Low-power wide area network planning method based on data mining

Abstract

The invention discloses a low-power wide area network planning method based on data mining, which obtains measured data of a low-power wide area network, starts from a covering target to comprehensively consider an influencing factor of weak coverage of the network, uses an improved regression tree algorithm to establish a signal quality prediction model for extracting the covering distribution space mode of the network; then, the selection of the base station position is treated as a weighted problem based on the covering distribution space mode to be processed; a weighted K-centroids clustering algorithm is used for obtaining optimal base station deployment adapting to the current mode; finally, the final base station topology is obtained according to determination of a general objectivefunction. The low-power wide area network planning method based on data mining in the invention can improve the covering quality of the low-power wide area network well; and a certain reference valueis achieved for network planning.

Description

technical field [0001] The invention relates to the field of wireless network planning and planning, in particular to a method for network planning of a low-power wide area network based on big data mining. Background technique [0002] With the rapid development of the Internet of Things, the number of connected devices is expected to grow to 50 billion, and the business volume will increase by more than a thousand times. Traditional short-distance wireless technology and cellular network technology can no longer meet the diverse business needs of the Internet of Things. Therefore, a new communication mode——Low Power Wide Area Network (LPWAN) emerged at the historic moment, which mainly satisfies large connections and low-speed Internet of Things services, and has the characteristics of large coverage, low connection cost, and low power consumption. . LPWAN mainly includes wireless communication technologies such as NB-IoT, LORA, and RPMA, which can support a very large nu...

AI Technical Summary

Problems solved by technology

However, the determination of the base station site is an NP-hard problem. If the traditional site selection model is used to analyze various factors of the site site problem, it will lead to the dimension disaster of the variables and constraints in the built model. This site selection method not scientific

In addition, network planning needs to consider not only coverage, but also service distribution, and the need to process and integrate space-time characteristics, which makes network planning more complicated and requires a reasonable network planning solution

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