CN109327851B - Super-dense heterogeneous cellular network user access method with separated coverage and data plane - Google Patents

Super-dense heterogeneous cellular network user access method with separated coverage and data plane Download PDF

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CN109327851B
CN109327851B CN201811473149.6A CN201811473149A CN109327851B CN 109327851 B CN109327851 B CN 109327851B CN 201811473149 A CN201811473149 A CN 201811473149A CN 109327851 B CN109327851 B CN 109327851B
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base station
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钱志鸿
朱巧
黄岚
许建华
向长波
王雪
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Jilin University
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Abstract

The invention belongs to the technical field of ultra-dense heterogeneous cellular network user access, and discloses an ultra-dense heterogeneous cellular network user access method with separated coverage and data plane, which is characterized in that a micro-cellular base station system model is established based on a Poisson cluster process; a user can cooperatively access service by a plurality of micro base stations distributed around the same hotspot; establishing a macro base station system model based on a poisson point process; under the premise that the macro base station is mainly responsible for completing a coverage function and the micro base station is responsible for high data rate transmission, respectively deducing an SINR (signal to interference ratio) distribution model and an interference distribution model received by macro base station users and micro base station users; deducing the average reachable rate of users in the network when the users are served by different types of base stations by utilizing an SINR distribution model and a known distance distribution model; and deducing reliable closed upper and lower bounds of the Laplace transform of the interference distribution model. The numerical simulation result shows that the method can obtain higher data rate.

Description

Super-dense heterogeneous cellular network user access method with separated coverage and data plane
Technical Field
The invention belongs to the technical field of ultra-dense heterogeneous cellular network user access, and particularly relates to an ultra-dense heterogeneous cellular network user access method with coverage separated from a data plane.
Background
Currently, the current state of the art commonly used in the industry is such that:
the random geometry is a mathematical tool with wide applicability for describing the spatial distribution of the network, is suitable for modeling the spatial distribution of the ultra-dense base station and the users, can more accurately describe the theoretical relationship between the performance index of the network and the network deployment parameters, and can provide reference for the deployment of the future ultra-dense heterogeneous cellular network.
In a traditional mobile wireless network, a user is served by a single user meeting the service index of the user, but with the ultra-dense deployment of base stations, the service mode is not applicable any more.
The base station with the user accessing multiple cooperative services is considered as an effective working mode to solve the high data rate requirement of future large-scale networks and simultaneously solve the problem of serious interference among densely deployed base stations. Based on the widely accepted data \ control separation architecture, the macro base station is responsible for forwarding all control signaling, and wide coverage is provided; the micro base station is used as a supplement to the hot spot area and is responsible for high data rate service. In this mode, there are two types of users, the first user is a macro base station user, and such users do not have high data transmission requirements and only need the macro base station to provide basic data transmission guarantee; the second is a micro base station user, which often needs a very high transmission rate and can be served by a plurality of base stations cooperatively.
In summary, the problems of the prior art are as follows:
(1) in the traditional mobile wireless network, a single user meeting the service index of the user provides service, but with the ultra-dense deployment of base stations, the distance between the base stations is shortened, a worse interference environment is formed, and the service mode is not suitable any more.
(2) The ultra-densely deployed micro base stations have the characteristic of being deployed in a hot spot area in a cluster, and the characteristic does not bring gain to the existing traditional network access mode and can also seriously interfere the communication between the service base station and the user.
(3) The future network is a structure with separated coverage and data, the ultra-dense network densely deploys micro base stations for high data rate transmission, and the macro base stations are used for controlling the comprehensive coverage of signals, so that a light-load network is formed, and although considerable cell splitting gain is brought, resource waste and low-frequency spectrum utilization rate are inevitably caused.
The significance of solving the technical problems is as follows:
by utilizing the clustering characteristic of the ultra-dense micro base stations and cooperatively serving the same user by the clustered micro base stations, considerable data rate gain can be brought.
In a lightly loaded network, the density of base stations is greater than that of users, and the base stations cooperatively serve the same user, so that considerable spectrum multiplexing gain can be brought.
The complex interference environment caused by the ultra-dense deployment of the base station needs to design a reliable interference cancellation algorithm and receiving hardware for interference cancellation, and the disadvantage of cluster deployment is aggravated. The clustered micro base station cooperative service directly avoids a plurality of nearest interference sources, has important significance for interference elimination, and can improve the resource utilization rate.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a super-dense heterogeneous cellular network user access method with separated coverage and data plane.
The invention is realized in such a way that a super-dense heterogeneous cellular network user access method with separated coverage and data plane comprises the following steps:
the macro base station is responsible for coverage, and clustered micro base station cooperation service users provide high data rate;
modeling a distribution model of a user and a macro base station based on a poisson point process, and establishing a micro base station distribution model in the poisson point process which is one of poisson cluster processes;
acquiring a distance distribution model between a base station and a user under different point process models;
deducing an SINR distribution model and an interference distribution model;
deducing an average reachable rate theoretical expression when users are respectively cooperatively served by a single macro base station or clustered micro base stations in the network by utilizing an SINR distribution model and a distance distribution model;
analyzing an interference distribution model of the super-dense heterogeneous network by using the Laplace transform of interference;
deducing reliable upper and lower bounds of Laplace transform of the interference distribution model;
obtaining the final upper bound and the final lower bound of the average reachable rate of the user through the cooperative service of a single macro base station or a plurality of clustered micro base stations by utilizing the result;
by comparing the average user reachable rate and the numerical simulation result of the poisson cluster process and the poisson point process under the same condition, it can be found that the clustered base station deployment can bring remarkable rate increase when in cooperative service. This is in contrast to the negative impact of clustered deployment when a single micro base station serves, which can result in significant throughput gain when cooperatively accessing.
Further, the user distribution and the macro base station distribution are respectively modeled as an intensity function of λuAnd λmThe micro base station position is modeled as a sub-process which is distributed around a hot spot location position as a parent process in the poisson point process, and the strength function of the parent process is lambdapAverage of the points in each cluster is
Figure BDA0001891497660000041
So the intensity function of the micro base station is
Figure BDA0001891497660000042
Wherein
Figure BDA0001891497660000043
The average value of the number of points in each cluster;
the micro base stations of different clusters are uniformly distributed in a circle which takes a user as a circle center and gamma as a radius, and have probability density functions of the following forms:
Figure BDA0001891497660000044
further, the obtained conclusion is popularized to users located at any position in the ultra-dense heterogeneous cellular network by utilizing the characteristics of the Poisson point process.
Furthermore, the macro base station is responsible for coverage by utilizing the characteristics of wide coverage range of the macro base station and dense deployment of the micro base stations, and the plurality of clustered micro base stations cooperatively serve the same user, so that the switching times in the moving process of the user can be effectively reduced, and the reachable data rate of the user is obviously improved.
Further, based on a poisson cluster process and a poisson point process, a system model is established, and a distance distribution model between a user and different base stations in a cluster is obtained, wherein the service distance distribution models from the user to a macro base station and a micro base station are respectively as follows:
Figure BDA0001891497660000045
Figure BDA0001891497660000046
wherein I0(. cndot.) is a first type of modified zero order Bessel function, and η is a scalar parameter. r is the distance between the user and the serving base station, | x0And | | is the relative distance between the user and the nearest clustered micro base station cluster center.
Further, the expression form of the SINR distribution model when the user is served by the macro base station and the micro base station respectively is as follows:
Figure BDA0001891497660000051
wherein the above expression is taken with the reference point of the typical user located at the origin, since the typical user can represent the performance of all users. Wherein, k is { m, s }, which respectively represents that the macro base station provides service and the micro base station provides service; sk={bm,CsAnd represents a served macro base station and a micro base station cluster of cooperative service, respectively. Assuming that macro base stations and micro base stations are deployed on different frequency bands,
Figure BDA0001891497660000052
and
Figure BDA0001891497660000053
respectively representing the cumulative interference, σ, experienced by the user from other peer base stations than the serving base station when served by the macro base station and the clustered micro base stations2Is additive white gaussian noise; the fading model in the network is Rayleigh distribution, the average value is 1, and the index alpha in the path fading model is more than 2.
Further, in the case of the ultra-dense heterogeneous cellular network, the model of the average achievable rate provided by any base station in the serving base station cluster for the user is as follows:
Figure BDA0001891497660000054
further, the definition of the lagrangian transformation using the poisson cluster process gives the lagrangian transformation of the accumulated interference received at the user as follows:
Figure BDA0001891497660000055
wherein
Figure BDA0001891497660000056
Further, in order to embody the superiority of the proposed access algorithm and take into account the computational complexity of the laplace transform of the poisson cluster process, a reliable upper bound and a reliable lower bound of the laplace transform convenient for analysis are proposed:
Figure BDA0001891497660000061
further, substituting the Laplace transform result into RsObtaining an upper bound and a lower bound of the average reachable rate of the network user, and decoupling the correlation between the nodes in the cluster to obtain:
Figure BDA0001891497660000062
Figure BDA0001891497660000063
wherein,
Figure BDA0001891497660000064
furthermore, the method utilizes the characteristic that ultra-dense micro base station deployment has clustering, uses a Poisson cluster process and a Poisson point process to respectively model the geographical position distribution of the micro base station and the macro base station, and provides an access method for cooperatively serving the same user by a plurality of micro base stations according to the characteristic of clustering, and simulation proves that the method is superior to the distribution and cooperative access of the micro base stations under the condition of the Poisson point process.
Another object of the present invention is to provide a super-dense heterogeneous cellular network user access computer program with separated coverage and data plane, which implements the super-dense heterogeneous cellular network user access method with separated coverage and data plane.
Another object of the present invention is to provide a terminal, which at least carries a server for implementing the ultra-dense heterogeneous cellular network user access method with separation of coverage and data plane.
It is another object of the present invention to provide a computer-readable storage medium comprising instructions which, when run on a computer, cause the computer to perform the above-mentioned ultra-dense heterogeneous cellular network user access method with separation of coverage and data plane.
Another objective of the present invention is to provide a system for controlling access to a super-dense heterogeneous cellular network user with separated coverage and data plane, which implements the method for accessing a super-dense heterogeneous cellular network user with separated coverage and data plane.
Another object of the present invention is to provide a network platform for carrying the ultra-dense heterogeneous cellular network user access control system with the separation of the coverage and the data plane.
In summary, the advantages and positive effects of the invention are:
the invention provides a user access method facing a future super-dense heterogeneous cellular network, aiming at the characteristic that micro base stations are deployed with clusters surrounding a hot spot area in the future super-dense heterogeneous cellular network, a Poisson cluster process is used for modeling the distribution characteristic; meanwhile, in order to avoid the continuous switching of the user between the micro base stations, based on a network architecture of coverage and data separation, the macro base station is utilized to provide wide coverage for the user, and the micro base station provides a high data rate connection service; on the basis, an access method for the same user of the ultra-dense base station cooperative service is provided, and cell splitting gain is effectively improved. And a theoretical expression of the average achievable rate is deduced by using a random geometric theory. And solving the reliable upper bound and the reliable lower bound of the Laplace transform which is easy to analyze and calculate to obtain the theoretical upper bound and the lower bound of the average reliable rate. Theoretical analysis and numerical simulation show that compared with the traditional user access mode, the method can provide higher data rate and more flexible access mode, and has important significance for development and research of ultra-dense heterogeneous cellular networks in the future.
The invention provides a super-dense base station cooperative access method under a coverage and data separation architecture, which provides a super-dense heterogeneous cellular network working mode that one user is cooperatively served by a plurality of micro base stations deployed in clusters, and can effectively avoid the interference problem caused by super-dense deployment of the micro base stations and improve the average reachable rate of the user; the space models of the macro base station and the micro base station are respectively modeled by utilizing a Poisson cluster process and a Poisson point process, so that a distance distribution model and an interference distribution model of the network are obtained, the average reachable rate of users in the network is analyzed, and the numerical simulation result shows that the method can obtain higher data rate. As shown in fig. 3, the star line represents the average achievable rate of the original access method. Compared with the traditional wireless single access mode, the access mode which considers the clustering characteristic and uses the clustering characteristic to cooperatively serve the user is considered, and the data rate which can be provided by a single base station is at least 3 times of that of the original access mode; as shown in fig. 4, the increase of the number of base stations in the cooperative service can bring about a linear increase of the achievable rate of the average user, which results in a considerable data rate gain, and compared with the data rate of the original single access method, the data rate is at least 2.5 times higher.
Drawings
Fig. 1 is a diagram of an operation model of a super-dense heterogeneous cellular network user access method with separated coverage and data plane according to an embodiment of the present invention;
fig. 2 is a flowchart of a cooperative access method of an ultra-dense base station based on a coverage and data separation architecture;
fig. 3 is a simulation result of the average achievable rates of users under different micro base station deployment densities according to an embodiment of the present invention.
Fig. 4 is a simulation result of the average achievable rates of users for the number of base stations serving different cooperative services.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The invention provides a super-dense base station cooperative access method under a coverage and data separation architecture, and provides a super-dense heterogeneous cellular network working mode in which one user is cooperatively served by a plurality of micro base stations deployed in clusters. The interference problem caused by ultra-dense deployment of the micro base station can be effectively avoided, and the average reachable rate of users is improved; the space models of the macro base station and the micro base station are respectively modeled by utilizing a Poisson cluster process and a Poisson point process, so that a distance distribution model and an interference distribution model of the network are obtained, the average reachable rate of users in the network is analyzed, and the numerical simulation result shows that the method can obtain higher data rate.
The application of the present invention is further described below in conjunction with specific assays.
As shown in fig. 1, the present invention provides a cooperative access method for super-dense base stations under a coverage and data separation architecture, wherein a plurality of base stations deployed in a cluster simultaneously provide a same user with a plurality of base stationsAnd (6) serving. And respectively modeling the micro base station and the macro base station through a poisson cluster process and a poisson point process. To achieve higher data transmission rates, more and more micro base stations are deployed in future ultra-dense heterogeneous cellular networks, and the number of base stations per square kilometer may be much larger than 103In addition, the future network will be a light-load network, and the coordinated multi-point transmission technology is feasible. And due to the characteristic of clustering of the micro base stations in hot spots, if the situation is served by a single base station, the clustered base stations will be serious interference. The invention utilizes the characteristic to provide cluster micro base station cooperative transmission, converts the disadvantage into the advantage and can bring considerable data rate gain.
As shown in fig. 2, the method for cooperative access of an ultra-dense base station under a coverage and data separation architecture provided by the present invention includes the following steps:
the macro base station is responsible for coverage, and clustered micro base station cooperation service users provide high data rate;
modeling a distribution model of a user and a macro base station based on a poisson point process, and establishing a micro base station distribution model in the poisson point process which is one of poisson cluster processes;
acquiring a distance distribution model between a base station and a user under different point process models;
deducing an SINR distribution model and an interference distribution model;
deducing an average reachable rate theoretical expression when users are respectively cooperatively served by a single macro base station or clustered micro base stations in the network by utilizing an SINR distribution model and a distance distribution model;
analyzing an interference distribution model of the super-dense heterogeneous network by using the Laplace transform of interference;
deducing reliable upper and lower bounds of Laplace transform of the interference distribution model;
obtaining the final upper bound and the final lower bound of the average reachable rate of the user through the cooperative service of a single macro base station or a plurality of clustered micro base stations by utilizing the result;
by comparing the average user reachable rate and the numerical simulation result of the poisson cluster process and the poisson point process under the same condition, it can be found that the clustered base station deployment can bring remarkable rate increase when in cooperative service. This is in contrast to the negative impact of clustered deployment when a single micro base station serves, which can result in significant throughput gain when cooperatively accessing.
The concrete method of the steps is as follows:
step 201: based on a future network control \ data separation architecture, a heterogeneous base station coverage plane and a data plane are decoupled, and a dynamic cooperation access mechanism of an ultra-dense network is researched. By utilizing the characteristic of clustered deployment of ultra-dense micro base stations, an access mode of a clustered base station for cooperatively serving the same user is designed, and the network performance is captured by utilizing Poisson cluster process modeling.
Step 202: user distribution and macro base station distribution are respectively modeled as intensity function lambdauAnd λmThe micro base station position is modeled as a sub-process which is distributed around a hot spot location position as a parent process in the poisson point process, and the strength function of the parent process is lambdapAverage of the points in each cluster is
Figure BDA0001891497660000111
So the intensity function of the micro base station is
Figure BDA0001891497660000112
Wherein
Figure BDA0001891497660000113
The average value of the number of points in each cluster;
the micro base stations of different clusters are uniformly distributed in a circle which takes a user as a circle center and gamma as a radius, and have probability density functions of the following forms:
Figure BDA0001891497660000114
step 203: based on a poisson cluster process and a poisson point process, a system model is established, distance distribution models between a user and different base stations in a cluster are obtained, and service distance distribution models from the user to a macro base station and a micro base station are respectively as follows:
Figure BDA0001891497660000115
Figure BDA0001891497660000116
wherein I0(. cndot.) is a first type of modified zero order Bessel function, and η is a scalar parameter. r is the distance between the user and the serving base station, | x0And | | is the relative distance between the user and the nearest clustered micro base station cluster center.
The expression form of the SINR distribution model when the user is respectively served by the macro base station and the micro base station is as follows:
Figure BDA0001891497660000117
wherein the above expression is taken with the reference point of the typical user located at the origin, since the typical user can represent the performance of all users. Wherein, k is { m, s }, which respectively represents that the macro base station provides service and the micro base station provides service; sk={bm,CsAnd represents a served macro base station and a micro base station cluster of cooperative service, respectively. Assuming that macro base stations and micro base stations are deployed on different frequency bands,
Figure BDA0001891497660000121
and
Figure BDA0001891497660000122
respectively representing the cumulative interference, σ, experienced by the user from other peer base stations than the serving base station when served by the macro base station and the clustered micro base stations2Is additive white gaussian noise; the fading model in the network is Rayleigh distribution, the average value is 1, and the index alpha in the path fading model is more than 2.
Step 204: under the condition of the super-dense heterogeneous cellular network, the model of the average reachable rate provided by any base station in the serving base station cluster for the user is as follows:
Figure BDA0001891497660000123
the definition of the lagrangian transform using the poisson cluster process gives the lagrangian transform of the accumulated interference received at the user as follows:
Figure BDA0001891497660000124
wherein
Figure BDA0001891497660000125
Step 205: in order to embody the superiority of the proposed access algorithm and take into account the computational complexity of the laplace transform of the poisson cluster process, the reliable upper and lower bounds of the laplace transform for facilitating the analysis are proposed here:
Figure BDA0001891497660000126
step 206: substituting the Laplace transform result into RsObtaining an upper bound and a lower bound of the average reachable rate of the network user, and decoupling the correlation between the nodes in the cluster to obtain:
Figure BDA0001891497660000131
Figure BDA0001891497660000132
wherein,
Figure BDA0001891497660000133
the embodiment of the invention provides a super-dense heterogeneous cellular network user access control system with separated coverage and data plane.
The application of the present invention is further described below in conjunction with simulation experiments.
In the embodiment of the present invention, in order to embody the superiority of the present invention, the obtained result is compared with the deployment situation of the ultra-dense base station based on the poisson point process through numerical simulation, and verification of the embodiment under a special situation is considered, that is, noise is not considered, α is 4, and a fading model adopts rayleigh fading, so that fig. 3 and fig. 4 can be obtained.
It can be easily found that, when the clustering characteristic is considered, that is, when a plurality of base stations in a cluster provide a cooperative service for a user, the performance of the average reachable rate of the user is better than that obtained based on the poisson point process. Moreover, as the number of base stations cooperatively served increases, the performance can be improved better, but the improvement is limited.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When used in whole or in part, can be implemented in a computer program product that includes one or more computer instructions. When loaded or executed on a computer, cause the flow or functions according to embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL), or wireless (e.g., infrared, wireless, microwave, etc.)). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that includes one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.

Claims (5)

1. An overlay and data plane separated ultra-dense heterogeneous cellular network user access method, wherein the overlay and data plane separated ultra-dense heterogeneous cellular network user access method comprises:
establishing a microcellular base station system model based on a Poisson cluster process;
a user is cooperatively accessed to service by a plurality of micro base stations distributed around the same hotspot;
establishing a macro base station system model based on a poisson point process;
the macro base station carries out control signal coverage, the micro base station carries out high data rate transmission, and a received SINR distribution model and an interference distribution model of macro base station users and micro base station users are respectively deduced;
deducing the average reachable rate of users in the network when the users are served by different types of base stations by utilizing an SINR distribution model and a known distance distribution model;
deducing reliable closed upper and lower bounds of Laplace transformation of the interference distribution model;
deducing upper and lower bounds of the average reachable speed of the user based on the reliable closed upper and lower bounds;
user distribution and macro base station distribution are respectively modeled as intensity function lambdauAnd λmThe micro base station position is modeled as a sub-process which is distributed around a hot spot location position as a parent process in the poisson point process, and the strength function of the parent process is lambdapAverage of the points in each cluster is
Figure FDA0003016082380000016
Intensity function of micro base station is
Figure FDA0003016082380000011
Wherein
Figure FDA0003016082380000012
The average value of the number of points in each cluster;
the micro base stations of different clusters are uniformly distributed in a circle which takes a user as a circle center and gamma as a radius, and have probability density functions of the following forms:
Figure FDA0003016082380000013
establishing a micro-cellular base station system model based on a Poisson cluster process, and acquiring distance distribution models between a user and different base stations in a cluster, wherein the service distance distribution models from the user to a macro base station and a micro base station are respectively as follows:
Figure FDA0003016082380000014
Figure FDA0003016082380000015
wherein I0(. h) is a first class of modified zero-order Bessel function, η is a scalar parameter, r is the distance between the user and the serving base station, | | x0The | | is the relative distance between the user and the nearest clustered micro base station cluster center;
the expression form of the SINR distribution model when the user is respectively served by the macro base station and the micro base station is as follows:
Figure FDA0003016082380000021
wherein, k is { m, s }, which respectively represents that the macro base station provides service and the micro base station provides service; p is a radical ofkIs the transmit power of the different layer base stations; sk={bm,CsRespectively representing a served macro base station and a micro base station cluster of cooperative service; assuming that macro base stations and micro base stations are deployed on different frequency bands,
Figure FDA0003016082380000022
and
Figure FDA0003016082380000023
respectively representing the cumulative interference, σ, experienced by the user from other peer base stations than the serving base station when served by the macro base station and the clustered micro base stations2Is additive white gaussian noise; fading model in network is hk,0Obeying Rayleigh distribution, the mean value is 1, and the path fading model index alpha is more than 2;
under the condition of the super-dense heterogeneous cellular network, the model of the average reachable rate provided by any base station in the serving base station cluster for the user is as follows:
Figure FDA0003016082380000024
wherein f iss(v) Representing the distance distribution function from the user to the cluster center of the nearest micro base station, fs(r | v) represents a relative distance distribution function of the micro base stations to the cluster center;
the number of base stations in different super-dense micro base station clusters is mu, and the Laplace transform of the accumulated interference received by a user is given by using the definition of the Laplace transform in the Poisson cluster process as follows:
Figure FDA0003016082380000025
wherein
Figure FDA0003016082380000031
The reliable upper and lower bounds are:
Figure FDA0003016082380000032
substituting the Laplace transform result into RsObtaining an upper bound and a lower bound of the average reachable rate of the network user, and decoupling the correlation between the nodes in the cluster to obtain:
Figure FDA0003016082380000033
Figure FDA0003016082380000034
wherein,
Figure FDA0003016082380000035
2. a terminal characterized in that it is equipped with at least a server implementing the ultra-dense heterogeneous cellular network user access method with separation of coverage and data plane according to claim 1.
3. A computer-readable storage medium comprising instructions that, when executed on a computer, cause the computer to perform the ultra-dense heterogeneous cellular network user access method with coverage separated from a data plane of claim 1.
4. An overlay and data plane separated ultra-dense heterogeneous cellular network user access control system implementing the overlay and data plane separated ultra-dense heterogeneous cellular network user access method of claim 1.
5. A network platform carrying the ultra dense heterogeneous cellular network user access control system with the overlay separated from the data plane of claim 4.
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