Antenna parameter optimizing method based on mobile phone measurement report

Abstract

The invention relates to the technical field of communication, specifically to an antenna parameter optimizing method based on mobile phone measurement report, which is characterized in that the method comprises a wireless network basic data management sub-system, a mobile phone reported data locating sub-system, a wireless network covering emulating sub-system, an antenna feeder parameter automatic optimizing sub-system and a hardware configuring system; the basic data management sub-system stores and manages the wireless network basic data, including electronic map, the project parameter of the whole network and the mobile phone measuring report data; the mobile phone reported data locating sub-system can locate the original mobile phone reported data; the wireless network covering emulating sub-system can locate the result data according to the wireless network basic data, the electronic map and the mobile phone reported data; and the antenna feeder parameter automatic optimizing sub-system solves the problem of uncompleted wireless network covering and uneven telephone traffic distribution. The an antenna parameter optimizing method based on mobile phone measurement report can reduce workload, enlarge application scope and reduce manpower input and cost along with more accurate assessment.

Description

[technical field] [0001] The invention relates to the technical field of communication, in particular to an antenna parameter optimization method based on a mobile phone measurement report. [Background technique] [0002] Network optimization refers to making the network performance reach the optimal balance point required by the network through various hardware or software technologies. The aspect of hardware refers to making the optimal solution in terms of performance and price after reasonable analysis of system requirements, and the aspect of software refers to the setting of software parameters in order to achieve the highest performance load within the tolerance range of the software. [0003] For wireless networks, improving network coverage and reducing wireless interference are the main goals of network optimization. Network optimization ultimately improves the quality of all aspects of wireless networks. The most direct technical means is to adjust and optimize ne...

AI Technical Summary

Problems solved by technology

[0011] 1. Heavy workload: It is necessary to analyze the data through manual experience, and then give an optimization plan, resulting in a heavy workload;

[0012] 2. Low work efficiency: each optimization plan involves the adjustment of a single feeder parameter, and each network optimization engineer can only optimize a few stations every day, and the work efficiency cannot meet the current market needs;

[0013] 3. The optimization cycle is long: After the antenna feeder parameters are adjusted, data needs to be collected for verification, and the next adjustment plan is determined according to the verification results. Only by repeating this can a good antenna feeder optimization effect be ensured, and the cycle is very long;

[0014] 4. It is impossible to accurately know the user's location information. The location information can only be estimated through manual experience combined with specific scenarios. It is impossible to obtain user distribution without visiting the site. Without user distribution information, it is impossible to know the areas that need to be covered.

[0015] 5. It is difficult to obtain a good optimization effect: due to the adjustment of parameters based on artificial subjective experience, the optimization scheme is subjective and one-sided, and the overall performance of the local area wireless network cannot be optimal

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