基于复杂环境的无线电频谱地图构建研究

doi:10.12305/j.issn.1001-506X.2026.02.31

系统工程与电子技术 ›› 2026, Vol. 48 ›› Issue (2): 711-718.doi: 10.12305/j.issn.1001-506X.2026.02.31

• 通信与网络 • 上一篇

基于复杂环境的无线电频谱地图构建研究

田睿黠¹(), 齐小刚¹^,²^,*, 蔡维科³, 李家慧²^,³

1. 西安电子科技大学数学与统计学院，陕西西安 710071
2. 西安市信息网络优化与数学方法重点实验室，陕西西安 710071
3. 西安电子科技大学计算机科学与技术学院，陕西西安 710071

收稿日期:2024-11-14 修回日期:2025-02-01 出版日期:2025-04-22 发布日期:2025-04-22
通讯作者: 齐小刚 E-mail:18295880810@163.com
作者简介:田睿黠（1998—），女，硕士研究生，主要研究方向为无线电传播与频谱地图构建
蔡维科（1999—），男，硕士研究生，主要研究方向为无人机集群组网
李家慧（1996—），女，博士后，主要研究方向为网络故障诊断
基金资助:
国家自然科学基金（62372354）资助课题

Research on radio spectrum map construction based on complex environment

Ruixia TIAN¹(), Xiaogang QI¹^,²^,*, Weike CAI³, Jiahui LI²^,³

1. School of Mathematics and Statistics，Xidian University，Xi’an 710071，China
2. Xi’an Key Laboratory of Information Network Optimization and Mathematical Methods，Xi’an 710071，China
3. School of Computer Science and Technology，Xidian University，Xi’an 710071，China

Received:2024-11-14 Revised:2025-02-01 Online:2025-04-22 Published:2025-04-22
Contact: Xiaogang QI E-mail:18295880810@163.com

摘要/Abstract

摘要：

针对复杂环境下的无线电波传播损耗与无线电频谱地图构建问题，提出了一种结合地理信息与电波传播模型的无线电环境地图构建方法。首先根据地形特征区分近视距无线传输与非视距无线传输，建立相应模型精确计算电波传输中的路径损耗；其次在区域内根据稀疏的接收机信号强度进行网格化处理；最后利用地理信息与空间插值全面估计目标区域的接收信号强度。实验结果证实所提方法不仅能反映地形走势，同时在稀疏节点的条件下构建的频谱地图更加符合地理环境。

关键词: 电波传播模型, 路径损耗, 空间插值, 无线电环境地图

Abstract:

Aiming at the problems of radio wave propagation loss and radio spectrum map construction in complex environments, a method for constructing a radio environment map that integrates geographical information and radio wave propagation models is proposed. Firstly, based on topographical features, the method distinguishes between line of sight and non-line of sight wireless transmissions, establishing corresponding models to accurately calculate path loss during radio wave transmission. Secondly, grid processing is applied within the region based on sparse receiver signal strength measurements. Finally, geographical information and spatial interpolation are utilized to comprehensively estimate the received signal strength across the target area. Experimental results validate that the proposed method not only reflects topographical trends but also constructs spectrum maps that are more consistent with the geographical environment, especially under conditions of sparse nodes.

Key words: radio wave propagation model, path loss, spatial interpolation, radio environment map

中图分类号:

TN 925

田睿黠, 齐小刚, 蔡维科, 李家慧. 基于复杂环境的无线电频谱地图构建研究[J]. 系统工程与电子技术, 2026, 48(2): 711-718.

Ruixia TIAN, Xiaogang QI, Weike CAI, Jiahui LI. Research on radio spectrum map construction based on complex environment[J]. Systems Engineering and Electronics, 2026, 48(2): 711-718.

图/表 17

图1

图2

图3

图4

图5

图6

图7

图8

图9

图10

表1

图11

图12

图13

图14

图15

表2

参考文献 31

1	LIAO X, LI X, WANG Y, et al. Path loss modeling in urban water-land environments at 28 GHz: considering water surface reflection and building diffraction[J]. IEEE Antennas and Wireless Propagation Letters, 2023, 22 (4): 744- 748. doi: 10.1109/LAWP.2022.3224155
2	SUMAN S, KUMAR S, DE S. Path loss model for UAV-assisted RFET[J]. IEEE Communications Letters, 2018, 22 (10): 2048- 2051. doi: 10.1109/LCOMM.2018.2863389
3	LI H F, HE W X, HE X G. Prediction of radio wave propagation loss in ultra-rugged terrain areas[J]. IEEE Trans. on Antennas and Propagation, 2020, 69 (8): 4768- 4780.
4	HATA M. Empirical formula for propagation loss in land mobile radio services[J]. IEEE Trans. on Vehicular Technology, 1980, 28 (3): 317- 325.
5	CASTRO B S L, GOMES I R, RIBEIRO F C J, et al. COST231-Hata and SUI models performance using a LMS tuning algorithm on 5.8 GHz in Amazon region cities[C]//Proc. of the 4th European Conference on Antennas and Propagation, 2010.
6	LYTAEV M, BORISOV E, VLADYKO A. V2I propagation loss predictions in simplified urban environment: a two-way parabolic equation approach[J]. Electronics, 2020, 9 (12): 2011.
7	LEE B H, HAM D, CHOI J, et al. Genetic algorithm for path loss model selection in signal strength-based indoor localization[J]. IEEE Sensors Journal, 2021, 21 (21): 24285- 24296. doi: 10.1109/JSEN.2021.3110971
8	IKEGAMI F, YOSHIDA S, TAKEUCHI T, et al. Propagation factors controlling mean field strength on urban streets[J]. IEEE Trans. on Antennas and Propagation, 1984, 32 (8): 822- 829. doi: 10.1109/TAP.1984.1143419
9	WALFISCH J, BERTONI H L. A theoretical model of UHF propagation in urban environments[J]. IEEE Trans. on Antennas and Propagation, 1988, 36 (12): 1788- 1796. doi: 10.1109/8.14401
10	WEINER M. Use of the Longley-Rice and Johnson-Gierhart tropospheric radio propagation programs: 0.02−20 GHz[J]. IEEE Journal on Selected Areas in Communications, 1986, 4 (2): 297- 307. doi: 10.1109/JSAC.1986.1146313
11	BIANCO G M, GIULIIANO R, MARROCCO G, et al. LoRa system for search and rescue: path-loss models and procedures in mountain scenarios[J]. IEEE Internet of Things Journal, 2020, 8 (3): 1985- 1999.
12	倪育德, 于颖丽, 刘瑞华, 等. 大型障碍物影响下航向信标敏感区的划设[J]. 系统工程与电子技术, 2023, 45 (2): 360- 372.
	NI Y D, YU Y L, LIU R H, et al. Setting the sensitive area of localizer under the influence of large obstacles[J]. Systems Engineering and Electronics, 2023, 45 (2): 360- 372.
13	NARAYANAN G, KURUP D. Wireless channel path-loss modelling for agricultural and vegetation environments: a survey[J]. Agricultural Engineering International: CIGR Journal, 2023, 25 (2): 172- 199.
14	郭琪, 孙道宗, 赵文峰, 等. 基于Matlab电波预测模型在电磁场教学改革中的应用[J]. 电脑知识与技术, 2023, 19(14): 80−81, 85.
	GUO Q, SUN D Z, ZHAO W F, et al. Application of Matlab-based radio wave prediction model in the reform of electromagnetic field teaching[J]. Computer Knowledge and Technology, 2023, 19(14): 80−81, 85.
15	刘丹, 叶小舟, 肖伟, 等. 地形遮挡对GNSS干扰范围影响的高效仿真算法[J]. 系统工程与电子技术, 2020, 42 (11): 2418- 2425. doi: 10.3969/j.issn.1001-506X.2020.11.02
	LIU D, YE X Z, XIAO W, et al. Efficient simulation algorithm for the impact of terrain occlusion on GNSS interference range[J]. Systems Engineering and Electronics, 2020, 42 (11): 2418- 2425. doi: 10.3969/j.issn.1001-506X.2020.11.02
16	AYASLI S. SEKE: a computer model for low altitude radar propagation over irregular terrain[J]. IEEE Trans. on Antennas and Propagation, 1986, 34 (8): 1013- 1023. doi: 10.1109/TAP.1986.1143933
17	CASTRO E L E, NAKATA D S D K, CORREIA L, et al. A radio propagation model for a rainforest–river environment using UTD and geometrical optics[J]. IEEE Antennas and Wireless Propagation Letters, 2022, 21 (1): 54- 58. doi: 10.1109/LAWP.2021.3117522
18	宫峰勋, 张英. 非视距信号传播场强特性的分析与研究[J]. 电信科学, 2024, 40 (2): 83- 95. doi: 10.11959/j.issn.1000-0801.2024019
	GONG F X, ZHANG Y. Analysis and research on propagation field strength characteristics of non-line-of-sight signal[J]. Telecommunications Science, 2024, 40 (2): 83- 95. doi: 10.11959/j.issn.1000-0801.2024019
19	水宜水, 徐子龙, 卢毅. 基于ITU-R P. 1546-5建议书的多种复杂地形下信号覆盖状况研究[J]. 中国新通信, 2021, 23 (17): 46- 48. doi: 10.3969/j.issn.1673-4866.2021.17.024
	SHUI Y S, XU Z L, LU Y. Research on signal coverage under various complex terrains based on ITU-R P. 1546-5 recommendation[J]. China New Telecommunications, 2021, 23 (17): 46- 48. doi: 10.3969/j.issn.1673-4866.2021.17.024
20	HAO C Y, WAN X R, FENG D Q, et al. Satellite-based radio spectrum monitoring: architecture, applications, and challenges[J]. IEEE Network, 2021, 35 (4): 20- 27. doi: 10.1109/MNET.011.2100015
21	CHEN G K, LIU Y X, ZHANG T, et al. A graph neural network based radio map construction method for urban environment[J]. IEEE Communications Letters, 2023, 27 (5): 1327- 1331. doi: 10.1109/LCOMM.2023.3260272
22	PESKO M, JAVORNIK T, KOSIR A, et al. Radio environment maps: the survey of construction methods[J]. KSII Transactions on Internet and Information Systems, 2014, 8 (11): 3789- 3809.
23	DENKOVSKI D, ATANASOVSKI V, GAVRILOVSKA L, et al. Reliability of a radio environment map: case of spatial interpolation techniques[C]//Proc. of the 7th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications, 2012: 248−253.
24	SATO K, SUTO K, INAGE K, et al. Space-frequency-interpolated radio map[J]. IEEE Trans. on Vehicular Technology, 2021, 70 (1): 714- 725. doi: 10.1109/TVT.2021.3049894
25	BOLEA L, PEREZ-ROMERO J, AGUSTI R. Received signal interpolation for context discovery in cognitive radio[C]//Proc. of the 14th International Symposium on Wireless Personal Multimedia Communications, 2011.
26	UMER M, KULIK L, TANIN E. Spatial interpolation in wireless sensor networks: localized algorithms for variogram modeling and Kriging[J]. Geoinformatica, 2010, 14, 101- 134. doi: 10.1007/s10707-009-0078-3
27	夏海洋, 查淞, 黄纪军, 等. 电磁频谱地图构建方法研究综述及展望[J]. 电波科学学报, 2020, 35 (4): 445- 456.
	XIA H Y, ZHA S, HUANG J J, et al. Survey on the construction methods of spectrum map[J]. Chinese Journal of Radio Science, 2020, 35 (4): 445- 456.
28	OULD ISSELMOU Y, WACKERNAGEL H, TABBARA W, et al. Geostatistical interpolation for mapping radio-electric exposure levels[C]//Proc. of the 1st European Conference on Antennas and Propagation, 2006.
29	FENG J, YU H X, TIAN M Y, et al. Multi-subgrid cylindrical parabolic equation model for radio environment map generation in a large-scale region[J]. IEEE Antennas and Wireless Propagation Letters, 2023, 23 (1): 334- 338.
30	ZHOU F H, WANG C Y, WU G Y, et al. Accurate spectrum map construction for spectrum management through intelligent frequency-spatial reasoning[J]. IEEE Trans. on Communications, 2023, 71 (7): 3932- 3945. doi: 10.1109/TCOMM.2023.3267569
31	HE S S, ZHU L, WANG L, et al. Fine-grained spectrum map inference: a novel approach based on deep residual network[J]. IET Communications, 2024, 18 (16): 925- 937. doi: 10.1049/cmu2.12786

参数设置	辐射源1	辐射源2
发射功率/dBw	14	3
频率/MHz	1000	300
发射天线高度/m	20	2
天线增益/dB	4	4

场景	DEM栅格行列值	RMSE/%
1	526×617	6.4829
2	913×913	4.0306

基于复杂环境的无线电频谱地图构建研究

Research on radio spectrum map construction based on complex environment

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

图/表 17

参考文献 31

相关文章 1

编辑推荐

Metrics

本文评价