CN110912747B - Random geometry-based power wireless private network performance analysis method - Google Patents
Random geometry-based power wireless private network performance analysis method Download PDFInfo
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Abstract
The invention discloses a random geometry-based performance analysis method for a wireless power private network, which analyzes the network performance of the wireless power private network by using a random geometry theory and is divided into two aspects of network coverage performance analysis and system capacity analysis; the network coverage performance analysis comprises a random geometry-based electric wireless private network base station space distribution model and an estimation formula of network coverage probability, and the coverage performance of the electric wireless private network can be estimated by substituting the density of the network base stations; the system capacity analysis comprises the steps of introducing system bandwidth and the number of base station connection users on the basis of network coverage performance analysis, substituting the system bandwidth and the number of the base station connection users into a calculation formula of the capacity analysis, and estimating the system capacity of the electric power wireless private network. The invention solves the problems of excessive rationalization and inaccurate result of the traditional cellular network performance analysis method.
Description
Technical Field
The invention relates to a performance analysis method for a wireless private power network, in particular to a random geometry-based performance analysis method for the wireless private power network.
Background
With the development of the times, the demand of the power industry on the power wireless private network is increasing day by day. The business demand is increased explosively, the security of the public network is to be increased, the construction cost of the optical cable is high, and the scattered construction of each specialty is the main problem faced by the current electric power wireless private network. An electric power wireless private network based on the current 4G wireless communication and the coming 5G wireless communication is an important communication mode of a terminal communication access network. Therefore, the performance analysis of the wireless private network has important academic value and wide application prospect, and gradually becomes a common research hotspot in the power industry and the wireless communication industry.
The network performance analysis is a process of estimating key performance indexes of the network by a computer and combining with a corresponding mathematical tool, and the network performance analysis enables the computer to analyze the inherent characteristics of the network from the representation of the network and provides a basis for further network optimization. The electric power wireless private network performance analysis mainly comprises network coverage performance (coverage probability), system capacity (transmission rate) and the like.
The base station distribution description is a very important link of the performance analysis of the power wireless private network and is a key step for improving the estimation of network performance indexes. Among the base station distribution description methods, the grid analysis method is a common method and has the characteristics of intuition, simplicity and convenience, wherein the hexagonal grid analysis is a typical representative of the method. The hexagonal grid analysis method has the advantages that the network structure is simple, the factors influencing cell interference are only two, namely the cell size and the transmitting power of a base station, the hexagonal grid analysis method is widely applied to cellular network performance analysis in 2G/3G mobile communication, and the hexagonal grid analysis method is more and more widely applied to other network fields. However, with the development of wireless communication, the mesh analysis method has the following disadvantages:
1. the hexagonal cell structure is over-ideal, even in a single-layer network, the actual coverage of the base station and the hexagonal cell structure has larger deviation, the actual distribution characteristics of the base station cannot be accurately described, and the regularity similar to a hexagon can be shown only under the condition that the base station is very densely distributed;
2. the method has no mathematical analyzability, can only obtain corresponding results through Monte Carlo simulation, and is not beneficial to later-stage network performance optimization.
Disclosure of Invention
Based on the above situation, the present invention aims to provide a method for analyzing the performance of a wireless private power network based on random geometry, which uses the random geometry theory to describe the probability distribution of the received signal-to-interference ratio of a target user in the wireless private power network, comprehensively considers the spatial distribution situation of a base station and the distribution situation of the received signal and interference of the target user, and is different from the traditional grid analysis method that the cell size is a fixed value, and finally obtains the coverage performance index value (coverage probability) of the network; the network capacity (transmission rate) is further analyzed on the basis of coverage performance analysis to obtain an analytical expression of the network transmission rate, and the result can be directly calculated after the analytical expression is substituted into the basic network parameters, so that the method has strong practicability.
The purpose of the invention is realized by the following technical scheme:
a method for analyzing the performance of a wireless private power network based on random geometry is characterized by comprising the following steps: the method utilizes a random geometric theory to analyze the network performance of the power wireless private network and is divided into two aspects of network coverage performance analysis and system capacity analysis; wherein:
the coverage performance analysis comprises a random geometry-based power wireless private network base station space distribution model and a network coverage probability estimation formula, and the coverage performance of the power wireless private network can be estimated by substituting the density of the network base stations;
the system capacity analysis comprises the steps of introducing system bandwidth and the number of base station connection users on the basis of network coverage performance analysis, substituting the system bandwidth and the number of the base station connection users into a calculation formula of the capacity analysis, and estimating the system capacity of the electric power wireless private network.
The method comprises the following specific steps:
1) network coverage performance analysis
Constructing a distribution model of the base stations according to the number of the base stations in a certain space based on a space distribution model of random geometry;
assuming that the target user is located at the center origin, the base station closest to the target user is a communication base station, the other base stations are interference base stations, the distance from the communication base station to the target user is r, and the probability density function is
According to the wireless communication path loss model, the Signal to Interference plus Noise Ratio (SINR) of the target user of the downlink of the power wireless private network is
h is a random variable comprehensively considering the transmitting power of the base station and shadow fading, and the obedience parameter is
The index distribution of (D) is denoted as h to exp (mu),
is the transmit power of the base station; therefore, the numerator of equation (2) represents the received signal power and the denominator represents interference and noise;
the coverage performance (coverage probability) of the network generally refers to the probability that the received SINR of the target user is greater than a certain threshold T; according to the two points, a general analytic conclusion of the coverage probability is obtained by combining a random geometric theory
Wherein the content of the first and second substances,
in the formula (3), λ represents the base station density, α represents the path loss exponent, σ2Representing noise power, and T is a network SINR threshold value; the parameters are obtained from a network operator; calculating the coverage performance of the power wireless private network through a formula (3);
2) system capacity analysis (transmission rate)
Since the coverage performance is the probability that the received SINR of the target user is greater than a certain threshold T, i.e. the SINR distribution, the system capacity (transmission rate) of the network is calculated according to shannon's theorem
Wherein the content of the first and second substances,
in the formula (4), W represents the system bandwidth, N represents the number of base station connection users, and the number is obtained from a network operator; and (4) estimating the system capacity of the electric power wireless private network through the formula (4).
The invention has the beneficial effects that:
1. comparison of random geometric model, grid model and base station actual distribution
The random geometric model and the hexagonal grid model are respectively tested in a certain area of power wireless private network scene, network structures simulated according to the density of the base station provided by an operator are respectively shown in fig. 1 and fig. 2, and fig. 3 is a network structure drawn according to the actual position of the base station. From the three images, the network structure simulated by the random geometric model is closer to the distribution condition of the actual network than the hexagonal grid model, and the network performance index estimated according to the random geometric model is more accurate.
2. Comparing the random geometric model with the grid model and the measured coverage performance
The base station distribution described by the stochastic geometry model is more practical and is largely used in network performance analysis of cellular networks, Ad-hoc networks, self-organizing networks and the like. As can be seen from fig. 4, the estimation value of the random geometric model to the coverage performance of the wireless power private network is significantly more accurate than that of the grid model and substantially consistent with the measured value. Table 1 shows the error comparison and computation time comparison of the random geometry model and the network model for the coverage performance estimation. Therefore, the random geometric model has small error and greatly reduced calculation time, and the calculation efficiency is improved. In addition, the estimation value of the grid model is higher than the measured value from the estimation result, which may cause the network manager to excessively trust the coverage performance of the network, thereby causing the actual coverage to be insufficient.
TABLE 1 estimated error and calculated time of different models of wireless private network coverage performance of electric power
3. Comparing the capacity of the random geometric model with the capacity of the grid model and the measured system
And respectively carrying out transmission capacity estimation on the random geometric model and the hexagonal grid model in a certain area power wireless private network scene by taking the actually measured speed value as a reference. The results are shown in Table 2. It can be seen from the table that the estimated value of the system capacity by the random geometric model is closer to the measured value, and meanwhile, because the random geometric model only relates to integral calculation when calculating the system capacity, and the grid model needs monte carlo simulation, the consumed time is greatly reduced, and the calculation efficiency is improved. This is disadvantageous for network performance evaluation, since the capacity value estimated by the mesh model is higher than the actual value.
TABLE 2 comparison of stochastic geometry model and grid model to calculated values of capacity and calculated time for wireless power private network system
The probability distribution of the receiving signal-to-interference ratio of the target user in the electric power wireless private network is described by utilizing a random geometric theory, the space distribution condition of a base station and the distribution condition of the receiving signal and the interference of the target user are comprehensively considered, the cell size is a fixed value different from that of a traditional grid analysis method, and finally the coverage performance index value of the network is obtained; the network capacity is further analyzed on the basis of coverage performance analysis to obtain an analytical expression of the network transmission rate, and the result can be directly calculated after the analytical expression is substituted into the basic network parameters, so that the method has strong practicability.
The invention solves the problems of excessive rationalization and inaccurate result of the traditional cellular network performance analysis method.
Drawings
FIG. 1 is a schematic diagram of a network structure simulated by a random geometric model according to the present invention.
Fig. 2 is a schematic diagram of a network structure simulated by a grid model in the invention.
Fig. 3 is a schematic diagram of the actual distribution of the network in the present invention.
Fig. 4 is a comparative illustration of the coverage performance of the present invention.
Detailed Description
A method for analyzing the performance of a wireless private power network based on random geometry analyzes the network performance of the wireless private power network by using a random geometry theory and is divided into two aspects of network coverage performance analysis and system capacity analysis; wherein:
the network coverage performance analysis comprises a random geometry-based electric wireless private network base station space distribution model and an estimation formula of network coverage probability, and the coverage performance of the electric wireless private network can be estimated by substituting the density of the network base stations;
the system capacity analysis comprises the steps of introducing system bandwidth and the number of base station connection users on the basis of network coverage performance analysis, and substituting a calculation formula of the capacity analysis to estimate the system capacity of the electric power wireless private network.
The invention provides a space distribution model based on random geometry, and the distribution model of base stations is constructed according to the number of the base stations (namely, the density of the base stations) in a certain space.
Assuming that the target user is located at the center origin, the base station closest to the target user is a communication base station, and the rest base stations are interference base stations. The distance between the communication base station and the target user is r, and the probability density function is
SINR of target user (Signal to Interference plus Noise Ratio, SINR)
According to the wireless communication path loss model, the SINR of the target user of the downlink of the power wireless private network is
h is a random variable comprehensively considering the transmitting power of the base station and shadow fading, and the obedience parameter is
The index distribution of (D) is denoted as h to exp (mu),
is the transmit power of the base station. Therefore, the numerator of equation (2) represents the received signal power and the denominator represents interference and noise.
The coverage performance (coverage probability) of the network generally refers to the probability that the received SINR of the target user is greater than some threshold T. According to the two points, the general analytic conclusion of the coverage probability can be obtained by combining the random geometric theory
Wherein the content of the first and second substances,
in the formula (3), λ represents the base station density, α represents the path loss exponent, σ2Representing the noise power, and T is the network SINR threshold value. The above parameters can be easily obtained from the network operator. And (3) counting the number of the base stations in the area, dividing the number by the area to obtain the density of the base stations in the area, and conveniently estimating the coverage performance of the electric power wireless private network through a formula (3).
Since the coverage performance is the probability that the received SINR of the target user is greater than a certain threshold T, i.e. the SINR distribution, the system capacity (transmission rate) of the network can be calculated according to shannon's theorem
Wherein the content of the first and second substances,
in the formula (4), W represents the system bandwidth, and N represents the number of base station connection users, which can also be obtained from the network operator; the remaining parameters are already stated in point 3. The system capacity of the electric wireless private network can be conveniently estimated by combining the density of the base station and substituting the density into the formula (4).
The probability distribution of the receiving signal-to-interference ratio of the target user in the electric power wireless private network is described by utilizing a random geometric theory, the space distribution condition of a base station and the distribution condition of the receiving signal and the interference of the target user are comprehensively considered, the cell size is a fixed value different from that of a traditional grid analysis method, and finally the coverage performance index value of the network is obtained; the network capacity is further analyzed on the basis of coverage performance analysis to obtain an analytical expression of the network transmission rate, and the result can be directly calculated after the analytical expression is substituted into the basic network parameters, so that the method has strong practicability.
Claims (1)
1. A method for analyzing the performance of a wireless private power network based on random geometry is characterized by comprising the following steps: the method utilizes a random geometric theory to analyze the network performance of the power wireless private network and is divided into two aspects of network coverage performance analysis and system capacity analysis; wherein:
the network coverage performance analysis comprises a random geometry-based electric wireless private network base station space distribution model and an estimation formula of network coverage probability, and the coverage performance of the electric wireless private network can be estimated by substituting the density of the network base stations;
the system capacity analysis comprises the steps of introducing system bandwidth and the number of base station connection users on the basis of network coverage performance analysis, substituting the system bandwidth and the number of the base station connection users into a calculation formula of capacity analysis, and estimating the system capacity of the electric power wireless private network;
the method comprises the following specific steps:
1) network coverage performance analysis
Constructing a distribution model of the base stations according to the number of the base stations in a certain space based on a space distribution model of random geometry;
assuming that the target user is located at the center origin, the base station closest to the target user is a communication base station, the other base stations are interference base stations, the distance from the communication base station to the target user is r, and the probability density function of the communication base station is r
According to the wireless communication path loss model, the signal-to-interference-and-noise ratio of the target user of the downlink of the power wireless private network is
h is a random variable comprehensively considering the transmitting power of the base station and shadow fading, and the obedience parameter is
The index distribution of (D) is denoted as h to exp (mu),
is the transmit power of the base station; therefore, the numerator of equation (2) represents the received signal power and the denominator represents interference and noise;
the coverage performance of the network generally refers to the probability that the received SINR of a target user is greater than a certain threshold T; obtaining a general analytic conclusion of the coverage probability according to the formulas (1) and (2) and combining with a random geometric theory
Wherein the content of the first and second substances,
in the formula (3), λ represents the base station density, α represents the path loss exponent, σ2Representing noise power, and T is a network SINR threshold value; the parameters are obtained from a network operator; calculating the coverage performance of the power wireless private network through a formula (3);
2) system capacity analysis
Because the coverage performance is the probability that the received SINR of the target user is greater than a certain threshold T, namely the distribution condition of the SINR, the system capacity of the network is calculated according to the Shannon theorem
Wherein the content of the first and second substances,
in the formula (4), W represents the system bandwidth, N represents the number of base station connection users, and the number is obtained from a network operator; and (4) estimating the system capacity of the electric power wireless private network through the formula (4).
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