Mobility prediction-based load balance optimization method applied to heterogeneous network

Abstract

The invention provides a mobility prediction-based load balance optimization method applied to a heterogeneous network and belongs to the communication technical field. According to the method of thepresent invention, the influence of the previous state of a user on future position prediction is researched and compared; optimal decision tree input attribute features are selected, so that a decision tree model can be established to predict the position of the user at the next moment; a time series analysis method is adopted to predict the load status of a base station when the user arrives; and a resource allocation strategy is formulated in advance to optimize the load balance of a network. With the method of the invention adopted, the accuracy of mobility prediction can be improved; thepossible impact of each potential user in adjacent areas on the base station does not need to be monitored; and therefore, the burden of the network is reduced, the network performance of hot spot areas can be improved, and user service experience can be improved.

Description

technical field [0001] The invention belongs to the technical field of communication, and relates to a load balancing optimization method based on mobility prediction in a heterogeneous network. Background technique [0002] With the rapid growth of mobile data traffic in communication networks, a large number of small base stations are widely deployed to increase network capacity. Some hotspots tend to gather more users than others. Due to the uneven distribution of users in the communication network, some base stations are overloaded due to too many users, and at the same time, other base stations are relatively idle with light loads. Users in hotspots may experience poor service experience because base stations cannot provide sufficient resources in a timely manner. In order to improve the service quality of users and make full use of the idle resources of base stations with lighter loads, it is necessary to use load balancing technology to adjust user connections and i...

AI Technical Summary

Problems solved by technology

However, in these two documents, it is necessary to analyze and monitor the impact of each possible incoming user on the target cell through the mobile trend of users in adjacent cells to predict the load status of the base station, which will have a negative impact on the entire communication network. great burden

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