基于聚类分析和深度学习的多频多模网络负载均衡优化

doi:10.11959/j.issn.1000-0801.2020159

Abstract

Abstract:

Load balancing is a huge challenge for LTE multi-frequency and multi-mode network.Hundreds of parameters are involved in load balancing for the complex network structure.Therefore,it is difficult to perform precise and meticulous configuration only relying on human experience.In order to cope with the challenge,a load balancing scheme based on clustering analysis and deep learning was proposed.Firstly,the key indicators were selected to identify the network scenes,and then big data and deep learning technologies were used to mine the relationship between data.Finally,the optimum system parameters for different network scenes were found.It has been proved that machine learning technology can greatly improve the accuracy and the efficiency of parameter configuration.

Key words: multi-frequency and multi-mode network, machine learning, load optimization

CLC Number:

TN929.53

Yaxing QIU,Xidong WANG,Sen BIAN,Lei YUE. Load balancing based on clustering analysis and deep learning for multi-frequency and multi-mode network[J]. Telecommunications Science, 2020, 36(7): 156-162.

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References 7

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数据类别	数量/条
MR数据	33 839
配置数据	2 224
性能数据	64 655

评价指标	性能参数	A类场景	B类场景	C类场景	D类场景
MAE	F1	0.050 305 1	0.085 069	0.083 26	0.072
	D1	0.075 814 53	0.081 356	0.090 3	0.097 4
	D2	0.049 532 81	0.062 331	0.059 16	0.063 4
	FDD 900 MHz	0.066 624 23	0.056 063	0.077 29	0.082
MSE	F1	0.004 173 82	0.012 049	0.014 59	0.008 6
	D1	0.009 467 74	0.010 753	0.011 83	0.015 2
	D2	0.004 050 8	0.007 063	0.005 61	0.006 9
	FDD 900 MHz	0.006 955 2	0.004 995	0.009 56	0.011 6
R-squared	F1	0.041 087 96	0.072 958	0.111 81	0.122 8
	D1	0.287 457 44	0.287 098	0.233 28	0.146 1
	D2	0.296 022 1	0.197 456	0.290 42	0.150 5
	FDD 900 MHz	0.162 224 46	0.226 527	0.252 51	0.065 3

结果		A类场景	B类场景	C类场景	D类场景
优化配置参数		－103	－109	－107	－110
		－101	－103	－99	－92
		－87	－93	－86	－101
		－98	－101	－98	－88
		－88	－88	－80	－95
		－108	－85	－84	－97
		…	…	…	…
业务预测比例	F1	0.305	0.311	0.306	0.324
	D1	0.310	0.311	0.312	0.296
	D2	0.307	0.304	0.313	0.311
	FDD 900 MHz	0.077	0.071	0.068	0.067

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Load balancing based on clustering analysis and deep learning for multi-frequency and multi-mode network

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