基于大数据分析的室内深度覆盖优化方法研究

doi:10.11959/j.issn.1000-0801.2019140

Abstract

Abstract:

The indoor prediction method of indoor depth coverage includes user complaints,CQT and propagation model correction,and the prediction error of these methods is large.Firstly,the indoor coverage optimization method was introduced.Then,the indoor deep coverage optimization method based on big data was introduced,which significantly improved the network quality and user perception.Finally,the application case was introduced,which provided a very important reference and guiding significance for the construction,optimization and maintenance of indoor deep coverage in the later period.

Key words: big data, MR, investment efficiency, wireless indoor coverage

CLC Number:

TN929.53

Yuanfeng GONG,Yi HUANG. Optimization method of wireless indoor coverage based on big data analysis[J]. Telecommunications Science, 2019, 35(5): 149-154.

Figures/Tables 10

References 5

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站点	楼层面积/m²	楼宇高度/m	楼宇层数	面积/m²	区域类型
站点1	2 205.42	9	3	6 616.26	餐饮及娱乐

站点	BBU数量	RRU数量	单RRU日均流量/GB	总投资/万元
站点1	1	1	20.75	4.68

区域	楼层面积/m²	楼宇高度/m	楼宇层数	面积/m²
车间	11 873.27	9	3	35 619.81
办公楼	1 815.82	18	6	10 894.92
宿舍1	1 575.76	18	6	9 454.56
宿舍2	1 575.76	18	6	9 454.56

区域	BBU数量	RRU数量	RRU日均流量/GB	单RRU平均日均流量/GB	投资/万元
车间	1	1	5.9	23.93	6.86
办公楼		1	11.2
宿舍1	1	1	68.7
宿舍2		1	9.9

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Optimization method of wireless indoor coverage based on big data analysis

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