模拟巷道

Figure 9. 2D simulated roadways

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图 10 基站数量和覆盖率的关系

Figure 10. Relationship between the number of base stations and coverage rate

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图 11 巷道三维模型

Figure 11. 3D model of roadway

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图 12 优化的基站覆盖结果

Figure 12. Optimized base station coverage results

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图 13 巷道部分路径的接收功率

Figure 13. Received power of certain paths in the roadways

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图 14 巷道测试环境

Figure 14. Roadway testing environment

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图 15 测试结果和模拟结果对比

Figure 15. Comparison of test results and simulated results

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表 1 13个基站的位置信息，覆盖率86.0%

Table 1 Location information of 13 base stations with a coverage of 86.0% m

序号	基站坐标（x， y）	序号	基站坐标（x， y）
1	79，346	8	454，463
2	247，129	9	858，463
3	578，196	10	276，632
4	451，213	11	738，643（302）
5	810，212	12	473，642（122）
6	247，442	13	813，632
7	578，451

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表 2 14个基站的位置信息，覆盖率91.2%

Table 2 Location information of 14 base stations with a coverage rate of 91.2% m

序号	基站坐标（x， y）	序号	基站坐标（x， y）
1	68，326	8	376，462
2	247，145	9	804，462
3	580，140	10	90，641（200）
4	413，212	11	215，632
5	843，212	12	461，642（113）
6	247，436	13	780，632
7	578，427	14	724，642（292）

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表 3 15个基站的位置信息，覆盖率94.4%

Table 3 Location information of 15 base stations with a coverage rate of 94.4% m

序号	基站坐标（x， y）	序号	基站坐标（x， y）
1	53，300	9	836，462
2	248，203	10	90，644（200）
3	578，179	11	218，635
4	448，212	12	493，642（135）
5	827，213	13	618，633
6	246，431	14	736，643（300）
7	576，387	15	782，518
8	369，463

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表 4 基站位置优化方法对比

Table 4 Comparison of base station location optimization methods

方法	全局	非视距	可视化
遗传算法^[17]	否	否	否
启发式算法^[18]	是	否	否
几何方法和优化工具^[19-21]	是	否	是
搜索算法^[22]	否	是	是
本文方法	是	是	是

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