Monitoring and analysis of water vapor density based on wireless communication network in Gothenburg area

Gui-Yang SU; Cong-Zheng HAN; Yong-Heng BI; Kun LIU; Lei BAO

doi:10.11972/j.issn.1001-9014.2020.01.008

Journals >Journal of Infrared and Millimeter Waves >Volume 39 >Issue 1 >Page 47 > Article

Journal of Infrared and Millimeter Waves
Vol. 39, Issue 1, 47 (2020)

Monitoring and analysis of water vapor density based on wireless communication network in Gothenburg area

Gui-Yang SU^1、2, Cong-Zheng HAN^1、2、*, Yong-Heng BI², Kun LIU¹, and Lei BAO³

Author Affiliations

¹School of Electronic Engineering, Chengdu University of Information Engineering, Chengdu60225, China

²Laboratory of Middle Atmosphere and Global Environment Exploration, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing10009, China

³Ericsson AB, Lindholmspiren 11, 412 56 Göteborg, Sweden

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DOI: 10.11972/j.issn.1001-9014.2020.01.008 Cite this Article

Gui-Yang SU, Cong-Zheng HAN, Yong-Heng BI, Kun LIU, Lei BAO. Monitoring and analysis of water vapor density based on wireless communication network in Gothenburg area[J]. Journal of Infrared and Millimeter Waves, 2020, 39(1): 47 Copy Citation Text

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Fig. 1. [in Chinese]

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Fig. 2. 不同频段电磁波信号在大气中的衰减特征

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Fig. 3. [in Chinese]

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Fig. 4. 气象要素评估（a）同一个区域两个气象站的温度测量值对比，（b）湿度测量值对比

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Fig. 5. 一个月内使用从微波通讯链路获得的数据计算的水汽密度数值与气象站测量值相比较的日间变化结果（a）气象站1的测量值与微波通讯链路获得的数据计算的水汽密度对比，（b）气象站2的测量值与微波通讯链路获得的数据计算的水汽密度对比

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环境类型	路径损耗指数（n）
自由空间	2
城市地区蜂窝无线电	2.7 to 3.5
密集城区微蜂窝	3 to 5
建筑物上的视距传播	1.6 to 1.8
建筑物遮挡	4 to 6
工厂环境	2 to 3

Table 1. 不同环境的路径损耗指数^[23]

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湿度频率	10%	20%	30%	40%	50%	60%	70%	80%	90%	100%
25 $G H z$	0.0217	0.0437	0.0661	0.0888	0.1118	0.1351	0.1587	0.1827	0.2069	0.2315
28 $G H z$	0.0137	0.0280	0.0427	0.0579	0.0735	0.0897	0.1063	0.1235	0.1411	0.1592
$38 G H z$	0.0119	0.0246	0.0381	0.0525	0.0676	0.0836	0.1004	0.1180	0.1365	0.1557
$71 G H z$	0.0338	0.0704	0.1097	0.1518	0.1967	0.2443	0.2948	0.3480	0.4040	0.4627
$81 G H z$	0.4343	0.0905	0.1411	0.1954	0.2533	0.3148	0.3799	0.4486	0.5209	0.5969

Table 2. 不同湿度条件下典型5G频率的ITU模型理论衰减值（dB/km）

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	Weather Station 1						Weather Station 2
测量日期	最高温度 $(℃)$	最低温度 $(℃)$	平均温度 $(℃)$	水汽密度最大值 $(g / m^{3})$	水汽密度最小值 $(g / m^{3})$	水汽密度平均值 $(g / m^{3})$	最高温度 $(℃)$	最低温度 $(℃)$	平均温度 $(℃)$	水汽密度最大值 $(g / m^{3})$	水汽密度最小值 $(g / m^{3})$	水汽密度平均值 $(g / m^{3})$
2017/06/13	20.30	16.40	13.30	10.13	9.26	7.74	20.77	17.31	13.90	10.95	10.43	9.59
2017/06/14	20.40	16.64	12.70	11.03	9.67	8.54	17.71	15.69	13.40	11.30	10.46	9.77
2017/06/15	20.60	17.37	13.80	11.24	10.60	9.12	20.67	17.75	14.64	12.35	11.69	10.95
2017/06/16	18.70	16.78	15.20	13.82	12.67	10.59	18.06	16.59	15.23	13.39	12.49	11.12
2017/06/17	21.80	18.43	15.80	13.23	11.21	8.07	19.67	17.54	15.70	13.22	11.87	9.36
2017/06/18	22.50	19.10	15.90	13.19	12.47	11.79	19.89	17.67	15.64	13.95	13.00	11.85
2017/06/19	21.60	18.59	15.10	13.60	11.98	10.85	20.08	17.39	14.80	14.07	12.70	11.77
2017/06/20	18.80	16.88	15.30	11.93	8.37	6.28	17.07	15.95	15.17	13.14	9.54	7.70
2017/06/21	19.40	16.22	13.40	8.84	7.35	5.17	17.28	15.52	13.72	9.61	8.34	6.48
2017/06/22	16.00	14.79	13.40	10.51	9.59	8.87	15.75	14.46	13.44	10.77	10.16	9.42
2017/06/23	20.70	16.32	13.50	12.83	11.34	10.29	20.02	15.92	13.45	12.53	11.59	10.17
2017/06/24	18.80	16.16	13.70	11.59	9.31	6.84	16.49	15.34	14.12	11.83	10.22	8.25
2017/06/25	16.40	13.81	11.50	9.81	8.94	8.31	14.47	13.38	11.64	9.74	9.38	9.06
2017/06/26	18.00	15.04	12.30	9.12	8.57	7.80	15.83	14.19	12.50	9.60	9.29	9.00
2017/06/27	20.20	16.68	13.50	9.16	6.68	5.24	19.06	15.85	13.21	9.75	7.60	6.15
2017/06/28	23.60	18.50	13.10	8.65	7.55	6.01	22.07	18.00	13.37	9.63	8.56	7.36
2017/06/29	21.20	18.33	15.60	9.26	7.79	6.50	20.71	17.95	15.40	10.21	8.81	7.59
2017/06/30	22.00	18.63	15.30	9.89	8.66	7.42	21.50	18.28	15.18	10.70	9.55	8.57
2017/07/01	24.30	19.77	15.10	10.65	8.78	6.78	22.91	19.00	15.85	11.18	9.81	7.91
2017/07/02	18.50	15.50	13.80	10.57	9.22	7.98	16.48	14.82	13.56	10.91	10.06	9.19
2017/07/03	18.30	15.19	13.00	9.64	8.50	7.55	16.29	14.41	12.63	10.24	9.28	8.47
2017/07/04	20.20	16.38	12.40	9.88	8.43	6.43	17.62	15.34	12.35	10.14	9.23	8.26
2017/07/05	19.80	16.32	11.20	11.57	9.94	8.51	17.80	15.53	12.14	11.90	10.66	9.59
2017/07/06	18.60	15.96	11.40	10.51	9.85	7.59	17.27	15.38	12.49	11.13	10.55	9.50
2017/07/07	21.60	17.48	14.80	11.56	10.18	8.44	18.82	16.60	14.76	11.86	11.17	10.42
2017/07/08	18.50	16.09	14.20	12.35	10.95	9.04	17.43	15.60	14.26	12.21	11.36	9.92
2017/07/09	18.70	16.28	14.00	10.70	9.42	8.19	17.32	15.42	13.88	11.29	10.17	9.09
2017/07/10	19.70	17.26	12.80	11.43	9.92	8.77	18.35	16.49	13.16	12.05	10.88	10.21
2017/07/11	21.50	17.73	13.90	12.50	11.16	9.18	18.90	17.08	14.17	13.12	11.84	10.69
2017/07/12	18.70	16.15	13.30	11.37	8.97	8.00	17.14	15.31	13.82	12.09	9.94	8.82
2017/07/13	19.70	16.11	10.60	10.13	7.90	5.84	17.63	15.41	11.63	10.35	8.76	7.59