Research And Implementation For Wireless Network Coverage Prediction System Based On Google Earth

With the development of mobile communication technology, the network architecture of mobile communication is becoming more and more complex. Under this circumstance, the corresponding coverage prediction model should be more adaptable to the complex network technology and different network systems, network optimization tool more intelligence and automatic.Based on an extensive reading of relevant literature, this paper reviews and compares different kinds of propagation models at first, and then describes the propagation characteristics of wireless channel. After that, the application requirements and development direction of the propagation prediction model are discussed. Finally, our research work is presented.The main contribution and innovation points of this paper are as follows:(1) A novel coverage prediction tool is developed. This tool is based on the inversion prediction model. It combines the data of drive test with the coverage prediction model, and uses Google Earth as its geographic data support system, which expands the network optimization platform digital map source, reduces system development cost, and provides a novel thought of low cost and high efficiency development for network planning and optimization.(2) Realizing the coverage prediction and performance analysis for single-cell and multi-cells based on the information of automatic drive test. Optimizing the network coverage by referring to the boundary of these cells. Application shows that the standard deviation of the inversion prediction model is between4to7dBm, which is equal to or higher than the accuracy of international deterministic model, while less computing time is required.