Frequency sweeping-based method and system for optimizing frequency and scrambler

Abstract

The invention discloses a frequency sweeping-based method for optimizing frequency and scrambler. The method is applied to the optimization of frequency and scrambler of cells in a TD-SCDMA (Time Division-Synchronous Code Division Multiple Access) communication network, and basic information of the cells are contained in cell libraries. The method comprises the steps of: establishing an original overlapping relation matrix of cells; acquiring cell types and inter-cell correlation information; calculating the original overlapping relation matrix by utilizing a genetic algorithm, and outputting a frequency configuration scheme; and estimating the frequency configuration scheme. Correspondingly, the invention provides a system implementing the method, the acquired data with single frequency sweeping is only required in project, configuration is optimized according to the method disclosed by the invention to achieve the purpose of optimizing frequency and scrambler, thereby plenty of manpower and material resources are saved, working efficiency is improved and project period is shortened.

Description

technical field [0001] The invention relates to network optimization technology, in particular to a frequency and scrambling code optimization method and system based on frequency scanning. Background technique [0002] TD-SCDMA (Time Division Synchronization-Code Division Multiple Access) is one of the most commonly used networks in mobile communications, but it currently uses few frequency points, short scrambling codewords, and high frequency reuse. The problem of network interference is prominent. Conventional network interference finding methods require a lot of manpower and material resources, and are inefficient and costly. In the case of limited frequency resources, co-frequency networking is unavoidable. At the same time, co-frequency interference is also the main cause of network anomalies. TD scrambling codes have the characteristics of small number of scrambling codes, short chips, and poor correlation between codes after shifting. The planning of scrambling cod...

AI Technical Summary

Problems solved by technology

However, the actual application experience shows that the above method has the following problems: it requires specialized testing equipment and personnel to collect a large amount of test data, which is time-consuming, laborious and costly, and the operation time is short

The main reason for this situation is that in order to obtain more comprehensive data, intensive signal strength collection is required for the test speed, road section and the information of the live network community taken by the test terminal. Since the collection of a comprehensive network area requires a large number of professional and technical personnel time, thus greatly reducing work efficiency and increasing costs

During the period from the data collection to the implementation of the plan, due to the accuracy of the data collected on the live network, the hardware parameters of the cells in the collection area cannot be changed, which increases the difficulty of network optimization

[0004] In summary, the existing frequency optimization technology obviously has inconvenience and defects in actual use, so it is necessary to improve it

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