Network user access method based on Neyman-Scott cluster process

Abstract

The invention provides a network user access method based on a Neyman-Scott cluster process. The method comprises the following steps of 1), establishing a system model based on the Neyman-Scott cluster process; 2), deriving a distance distribution model between users and different base stations in clusters; 3), deriving an SINR distribution model and an interference distribution model; 4), deriving an average reachable rate when the users are served by certain base station, through utilization of the SINR distribution model and the interference distribution model; 5), analyzing the interference distribution model of an ultra dense network; 6), obtaining a final average reachable rate when the users are served by a plurality of base stations at the same time, through utilization of the result; and 7), showing that the average reachable rate of the users can be improved through utilization of the method, according to comparison. Compared with a Poisson point process, the method has theadvantages that the method is closer to a practical ultra dense network environment, a higher network average reachable rate is obtained, and the method is significant to the future practical deployment of the ultra dense network.

Description

technical field [0001] The invention belongs to the technical field of ultra-dense network user access, and relates to a network user access method based on the Neyman-Scott cluster process. Background technique [0002] In recent years, effective progress has been made in modeling small cells with random geometry. Due to the randomness and unpredictability of the deployment position of the micro base station, it can be modeled as one or more random point processes on the Euclidean plane. Compared with the traditional hexagonal network model, the Poisson point process is used to build Based on the location distribution of the modular base station, the user's outage probability and coverage probability are obtained by analyzing the cumulative distribution function and complementary cumulative distribution function of the SINR, which is more suitable for the actual network scenario. However, the Poisson point process assumes that all base stations and users are independent of...

AI Technical Summary

Problems solved by technology

[0005] In order to achieve the above object, the present invention provides a network user access method based on the Neyman-Scott cluster process, which solves the problem that the existing system model for analyzing ultra-dense networks does not consider the relationship between the user and the base station. The Neyman-Scott cluster process can be closer to the actual communication environment and obtain a higher average network achievable rate

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