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Operator consumer pricing method based on large-scale base station mobile APP usage behavior

A technology for consumers and operators, applied in the field of telecom big data, it can solve problems such as traffic congestion in base stations

Inactive Publication Date: 2018-06-22
SUN YAT SEN UNIV +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to solve the problem of base station traffic congestion and provide a pricing method for operators and consumers based on large-scale base station mobile APP usage behavior

Method used

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  • Operator consumer pricing method based on large-scale base station mobile APP usage behavior
  • Operator consumer pricing method based on large-scale base station mobile APP usage behavior
  • Operator consumer pricing method based on large-scale base station mobile APP usage behavior

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Embodiment 1

[0058] This embodiment discloses a pricing method for operators and consumers based on the mobile APP usage behavior of large-scale base stations. First, a consumer expectation function is constructed according to the three-dimensional information of the location, time, and category of the APP. Then, the consumer's utility function and the operator's profit function are constructed. Finally, by jointly solving the utility function and the profit function, the optimal traffic consumption of consumers and the optimal pricing strategy of operators are obtained. The pricing method for operators and consumers based on the mobile APP usage behavior of large-scale base stations includes the following steps:

[0059] S1. Initialize parameters, determine the APP usage category i∈[1,I] of the base station j∈[1,J], the APP usage time t∈[1,T] and the ranking of APP usage characteristics Wherein, J is the total base station number, T is the total time number, and I is the total APP categ...

Embodiment 2

[0079] This embodiment is attached in conjunction with the instructions Figure 1 to Figure 8 The precise and practical method proposed by the present invention will be described in detail with a specific embodiment of a pricing method for operators and consumers based on large-scale base station APP usage behavior.

[0080] The actual data set comes from J=9600 base stations and I=16 types of APPs. Divide a day into 4 time units with 6 hours as a time unit, and distinguish weekdays and weekend time units. Therefore, T=8, t∈{1,2,3,4,5,6,7,8 }, the first 4 time units are used to represent the time on weekdays, and the last 4 time units are used to represent the time on weekends. APP usage characteristics include 16 (APP categories) × 4 (time unit) × 2 (time category) has a total of 128 dimensions. Select one of the types of base stations for feature ranking. Among all the sorting results, select the top 5 (shown in Figure 4(a)) and bottom 5 (shown in Figure 4(b)) APP persona...

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Abstract

The invention discloses an operator consumer pricing method based on the usage behavior of a large-scale base station mobile APP. Compared with a traditional rough traffic pricing method, the operatorconsumer pricing method based on the usage behavior of the large-scale base station APP can formulate a refined pricing scheme based on the use location, time and category of an actual base station APP, and has a great practical value. The method comprises the steps that a consumer expectation function is constructed according to the three-dimensional information of the use location, time and category of the APP; the utility function of a consumer and the profit function of an operator are constructed; and finally, the optimal traffic consumption of the consumer and the best pricing policy ofthe operator are acquired by jointly solving the utility function and the profit function. Compared with a simple pricing method based on use traffic, the method has the advantages that the profit ofthe operator is improved; the satisfaction of the customer is effectively improved; and especially in the period when the APP is active, the problem of traffic congestion can be effectively alleviated.

Description

technical field [0001] The invention relates to the field of telecommunications big data technology, in particular to a pricing method for operators and consumers based on large-scale base station mobile APP usage behavior. Background technique [0002] Mobile devices' demand for traffic is growing rapidly, exceeding the growth rate of base station traffic capacity. In order to solve the problem of short supply of traffic, there are currently two research solutions. On the one hand, technical solutions such as buffer design, intelligent spectrum utilization, and data measurement are adopted. On the other hand, it is to design economic measures such as pricing adjustments. However, the traffic demand of the base station is erratic due to different time and place, and the volatile traffic demand is affected by the complex behavior of users, which is not easy to achieve and the cost is relatively high only by relying on technical solutions. In addition, traditional pricing sc...

Claims

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Application Information

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IPC IPC(8): G06Q30/02G06Q50/30
CPCG06Q30/0283G06Q50/40
Inventor 尹杰丽陈翔李勇叶家恒
Owner SUN YAT SEN UNIV
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