Signal intensity prediction method and system based on wireless propagation model correction

Abstract

The invention provides a signal intensity prediction method and system based on wireless propagation model correction. The method includes the following steps: inputting the preset base station data to a preset wireless propagation model and building a least square model; solving the least square model through a coordinate descent method and obtaining an optimal correction coefficient; and adjusting the parameters of the wireless propagation model according to the optimal correction efficient and conducting wireless signal intensity prediction according to the wireless propagation model whose parameters are adjusted. The signal intensity prediction method and system based on the wireless propagation model correction can rapidly realize wireless model coefficient correction and accurately predicts the intensity of wireless signals.

Description

technical field [0001] The invention relates to the field of wireless communication, in particular to a signal strength prediction method based on wireless propagation model correction and a signal strength prediction system based on wireless propagation model correction. Background technique [0002] The mobile wireless communication system relies on the radio to transmit signals between the base station and the user to achieve the purpose of communication, and the radio in the mobile wireless communication system generally propagates under irregular terrain conditions. Therefore, the propagation of radio between the base station and the user (or between the transmitter and the receiver) will encounter various complex terrains, such as the urban core area with high-rise buildings, the suburbs with dense plants, and the terrain of mountains and mountains. Mountainous areas, etc., even leaves, street lamps, etc. These factors make mobile wireless channels unpredictable and e...

AI Technical Summary

Problems solved by technology

[0005] With the development of wireless communication, the current wireless propagation model can no longer meet the planning and design requirements of the communication network

In the calibration of traditional wireless propagation model coefficients, design and planning personnel are required to continuously intervene manually, and the calibration accuracy is too dependent on personal engineering experience, thus requiring high professional quality of personnel; the traditional calibration method separates the relationship

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