Self-adaptive switching method and device based on support vector machine

Abstract

The embodiment of the invention provides a self-adaptive switching method and device based on a support vector machine, and the method comprises the steps: inputting cell state information to an optimal switching classification plane, and outputting a judgment result whether user equipment needs to be switched or not; if judging that the user equipment needs to be switched, determining an optimalswitching target cell based on the cell state information and the optimal switching classification plane; and sending switching indication information to the source base station, so that the source base station sends switching request information to the target base station, and the user equipment is switched to the optimal switching target cell. The embodiment of the invention provides a self-adaptive switching method and device based on a support vector machine. The user signaling and the wireless network environment are accurately analyzed, the optimal switching classification surface is adaptively optimized by means of the support vector machine, and whether the switching is required and the optimal switching target cell during the switching are decided by judging the cell state information, so that the switching success rate is improved, the switching time delay is reduced, and the user perception is improved.

Description

technical field [0001] The embodiment of the present invention relates to the technical field of mobile communication, and in particular to an adaptive handover method and device based on a support vector machine. Background technique [0002] In mobile communication, due to the limited coverage of a cell, in order to ensure that users in the connected state can use the network normally in the mobile state, it is necessary to hand over the user equipment (User Equipment, UE) from the serving cell to the target cell to ensure The continuity of the network connection of the user equipment, and the success rate and delay of the handover will directly affect the user experience. [0003] In the prior art, the handover strategy is that the UE reports a periodic measurement report (MeasurementReport, MR) to the source base station (Evolved Node-B, eNodeB) in the LTE network in the service state, and the source eNodeB monitors whether it is necessary according to the cause of the c...

AI Technical Summary

Problems solved by technology

[0004] There are certain defects in the handover method in the prior art. For example, when the wireless network environment of the serving cell meets the measurement trigger condition, the UE will perform measurement according to the relevant parameters such as the measurement frequency point and the measurement event issued by the eNodeB, and then the eNodeB will send the measurement result to the The cell with the strongest signal initiates a handover request, and frequency point measurement and event measurement will bring a certain network delay, thereby affecting user perception; at the same time, the existing technology only selects the target cell according to the strength of the signal level of the neighboring cell. If the target cell has the strongest signal but the status is abnormal, such as alarms, congestion, or voice quality problems, normal services cannot be realized, resulting in handover failure

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