End-to-end multi-dimension normalization LTE (long term evolution) network evaluation optimization system

Abstract

The invention discloses an end-to-end multi-dimension normalization LTE (long term evolution) network evaluation optimization system, which comprises a data collecting device, a data completeness evaluation device, a model evaluation device and a normalization evaluation device, wherein collected data types include LTE soft collection data, north MR (measurement report) data, LTE hard collection data, sweeping frequency data, drive test and ATU (auxiliary test unit) data, OMC (operation and maintenance center) performance statistics data and network element equipment basic data, the data completeness evaluation device is used for evaluating the completeness of the collected data, the model evaluation device comprises data evaluation modules for carrying out classified evaluation on the collected data, in addition, different types of data corresponds to one data evaluation module, the corresponding data evaluation modules are respectively used for evaluating the corresponding data types for obtaining evaluation values, and the normalization evaluation device sets the corresponding weight for the data evaluation modules for the corresponding data types, and can obtain a normalization value through the weight and the evaluation values. The end-to-end multi-dimension normalization LTE network evaluation optimization system has the advantage that the evaluation result has normalization performance, continuity and traceability.

Description

technical field [0001] The invention relates to the field of wireless communication, in particular to an end-to-end multi-dimensional normalized LTE network evaluation and optimization system. Background technique [0002] Since LTE was deployed and put into commercial use in mainland China, there has not been an intelligent and automatic normalized evaluation method so far. Network operation managers lack a unified and comprehensive understanding and grasp of LTE network coverage level, interference degree, resource efficiency, network performance, network load, terminal perception, etc., so that resource investment is not targeted, network optimization only treats the symptoms but not the root cause, etc. The phenomenon that businessmen do not want to see. [0003] LTE network planning depends on simulation, optimization depends on experience; the direction of base station investment and construction depends on user complaints; analysis and data mining rely solely on one ...

AI Technical Summary

Problems solved by technology

Optimization experience lacks uniformity and cannot be promoted on a large scale

Drive test data can be collected in a limited range, with high labor intensity and low efficiency; northbound MR data lacks data samples related to downlink interference and resource scheduling, and cannot fully reflect network conditions; hard-collected data only focuses on the core network business side; soft-collected data focuses On the wireless side, focus on the control plane

None of the above technologies can comprehensively and uniformly evaluate and optimize the LTE network end-to-end and multi-dimensional. Moreover, the evaluation results of different technicians in different cities and cities at different times are not the same, and the optimization methods will appear repeated and inconsistent. Normalization, Continuity and Traceability

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