Method for achieving dynamic load balancing in heterogeneous network

Abstract

The invention discloses a method for achieving dynamic load balancing in the heterogeneous network, and relates to the technical field of the heterogeneous communication network. According to the method, each base station senses the changes of network loads in the heterogeneous network, historical network load information is learnt, the network load situation in the future is forecasted, inter-cell handover or intra-cell handover is carried out on users newly connected into the network to achieve load balancing according to the forecasted load value of each base station, and the reinforcement learning algorithm, the optimal relevance algorithm, the bias factor solution algorithm and the optimal resource distribution algorithm based on the load balancing are included. The method achieves the intelligence of the network in a sense, combines the rapid load balancing with the dynamic network resource distribution adjustment, and improves the performance of the whole network. The method can also be used in the homogeneous network, and has good compatibility.

Description

technical field [0001] The invention belongs to the technical field of mobile communication, and relates to a method for realizing dynamic load balancing in a heterogeneous network. Background technique [0002] In order to meet the needs of people's increasing business volume, the traditional cellular network is developing towards heterogeneity and intelligence, especially the deployment of a large number of small base stations (picocell and femtocell) to further improve network coverage and system capacity , to increase the data transmission rate of the user, so that the user can get better service. However, with the random access and departure of users, the load conditions of each base station are different, and some base stations are congested due to too many users accessing, so that users accessing these base stations cannot get good services , and some base stations waste their resources due to too few or no users accessing them, so how to quickly realize load balanci...

AI Technical Summary

Problems solved by technology

Moreover, the existing technology considers the resource utilization rate of a single cell in the resource allocation part. If it is a local optimization technology from the perspective of the entire system, this consideration may lead to a certain loss in the performance of other nodes.

[0004] In addition, the existing load balancing methods do not have the characteristics of load perception, and when considering the correlation between users and base stations, they simply use the user's signal quality as an indicator, and do not take into account the load and resource usage of each base station. , so the final utility function of the entire network is not the optimal value, and it has certain limitations in resource utilization, that is, the type of handover considered is only intra-cell handover or only inter-cell handover, which cannot make users effectively use the resources of the entire network, resulting in The resource utilization of the entire network is not high

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