UE target cell determination method and device, communication equipment and storage medium

A target cell and determination method technology, applied in wireless communication, electrical components, etc., can solve the problem of high frequency of cell reselection or handover
CN112385267APending Publication Date: 2021-02-19BEIJING XIAOMI MOBILE SOFTWARE CO LTD
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Patent Information

Authority / Receiving Office
CN ยท China
Current Assignee / Owner
BEIJING XIAOMI MOBILE SOFTWARE CO LTD
Publication Date
2021-02-19

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Abstract

The embodiment of the invention provides a method and device for determining a target cell of UE, communication equipment and a storage medium. The method for determining the target cell of the UE comprises the following steps: determining candidate cells for cell switching or cell reselection according to measured cell signal quality; according to the mobility management parameters and a revenuealgorithm model, determining expected revenue of the access candidate cell; and selecting a target cell for cell switching or cell reselection from the candidate cells according to the expected income. According to the method provided by the embodiment of the invention, compared with cell switching or cell reselection carried out according to the signal intensity of the cell, the situation of frequent occurrence of cell switching or cell reselection caused by jittering and the like of the signal intensity of the cell can be at least reduced, and thus the stability of the system is improved.
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Description

technical field

[0001] The present disclosure relates to the field of wireless communication but is not limited to the field of wireless communication, and in particular to a method, device, communication device and storage medium for determining a target cell of a UE. Background technique

[0002] Machine learning algorithm is one of the most important implementation methods of artificial intelligence technology. Machine learning can obtain a model through a large amount of training data, and events can be predicted through the model. In many fields, the models trained by machine learning can obtain very refined prediction results.

[0003] For example, a multi-arm bandit algorithm (Multi Arm Bandit, MAB) can be used to solve the problem of maximizing expected revenue when there are multiple optional targets and the revenue of each optional target is unknown. User Equipment (UE) maintains a cumulative benefit for each optional target, and in each round, the UE decides whe...

Claims

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