Weak coverage area determination method and apparatus

Abstract

The invention provides a weak coverage area determination method and apparatus, and relates to the technical field of communications. The method comprises: subdividing the electronic map comprising communication network signal intensity distribution into a plurality of filtering blocks with specified sizes, the filtering blocks comprising multiple bin points; scanning each bin point in the electronic map, obtaining the signal strength of each bin point, and defining the bin points whose signal intensity is lower than a first preset threshold value as first-type bin points; and obtaining the proportion which the first-type bin points in each filtering block accounts for, and determining the filtering blocks whose first-type pin point proportions are greater than a first preset factor as weak coverage areas. The method and apparatus provided by the invention can determine the weak coverage areas in a highly-efficient and highly-accurate manner, the needed manpower investment is small, and the method and apparatus are suitable for various network standards.

Description

technical field [0001] The present invention relates to the technical field of wireless communication, and in particular provides a method and device for determining a weak coverage area. Background technique [0002] Weak coverage refers to the situation where the signal in the border area is weak due to the large coverage area required by the base station, the distance between the base stations is too large, or the building is blocked. Usually, when the received power of the terminal is less than -90dBm, it is considered to be weak coverage. Weak coverage areas not only affect the quality of network calls, but also easily cause call drop, resulting in a series of problems such as low paging response rate. Therefore, how to accurately find out the weak coverage area or weak coverage point in the network in the live network, and then optimize the solution in real time has become the key to network optimization. [0003] In the process of wireless network (GSM, TD-SCDMA, WCD...

AI Technical Summary

Problems solved by technology

The main disadvantage is that the test can only be analyzed from the perspective of the line. Due to the limitation of the driving route, it can only test the main road signals, and cannot comprehensively test the signals in small roads and buildings. The weak coverage of the surrounding areas of the road cannot be accurately analyzed only by road tests. Therefore, this method cannot comprehensively discover and define weak coverage problems in the network

In addition, the log analysis of the test needs to rely on the optimization experience of the optimization personnel to judge and locate the scope of weak coverage, which has high requirements for personnel skills

[0007] Monitoring of key indicators of network performance: Weak coverage can be found through the research and analysis of various performance indicators in the network by optimization personnel. The disadvantage is that it can only roughly determine which base station or wireless cell in the network has weak coverage, and cannot accurately locate the specific weak coverage Location

In addition, this method needs to arrange special personnel to analyze the indicators of the whole network, and judge whether there is weak coverage in the network through joint analysis of performance indicators and equipment alarms, which requires high personnel skills

[0008] Statistical analysis of the measurement messages reported by the terminal: through the reported measurement cell and a certain positioning algorithm, weak coverage can be found and located. The disadvantage is that the deviation range for locating the weak coverage through the measurement message reported by the terminal is relatively large, and the industry can basically only do it Accuracy to 100 meters

Other related means, such as locating the location of weak coverage by measuring the received power of the mobile phone in the message combined with the wireless propagation model algorithm, also have similar problems such as large location deviations

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