CN118102324A

CN118102324A - Networking method and device of macro base station, electronic equipment and computer program product

Info

Publication number: CN118102324A
Application number: CN202410362247.1A
Authority: CN
Inventors: 卢晓春; 耿雅雷; 杨涛
Original assignee: China Telecom Intelligent Network Technology Co ltd
Current assignee: China Telecom Intelligent Network Technology Co ltd
Priority date: 2024-03-27
Filing date: 2024-03-27
Publication date: 2024-05-28

Abstract

The invention discloses a networking method and device of macro base stations, electronic equipment and a computer program product. Wherein the method comprises the following steps: determining a target networking area comprising a plurality of narrowband internet of things terminals, a plurality of non-internet of things terminals and a plurality of dual-mode macro base stations, wherein the non-internet of things terminals comprise: the dual-mode macro base station is used for providing communication services for the long-term evolution technology terminal and the new air interface terminal; clustering a plurality of narrowband internet of things terminals in a target networking area to obtain a plurality of clusters; determining a dual-mode macro base station closest to the cluster head of each cluster from a plurality of dual-mode macro base stations as a target macro base station corresponding to the cluster; and controlling the target macro base station to provide communication service for the narrowband Internet of things terminals in the cluster corresponding to the target macro base station. The invention solves the technical problem of poor networking effect of the macro base station providing the standard signals due to different coverage areas of the multiple standard signals.

Description

Networking method and device of macro base station, electronic equipment and computer program product

Technical Field

The present invention relates to the field of communications, and in particular, to a macro base station networking method, apparatus, electronic device, and computer program product.

Background

Fig. 1 is a schematic diagram of a customized outdoor station networking in the prior art, as shown in fig. 1, an 800MHz dual-mode customized outdoor station is a device for implementing wireless access functions of LTE and NR, an integrated design of BBU and RRU is adopted, inter-station cascading is supported, independent RRU remote is supported, an 800MHz dual-mode customized outdoor station supports PON or STN backhaul, a flattened network architecture is adopted in the system, a machine room and a transmission network are not required to be rebuilt, and the system is suitable for application areas with weak signal coverage of rural hot spot areas, low-value indoor scenes in urban areas and the like. Compared with the traditional macro base station, the method has the advantages of quick network construction, low maintenance cost and the like.

A complete customized outdoor station comprises an integrated machine and a remote RRU. The integrated machine is used as a main core baseband unit of the customized outdoor station and is mainly responsible for baseband signal processing functions (coding, multiplexing, modulation, spread spectrum and the like), signaling processing, local and remote operation maintenance functions and working state monitoring and alarm information reporting functions of a small station system. The integrated machine has the radio frequency signal processing function, can complete the whole processing flow from a digital signal to an analog signal, and has a system architecture equivalent to the integration mode of BBU and RRU. The RRU structure is similar to RRU of indoor subsystem, mainly completes the whole process flow from digital signal to analog signal, and the difference is that the output power is increased to watt level, the coverage area is improved, and the requirement of outdoor coverage is satisfied. The MCL of LTE is 142.7dB, single station coverage of about 1.5 km.

The NB-IoT network, namely the narrowband internet of things technology, is constructed In a cellular network by adopting an unlicensed frequency band, can be directly deployed In a large scale In an LTE network, supports In-band deployment, adopts three modes of Guard-band deployment or independent (Stand-alone) deployment, only consumes 180kHz bandwidth, has MCL of 164dB, improves the maximum coverage by 15 km compared with LTE, realizes deep coverage, low power consumption, low cost and large connection design, supports mass connection and continuous wide area coverage, and provides a solution for rapid development of continuously growing markets of the internet of things, such as wearable equipment, intelligent meter reading and the like. At present, in rural areas, suburbs, frontier defense and other scenes, the traffic volume is low, coverage points are distributed, machine rooms and transmission resources are insufficient, the cost for independently deploying NB-IoT base stations is high, time is wasted, maintenance is not facilitated, and therefore operators consider remote upgrading of 800MHz dual-mode customized outdoor stations to deploy NB-IoT in the existing LTE structure, and the low-cost rapid networking in suburbs, rural areas and other scenes is realized.

The NB-IoT had a link budget of 164dB and the LTE had a link budget of 142.7dB (TR 36.888). There is a 20dB improvement in NB-IoT link budget compared to LTE, and open environment signal coverage can be increased seven times. Therefore, when a customized outdoor station high-power outdoor station supporting three systems of LTE, NR and NB-IoT is deployed, the coverage of LTE/NR is different from that of NB-IoT.

Fig. 2 is a schematic diagram of a customized outdoor station networking taking only coverage of a non-internet of things terminal (LTE/NR users) into consideration in the prior art, as shown in fig. 2, if a high-power outdoor station is deployed and only LTE/NR is considered, the distance between base stations is relatively short, coverage areas of NB-IoT overlap, NB-IoT base station resources are wasted, NB-IoT users access to the base stations, and inter-base station interference also exists.

Fig. 3 is a schematic diagram of a customized outdoor station networking taking only NB-IoT coverage into consideration in the prior art, as shown in fig. 3, if only NB-IoT coverage is considered, the distance between deployed base stations is far, and full coverage of LTE/NR cannot be guaranteed.

Aiming at the problem that the macro base station providing the standard signals has poor networking effect due to different coverage areas of the multiple standard signals, no effective solution is proposed at present.

Disclosure of Invention

The embodiment of the invention provides a macro base station networking method, a macro base station networking device, electronic equipment and a computer program product, which are used for at least solving the technical problem that macro base stations providing standard signals have poor networking effect due to different coverage areas of various standard signals.

According to an aspect of the embodiment of the present invention, there is provided a method for networking a macro base station, including: determining a target networking region, wherein the target networking region comprises: the system comprises a plurality of narrowband internet of things terminals, a plurality of non-internet of things terminals and a plurality of dual-mode macro base stations, wherein the non-internet of things terminals comprise: the dual-mode macro base station is used for providing communication services for the long-term evolution technology terminal and the new air interface terminal; clustering a plurality of narrowband internet of things terminals in the target networking region to obtain a plurality of clusters; determining a dual-mode macro base station closest to the cluster head of each cluster from the plurality of dual-mode macro base stations, and determining the dual-mode macro base station closest to the cluster head of each cluster as a target macro base station corresponding to the cluster; and controlling the target macro base station to provide communication service for the narrowband internet of things terminal in the cluster corresponding to the target macro base station.

Optionally, before determining the target networking region, the method further includes: acquiring an area to be networked and an area parameter of the area to be networked, wherein the area parameter at least comprises: a first preset parameter and a first signal to noise ratio threshold; deploying a plurality of non-internet of things terminals in the area to be networked according to the first preset parameters, wherein the first preset parameters are used for indicating the non-internet of things terminals to present poisson distribution in the area to be networked, and the non-internet of things terminals are distributed in the area to be networked according to a first density; deploying the dual-mode macro base station in the area to be networked according to the first signal-to-noise ratio threshold, wherein the first signal-to-noise ratio between the dual-mode macro base station and the non-internet of things terminal is larger than the first signal-to-noise ratio threshold; and determining the area to be networked, in which the non-Internet of things terminal and the dual-mode macro base station are arranged, as a pre-networking area.

Optionally, deploying the dual mode macro base station in the area to be networked according to the first signal-to-noise ratio threshold includes: estimating a non-internet-of-things channel between the non-internet-of-things terminal and the dual-mode macro base station by using a preset path loss model to obtain a first channel coefficient, wherein the preset path loss model describes the first channel coefficient by using a path loss constant, a path loss index, a large effect gain and a small effect gain; estimating a first subcarrier channel coefficient of the non-internet of things terminal and the dual-mode macro base station on subcarriers of the non-internet of things channel based on a first channel noise in combination with the first channel coefficient, wherein the non-internet of things channel is divided into a plurality of non-internet of things subchannels by using an orthogonal frequency division multiple access technology, each non-internet of things subchannel comprises at least one non-internet of things subcarrier transmitting a modulation signal, and the first channel noise represents that the channel noise in the non-internet of things channel is additive Gaussian white noise; determining the first signal-to-noise ratio based on the first subcarrier channel coefficient and non-internet-of-things channel power of the non-internet-of-things channel provided by the dual-mode macro base station; and adjusting the deployment position of the dual-mode macro base station in the area to be networked to enable the first signal-to-noise ratio to be larger than the first signal-to-noise ratio threshold.

Optionally, after determining that the area to be networked in which the non-internet of things terminal and the dual-mode macro base station are arranged is a pre-networking area, the method further includes: identifying a second preset parameter of the area to be networked, wherein the area parameter further comprises: the second preset parameters; according to the second preset parameters, a plurality of narrowband internet of things terminals are arranged in the pre-networking area, wherein the second preset parameters are used for indicating the narrowband internet of things terminals to present poisson distribution in the pre-networking area, and the narrowband internet of things terminals are distributed in the pre-networking area according to a second density; and determining the pre-networking area in which the narrowband internet of things terminal is arranged as the target networking area.

Optionally, clustering the plurality of narrowband internet of things terminals in the target networking area to obtain a plurality of clusters includes: determining a known cluster center selected in the target networking area, wherein the known cluster center at least comprises: an initial cluster center randomly selected in the target networking area for the first time; randomly selecting a plurality of candidate clustering centers in the target networking area; determining a known cluster center among a plurality of the candidate cluster centers, wherein a cluster center distance between the candidate cluster center and the known cluster center is proportional to a probability that the candidate cluster center is selected as the known cluster center; and clustering a plurality of narrowband internet of things terminals based on a plurality of known clustering centers to obtain a plurality of clustering clusters.

Optionally, determining, from the plurality of dual-mode macro base stations, the dual-mode macro base station closest to the cluster head of each cluster, and determining, as the target macro base station corresponding to the cluster, the dual-mode macro base station closest to the cluster head of each cluster includes: determining the narrowband internet of things terminals representing the characteristics of the cluster as the cluster head at a plurality of narrowband internet of things terminals of each cluster; determining the base station distance between the cluster head of the cluster and each dual-mode macro base station; and determining the dual-mode macro base station with the closest base station distance as a target macro base station corresponding to the cluster.

Optionally, controlling the target macro base station to provide communication services for the narrowband internet of things terminal in the cluster corresponding to the target macro base station includes: remotely upgrading a narrowband internet of things function for the target macro base station, wherein the narrowband internet of things function in the target macro base station is deployed in an independent mode, the target macro base station provides communication service for the narrowband internet of things terminal based on a narrowband internet of things channel, the narrowband internet of things channel is divided into a plurality of internet of things sub-channels by using an orthogonal frequency division multiple access technology, and each internet of things sub-channel comprises at least one internet of things sub-carrier for transmitting a modulation signal; controlling the target macro base station to allocate sub-carriers of the internet of things for each narrowband internet of things terminal in the cluster corresponding to the target macro base station; and controlling the target macro base station to distribute and transmit the narrow-band Internet of things channel power of each distributed Internet of things subcarrier by adopting a gradient descent method with the maximum throughput as a target.

Optionally, the method further comprises: under the condition that the narrow-band internet of things channel power is distributed by adopting the gradient descent method, evaluating the convergence of the gradient descent method, wherein the convergence represents whether an optimization result adopting the gradient descent method is converged or not; updating the clustering quantity of the narrowband internet of things terminal under the condition that the convergence is not converged; and updating the clusters of the plurality of narrowband internet of things terminals in the target networking area based on the updated cluster number.

Optionally, before controlling the target macro base station to use throughput as a target and adopting a gradient descent method to allocate and transmit the narrowband internet of things channel power of each allocated internet of things subcarrier, the method further comprises: estimating a narrowband internet of things channel between the narrowband internet of things terminal and the target macro base station by using a preset wireless coverage model to obtain a second channel coefficient, wherein the preset wireless coverage model describes the second channel coefficient by using propagation loss, working frequency, antenna height of the target macro base station, antenna height of the narrowband internet of things terminal, base station distance between the narrowband internet of things terminal and the target macro base station, an antenna correction function, a cell coverage type correction factor and an environmental topography correction factor; based on second channel noise and the second channel coefficient, estimating second subcarrier channel coefficients of the narrowband internet of things terminal and the target macro base station on the internet of things subcarriers, wherein the second channel noise represents that channel noise in the narrowband internet of things channel is additive Gaussian white noise; determining the second signal-to-noise ratio based on the second subcarrier channel coefficient and narrowband internet of things channel power of the narrowband internet of things channel provided by the target macro base station; and based on the second signal-to-noise ratio, evaluating the throughput of the target macro base station.

According to another aspect of the embodiment of the present invention, there is also provided a networking device of a macro base station, including: the first determining module is configured to determine a target networking area, where the target networking area includes: the system comprises a plurality of narrowband internet of things terminals, a plurality of non-internet of things terminals and a plurality of dual-mode macro base stations, wherein the non-internet of things terminals comprise: the dual-mode macro base station is used for providing communication services for the long-term evolution technology terminal and the new air interface terminal; the clustering module is used for clustering a plurality of the narrowband internet of things terminals in the target networking area to obtain a plurality of clusters; the second determining module is used for determining a dual-mode macro base station closest to the cluster head of each cluster from the plurality of dual-mode macro base stations, and determining the dual-mode macro base station closest to the cluster head of each cluster as a target macro base station corresponding to the cluster; the control module is used for controlling the target macro base station to provide communication service for the narrowband internet of things terminal in the cluster corresponding to the target macro base station.

According to another aspect of the embodiment of the present invention, there is also provided an electronic device, including: the system comprises a memory and a processor, wherein the processor is used for running a program stored in the processor, and the program executes a networking method of the macro base station when running.

According to another aspect of the embodiment of the present invention, there is further provided a nonvolatile storage medium, where the nonvolatile storage medium is configured to store a program, and when the program runs, control a device where the nonvolatile storage medium is located to execute the networking method of the macro base station.

According to another aspect of the embodiments of the present invention, there is also provided a computer program product comprising a computer program which, when executed by a processor, implements the steps of the networking method of a macro base station.

In the embodiment of the invention, a target networking area is determined, wherein the target networking area comprises: a plurality of narrowband thing networking terminals, a plurality of non-thing networking terminals and a plurality of bimodulus macro base station, non-thing networking terminal includes: the dual-mode macro base station is used for providing communication services for the long-term evolution technology terminal and the new air interface terminal; clustering a plurality of narrowband internet of things terminals in a target networking area to obtain a plurality of clusters; determining a dual-mode macro base station closest to the cluster head of each cluster from a plurality of dual-mode macro base stations, and determining the dual-mode macro base station closest to the cluster head of each cluster as a target macro base station corresponding to the cluster; the target macro base station is controlled to provide communication service for the narrowband internet of things terminals in the cluster corresponding to the target macro base station, so that in a target networking area for providing communication service for the long-term evolution technology terminal and the new air interface terminal by utilizing the dual-mode macro base station, the cluster is obtained by clustering the narrowband internet of things terminals in the target networking area, and the dual-mode macro base station nearest to the cluster head of the cluster provides communication service for the narrowband internet of things terminals in the cluster, thereby achieving the purpose of signal coverage of the narrowband internet of things, the long-term evolution technology and the new air interface in the target networking area, enabling the signal coverage of the narrowband internet of things, the long-term evolution technology and the new air interface not to be overlapped and omitted, realizing the technical effect of improving the networking effect of the macro base station, and further solving the technical problem of poor networking effect of the macro base station for providing signals due to different coverage of signals of various systems.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:

FIG. 1 is a schematic diagram of a customized outdoor station network of the prior art;

fig. 2 is a schematic diagram of a customized outdoor station networking taking only non-internet of things terminal (LTE/NR user) coverage into account in the prior art;

FIG. 3 is a prior art customized outdoor station networking schematic that only considers NB-IoT coverage;

Fig. 4 is a flowchart of a method of networking a macro base station according to an embodiment of the present invention;

FIG. 5 is a schematic diagram of an NB-IoT based 800MHz dual-mode customized outdoor station networking deployment optimization scheme in accordance with an embodiment of the present invention;

FIG. 6 is a schematic diagram of a two-dimensional distribution of a scene according to an embodiment of the invention;

FIG. 7 is a schematic diagram of a three-dimensional distribution of a scene that accounts for dual mode outdoor base station altitude according to an embodiment of the present invention;

Fig. 8 is a schematic diagram of a dual mode outdoor base station deploying NB-IoT in accordance with an embodiment of the present invention;

fig. 9 is a schematic diagram of a relationship between a number of deployed NB-IoT base stations, a number of NB-IoT terminals, and system throughput in accordance with an embodiment of the present invention;

FIG. 10 is a schematic diagram of an alignment throughput performance according to an embodiment of the invention;

Fig. 11 is a schematic diagram of comparing access rates of LTE users according to an embodiment of the invention;

fig. 12 is a schematic diagram of a networking device of a macro base station according to an embodiment of the present invention;

Fig. 13 is a block diagram of a computer terminal according to an embodiment of the present invention.

Detailed Description

In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.

It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

First, partial terms or terminology appearing in the course of describing embodiments of the application are applicable to the following explanation:

NB-IoT (Narrow Band Internet of Things): the narrowband internet of things technology is a low-power-consumption wide area network technology standard, is based on a cellular technology, is used for connecting various intelligent sensors and devices using a wireless cellular network, focuses on a low-power-consumption wide-coverage networking market, and is an emerging technology which can be widely applied in the global scope.

NR (New Radio): and 5G, a new air interface.

LTE (Long Time Evolution): 4G long term evolution technology.

BBU (Building Base band Unit): and a baseband unit.

RRU (Remote Radio Unit): a remote radio unit.

Integration station: BBU and RRU unify the design, realize baseband signal processing function and wireless access function's equipment.

LPWANs (Low Power Wide Area Networks): a low power wide area network.

PON (Passive Optical Network): a passive optical network.

STN (Smart Transport Network): an intelligent transmission network.

ONU (Optical Network Unit): an optical fiber network unit.

MCL (Maximum Coupling Loss): maximum coupling loss.

OFDMA (Orthogonal Frequency Division Multiple Access): orthogonal frequency division multiple access techniques.

TDD (Time Division Mode): time division multiplexing mode.

MBS (Macro Base Station): and (5) a macro base station.

SC-FDMA (SINGLE CARRIER Frequency Division Multiple Access): single carrier frequency division multiple access techniques.

QoS (Quality of Service): quality of service.

According to an embodiment of the present invention, there is provided a method embodiment of networking of macro base stations, it being noted that the steps shown in the flowchart of the figures may be performed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be performed in an order different from that shown or described herein.

Fig. 4 is a flowchart of a method for networking a macro base station according to an embodiment of the present invention, as shown in fig. 4, the method includes the following steps:

Step S102, determining a target networking area, wherein the target networking area comprises: a plurality of narrowband thing networking terminals, a plurality of non-thing networking terminals and a plurality of bimodulus macro base station, non-thing networking terminal includes: the dual-mode macro base station is used for providing communication services for the long-term evolution technology terminal and the new air interface terminal;

step S104, clustering a plurality of narrowband Internet of things terminals in a target networking area to obtain a plurality of clusters;

Step S106, determining a dual-mode macro base station closest to the cluster head of each cluster from a plurality of dual-mode macro base stations, and determining the dual-mode macro base station closest to the cluster head of each cluster as a target macro base station corresponding to the cluster;

Step S108, the target macro base station is controlled to provide communication service for the narrowband Internet of things terminals in the cluster corresponding to the target macro base station.

In the step S102, the narrowband internet of things terminal is an NB-IoT terminal, the long term evolution technology terminal is an LTE terminal, and the new air interface terminal is an NB terminal.

In the above step S102, the dual mode macro base station is a macro base station for providing at least the standard signals of LTE and NB.

The macro base station is a base station for covering a wide range in a mobile communication network, and is typically installed in a building or an overhead structure to provide wide area coverage and a large capacity communication service. They are commonly used for urban and suburban coverage to meet the communication needs of a large number of users.

In the step S104, a K-means++ algorithm is adopted to cluster a plurality of narrowband internet of things terminals in the target networking area, so as to obtain a plurality of cluster clusters, wherein each cluster comprises at least one narrowband internet of things terminal.

In the step S106, the cluster head selects, for each cluster, a narrowband internet of things terminal that best represents the characteristics of the cluster.

In the above step S108, the dual mode macro base station, which is the target macro base station, obtains the capability of providing the standard signal of NB-IoT by means of remote upgrade.

It should be noted that, the deployment of NB-IoT in the dual-mode customized outdoor station based on 800MHz has many advantages, on the one hand, the dual-mode high-power outdoor station introducing NB-IoT can support the extension pRRU according to the coverage requirement, improve the flexible deployment of the base station, and simultaneously can reduce the occupation of machine room and transmission resources, realize the on-demand low-specification, low-cost and rapid networking of special scenes, on the other hand, the base station supports the access of LTE users, NR users and NB-IoT users, and improves the reusability of the base station. Therefore, the NB-IoT is deployed at the dual-mode high-power outdoor station, and the method is an effective scheme for realizing on-demand low-specification, low-cost and rapid networking for special application scenes such as rural areas, frontier posts and the like.

As an alternative example, the target networking area may be an area where the dual-mode macro base station has been deployed, or an area where the dual-mode macro base station needs to be deployed.

Alternatively, in the case that the target networking area is an area where a dual-mode macro base station has been deployed, a dual-mode macro base station for which NB-IoT functionality needs to be upgraded may be selected in the target networking area by the above-described macro base station networking method.

Optionally, in the case that the target networking area is an area where the dual-mode macro base station needs to be deployed, the distribution of the non-internet of things terminals in the target networking area can be simulated, the deployment position of the dual-mode macro base station is determined based on the simulated distribution of the non-internet of things terminals, and then the dual-mode macro base station for upgrading the NB-IoT function is selected.

As an alternative embodiment, before determining the target networking area, the method further includes: acquiring an area to be networked and area parameters of the area to be networked, wherein the area parameters at least comprise: a first preset parameter and a first signal to noise ratio threshold; according to a first preset parameter, a plurality of non-Internet of things terminals are deployed in a region to be networked, wherein the first preset parameter is used for indicating that the non-Internet of things terminals are in poisson distribution in the region to be networked, and the non-Internet of things terminals are distributed in the region to be networked according to a first density; according to a first signal-to-noise ratio threshold, a dual-mode macro base station is deployed in an area to be networked, wherein the first signal-to-noise ratio between the dual-mode macro base station and a non-internet-of-things terminal is greater than the first signal-to-noise ratio threshold; and determining the area to be networked, in which the non-Internet of things terminal and the dual-mode macro base station are arranged, as a pre-networking area.

According to the embodiment of the invention, the area to be networked is an area where the dual-mode macro base station is not deployed, under the condition that the dual-mode macro base station is deployed for the area to be networked, the distribution condition and the distribution density of the non-Internet of things terminals in the area to be networked can be simulated according to the area parameters set for the area to be networked, then the deployment position of the dual-mode macro base station in the area to be networked is simulated, the signal-to-noise ratio between the simulated deployed dual-mode macro base station and each non-Internet of things terminal is evaluated, the deployment position of the simulated dual-mode macro base station in the area to be networked is adjusted, the signal-to-noise ratio between the dual-mode macro base station and each non-Internet of things terminal meets the signal-to-noise ratio requirement indicated in the area parameters, and even if the first signal-to-noise ratio is larger than the first signal-to-noise ratio threshold, the deployment position of the dual-mode macro base station in the area to be networked is determined, and the pre-networking area of the dual-mode macro base station is obtained, and networking of the dual-mode macro base station is realized.

It should be noted that, the dual-mode macro base station provides communication service for the non-internet of things terminal through the non-internet of things channel, and the non-internet of things channel can perform performance and capacity evaluation through signal to noise ratio.

The signal-to-interference-and-noise ratio SINR (Signal to Interference plus Noise Ratio), that is, the signal-to-interference-and-noise ratio, refers to the ratio of the intensity of the received useful signal to the intensity of the received interfering signal (noise and interference).

As an optional example, for the non-internet of things terminal NO-IoT-UE in the above scenario, it is not differentiated whether the LTE terminal (i.e. the long term evolution technology terminal) or the NR terminal (i.e. the new air interface terminal), which is uniformly defined as L { L ₁,L₂,…,L_l } non-internet of things terminals, and the spatial distribution of the non-internet of things terminals uses poisson distribution, the distribution density is the first density λ _a.

As an alternative embodiment, deploying the dual mode macro base station in the area to be networked according to the first signal to noise ratio threshold includes: estimating a non-Internet of things channel between a non-Internet of things terminal and a dual-mode macro base station by using a preset path loss model to obtain a first channel coefficient, wherein the preset path loss model describes the first channel coefficient by using a path loss constant, a path loss index, a large effect gain and a small effect gain; based on the first channel noise and the first channel coefficient, estimating a first subcarrier channel coefficient of the non-Internet of things terminal and the dual-mode macro base station on subcarriers of a non-Internet of things channel, wherein the non-Internet of things channel is divided into a plurality of non-Internet of things subchannels by using an orthogonal frequency division multiple access technology, each non-Internet of things subchannel comprises at least one non-Internet of things subcarrier transmitting a modulation signal, and the first channel noise represents that the channel noise in the non-Internet of things channel is additive Gaussian white noise; determining a first signal-to-noise ratio based on a first subcarrier channel coefficient and non-internet-of-things channel power of a non-internet-of-things channel provided by the dual-mode macro base station; and adjusting the deployment position of the dual-mode macro base station in the area to be networked to enable the first signal-to-noise ratio to be larger than a first signal-to-noise ratio threshold.

Optionally, the preset path loss model is a 3gpp TR 38.901 path loss model, where 3gpp TR 38.901 defines a path loss model for a 5G system, and the path loss model may be used to predict path loss between a base station (e.g., a dual mode macro base station) and a user equipment (e.g., a non-internet of things terminal) in the 5G system, so as to perform radio network planning and optimization, and help radio network planners and engineers perform efficient radio network planning and optimization operations.

As an optional example, N { N ₁,N₂,…,N_n } 800MHz dual-mode customized outdoor base stations MBS (i.e., dual-mode macro base stations) in the above scenario, for non-internet of things terminals NO-IoT-UE, the transmission power of the dual-mode macro base stations MBS (i.e., non-internet of things channel power) is Q _i, i e N, and the system bandwidth is 15MHz, all modeled by using OFDMA.

It should be noted that OFDMA (Orthogonal Frequency Division Multiple Access) is a multiple access technology commonly used in Wi-Fi and LTE communication systems, and it implements parallel transmission between multiple users by dividing the spectrum into multiple subcarriers.

According to the embodiment of the invention, the dual-mode macro base station provides communication service for the non-Internet of things terminal through the non-Internet of things channel, the non-Internet of things channel can be divided into a plurality of non-Internet of things sub-channels through the orthogonal frequency division multiple access technology, each non-Internet of things sub-channel comprises at least one non-Internet of things sub-carrier for transmitting the modulation signal, the quality of the non-Internet of things sub-carrier can be described through the signal to noise ratio, and the deployment position of the current dual-mode macro base station is reasonable under the condition that the signal to noise ratio meets the preset condition, such as the condition that the first signal to noise ratio is larger than a first signal to noise ratio threshold value; otherwise, under the condition that the signal to noise ratio does not meet the preset condition, if the first signal to noise ratio is not greater than the first signal to noise ratio threshold value, the current deployment position of the dual-mode macro base station is unreasonable, and the deployment position of the dual-mode macro base station is adjusted to be redetected until the first signal to noise ratio is not greater than the first signal to noise ratio threshold value position, so that the determination of the deployment position of the dual-mode macro base station is realized.

As an alternative example, for non-internet of things terminal NO-IoT-UE, assuming that all wireless channels (e.g., non-internet of things channels) exhibit rayleigh fading, the channel model of all links adopts the 3gpp TR 38.901 path loss model and exhibits large-effect fading and small-effect fading of the dual-mode macro base station MBS-i to the non-internet of things terminal NO-IoT-UE-j. Thus, the channel coefficient (e.g., the first channel coefficient g_NO-IoT _i,j) between the dual-mode macro base station MBS-i and the non-internet of things terminal NO-IoT-UE-j may be modeled as: Where J is the path loss constant, h _i,j is the large effect gain, B _i,j is the small effect gain, α is the path loss index,/> Is the distance between the dual-mode macro base station MBS-i and the non-internet of things terminal NO-IoT-UE-j.

As an optional example, if the additive white gaussian noise σ ² is subjected to normal distribution (0, σ ²) and OFDMA is used for modeling by using the OFDMA, then the channel coefficients (such as the first subcarrier channel coefficient) of the dual-mode macro base station MBS-i and the non-internet of things terminal NO-IoT-UE-j on the subcarrier δ (such as the non-internet of things subcarrier)) Can be modeled as:

As an alternative example, the signal-to-interference-plus-noise ratio SINR (i.e., first signal-to-noise ratio) of the non-internet of things terminal NO-IoT-UE is: wherein/> The transmitting power (such as non-internet of things channel power) of the non-internet of things subcarrier delta is transmitted between the dual-mode macro base station MBS-i and the non-internet of things terminal NO-IoT-UE-j.

As an optional embodiment, after determining that the area to be networked where the non-internet of things terminal and the dual-mode macro base station are arranged is a pre-networking area, the method further includes: identifying a second preset parameter of the area to be networked, wherein the area parameter further comprises: a second preset parameter; according to a second preset parameter, a plurality of narrowband internet of things terminals are deployed in a pre-networking area, wherein the second preset parameter is used for indicating that the narrowband internet of things terminals are in poisson distribution in the pre-networking area, and the narrowband internet of things terminals are distributed in the pre-networking area according to a second density; and determining a pre-networking area in which the narrowband internet of things terminal is arranged as a target networking area.

According to the embodiment of the invention, before the target macro base station is selected from the dual-mode macro base stations, the distribution condition and the distribution density of the narrowband internet of things terminals in the pre-networking area are simulated to obtain the target networking area, and then the dual-mode macro base station serving as the target macro base station can be determined based on the distribution condition of the narrowband internet of things terminals in the target networking area.

As an alternative example, for defining M { M ₁,M₂,…,M_m } narrowband internet of things terminals NB-UE in the above scenario, it is assumed that each narrowband internet of things terminal NB-UE is equipped with a single antenna, and the spatial distribution of the narrowband internet of things terminals uses poisson distribution, the distribution density being the second density λ _b.

As an optional example, the narrowband internet of things terminal NB-UE-j is defined as follows:

As an optional embodiment, clustering the plurality of narrowband internet of things terminals in the target networking area, to obtain a plurality of clusters includes: determining a known cluster center selected in the target networking area, wherein the known cluster center at least comprises: an initial clustering center randomly selected in a target networking area for the first time; randomly selecting a plurality of candidate clustering centers in a target networking area; determining a known cluster center among a plurality of candidate cluster centers, wherein a cluster center distance between the candidate cluster center and the known cluster center is proportional to a probability that the candidate cluster center is selected as the known cluster center; and clustering a plurality of narrowband internet of things terminals based on a plurality of known clustering centers to obtain a plurality of clustering clusters.

According to the embodiment of the invention, the narrowband Internet of things terminal can adopt the K-means++ algorithm for clustering, wherein the K-means++ algorithm is an improved K-Means clustering algorithm and is used for solving the problem of local optimal solution possibly caused by random initialization of the center point of the K-Means algorithm. The K-means++ algorithm selects initial clustering center points through an intelligent initialization method, so that the distance between the initial center points is as far as possible, and the convergence speed and the clustering effect of the K-Means algorithm are improved. The main steps include selecting a first cluster center point and then selecting other center points according to a certain probability so that the probability that a point farther from the selected center point is selected is greater. By the mode, the K-means++ algorithm can better select the initial clustering center point, and the accuracy and stability of clustering are improved.

As an alternative embodiment, determining, from a plurality of dual-mode macro base stations, a dual-mode macro base station closest to a cluster head of each cluster, and determining, as a target macro base station corresponding to the cluster, the dual-mode macro base station closest to the cluster head of each cluster includes: determining a narrow-band internet of things terminal representing the characteristics of the cluster as a cluster head at a plurality of narrow-band internet of things terminals of each cluster; determining the base station distance between the cluster head of the cluster and each dual-mode macro base station; and determining the dual-mode macro base station with the closest base station as a target macro base station corresponding to the cluster.

According to the embodiment of the invention, the cluster head selects the narrowband internet of things terminal which can most represent the characteristics of each cluster head for each cluster head, after the cluster head of each cluster head is determined, the distance between the cluster head and each dual-mode macro base station in the target networking area can be calculated, then the dual-mode macro base station closest to the cluster head is determined as the target macro base station corresponding to the cluster head, the cluster head provides NB-IoT service for the corresponding target macro base station, a plurality of cluster heads respectively have the corresponding target macro base station, and the plurality of cluster heads also respectively provide NB-IoT service for the corresponding target macro base station, so that the determination of the target macro base station is realized.

As an optional embodiment, controlling the target macro base station to provide the communication service for the narrowband internet of things terminal in the cluster corresponding to the target macro base station includes: the method comprises the steps that a narrowband Internet of things function is remotely upgraded for a target macro base station, wherein the narrowband Internet of things function in the target macro base station is deployed in an independent mode, the target macro base station provides communication service for a narrowband Internet of things terminal based on a narrowband Internet of things channel, the narrowband Internet of things channel is divided into a plurality of Internet of things sub-channels by using an orthogonal frequency division multiple access technology, and each Internet of things sub-channel comprises at least one Internet of things sub-carrier for transmitting a modulation signal; controlling a target macro base station to allocate sub-carriers of the Internet of things for each narrowband Internet of things terminal in a cluster corresponding to the target macro base station; and controlling the target macro base station to distribute and transmit the narrow-band Internet of things channel power of each distributed Internet of things subcarrier by adopting a gradient descent method with the maximum throughput as a target.

According to the embodiment of the invention, the target macro base station can obtain the capability of providing communication service for the narrowband Internet of things terminals in a manner of remotely upgrading the narrowband Internet of things function, so that the target macro base station with the upgraded narrowband Internet of things function can allocate the subcarriers of the Internet of things for each narrowband Internet of things terminal in the corresponding cluster, and allocate the narrowband Internet of things channel power of the subcarriers of the Internet of things for each narrowband Internet of things terminal with the maximum throughput as a target, thereby realizing the balance of terminal coverage and optimizing the communication resource allocation manner.

As an optional example, controlling the target macro base station to be each narrowband internet of things terminal in the cluster corresponding to the target macro base station, and allocating the subcarriers of the internet of things specifically includes: based on the carrier allocation design scheme of the time division multiplexing mode TDD, in the system model, the maximum number of each NB-IoT subcarrier (such as the subcarrier of the internet of things) is 12. In order to reduce the complexity of the solution, in each cluster, a narrowband internet of things terminal NB-IoT accesses an NB-IoT outdoor station (such as a target macro base station) through a TDD mode for data transmission.

As an optional example, the specific manner of controlling the target macro base station to allocate and transmit the narrowband internet of things channel power of each allocated internet of things subcarrier by using the gradient descent method with the throughput as the target, includes: throughput of each narrowband internet of things terminal NB-IoT can be verified through lagrangian median theoremAnd the constraint is also a convex function, so that each narrowband internet of things terminal can obtain a power distribution factor through convex optimization to obtain the throughput maximum value. Since the system throughput is the sum of the data rates of all the narrowband internet of things terminals, and is defined by the convex function, the system throughput is known to be a power distribution factorThe present application therefore uses a gradient descent method to find the optimal power division factor to maximize system throughput.

As an alternative embodiment, the method further comprises: under the condition that the narrow-band internet of things channel power is distributed by adopting a gradient descent method, evaluating the convergence of the gradient descent method, wherein the convergence indicates whether an optimization result adopting the gradient descent method is converged or not; updating the clustering quantity of the narrowband internet of things terminals under the condition that the convergence is not converged; and updating the clusters of the plurality of narrowband internet of things terminals in the target networking area based on the updated cluster number.

In the above embodiment of the present invention, under the condition that the channel power of the narrowband internet of things is allocated by adopting the gradient descent method, if the analysis result is that the channel power of the narrowband internet of things cannot be allocated in a manner of taking the throughput as the maximum target, the clustering number can be adjusted, the clustering of the plurality of narrowband internet of things terminals in the target networking area is re-performed to obtain a new cluster, then the target macro base station is re-selected, and the channel power of the narrowband internet of things is allocated again in a manner of taking the throughput as the maximum target until the channel power of the narrowband internet of things can be allocated in a manner of taking the throughput as the maximum target, otherwise, the clustering number is continuously updated for multiple clustering.

As an optional embodiment, before the control target macro base station uses the gradient descent method to allocate and transmit the narrowband internet of things channel power of each allocated internet of things subcarrier with the throughput as the target, the method further includes: estimating a narrowband internet of things channel between a narrowband internet of things terminal and a target macro base station by using a preset wireless coverage model to obtain a second channel coefficient, wherein the preset wireless coverage model describes the second channel coefficient by using propagation loss, working frequency, antenna height of the target macro base station, antenna height of the narrowband internet of things terminal, base station distance between the narrowband internet of things terminal and the target macro base station, an antenna correction function, a cell coverage type correction factor and an environmental topography correction factor; based on the second channel noise and the second channel coefficient, estimating the second subcarrier channel coefficient of the narrowband Internet of things terminal and the target macro base station on the Internet of things subcarrier, wherein the second channel noise represents that the channel noise in the narrowband Internet of things channel is additive Gaussian white noise; determining a second signal-to-noise ratio based on a second subcarrier channel coefficient and narrowband Internet of things channel power of a narrowband Internet of things channel provided by the target macro base station; and based on the second signal-to-noise ratio, evaluating the throughput of the target macro base station.

As an optional example, for a narrowband internet of things terminal NB-UE, a target macro base station MBS adopts an independent antenna feed system, an independent mode stand-alone deploys NB-IoT, the transmitting power of the target macro base station MBS (i.e., the channel power of the narrowband internet of things) is P _i, i is e N, N is less than or equal to N, the downlink is modeled by using an Orthogonal Frequency Division Multiple Access (OFDMA) technology, and the uplink is modeled by using a single carrier frequency division multiple access (SC-FDMA) technology.

Optionally, the dual mode macro base station is defined as follows:

Optionally, assuming that the system bandwidth of NB-IoT is 180kHz, and uplink and downlink use 15kHz subcarrier spacing, the number of available subcarrier spacing γ is 12, and the dual-mode macro base station is defined as follows:

As an alternative example, for a narrowband internet of things terminal NB-UE, assuming that all channels (e.g. narrowband internet of things channels) employ a wireless coverage model Okumura-Hata (i.e. a preset wireless coverage model), then the channel coefficient (e.g. the second channel coefficient g _i,j) between the target macro base station MBS-i and the narrowband internet of things terminal NB-UE-j at subcarrier γ (e.g. the internet of things subcarrier) may be modeled as ：g_i,j＝69.55+26.16lg(f_c)-13.82lg(h_b)-α(h_m)+(44.9-6.55lg(h_m))lg(d)+C_cell+C_te, where g _i,j is the propagation loss, in d B, f _c is the operating frequency, h _b is the antenna height of the target macro base station, (h _m) is the antenna height of the narrowband internet of things terminal, d is the base station distance of the narrowband internet of things terminal from the target macro base station, α (h _m) is the antenna correction function, since there is a difference in antenna structure, C _cell is a cell coverage type correction factor, since the cell is a different coverage type, C _te is a different environmental topography correction factor, which may be obtained according to an actual situation test or specified by the user.

Optionally, the channel noise for the narrowband internet of things channel is Additive White Gaussian Noise (AWGN) σ ² =n0×b/γ, where N0 is the noise power spectral density.

Optionally, a channel coefficient (such as a second subcarrier channel coefficient) between the target macro base station MBS-i and the narrowband internet of things terminal NB-UE-j on subcarrier gamma (such as an internet of things subcarrier)) Can be modeled as: /(I)

It should be noted that, because NB-IoT adopts independent deployment, the center frequency point is independent of LTE and NR signals, so that interference influence from LTE and NR signals is not considered, OFDMA is adopted to allocate one subcarrier to each narrowband internet of things terminal, and because subcarriers are mutually orthogonal, there is no inter-subcarrier interference with a base station, but narrowband internet of things terminal NB-UE in an edge region may be interfered with by inter-subcarrier interference from neighboring base station k to narrowband internet of things terminal NB-UE-jSame carrier interference/>, with other narrowband internet of things terminals of neighboring base station kTherefore, the signal-to-noise ratio (such as the second signal-to-noise ratio) of the target macro base station MBS-i received by the narrowband internet of things terminal NB-UE-j on the subcarrier gamma is as follows: wherein/> The transmitting power of the sub-carrier gamma of the internet of things (such as the channel power of the narrow-band internet of things) is transmitted between the target macro base station MBS-i and the narrow-band internet of things terminal NB-UE-j.

Alternatively, throughputThis can be expressed by a second signal-to-noise ratio: /(I)

The invention also provides an alternative embodiment, which provides an optimization scheme for deployment of networking of an 800MHz dual-mode customized outdoor station based on NB-IoT, deployment of NB-IoT in an 800MHz dual-mode high-power outdoor station requires consideration of coverage areas of LTE, NR and NB-IoT at the same time, and a reasonable networking scheme of the dual-mode high-power station is provided, so that the coverage problem that LTE, NR and NB-IoT exist in the same base station at the same time is solved.

Fig. 5 is a schematic diagram of an NB-IoT based 800MHz dual mode customized outdoor station networking deployment optimization scheme, as shown in fig. 5, according to an embodiment of the present invention, comprising the steps of:

In step S51, the 800MHz customized outdoor station (e.g. dual mode macro base station) is deployed according to SINR requirements (e.g. first signal to noise ratio threshold) of LTE terminals and NR terminals and other non-internet of things terminals in the target area (e.g. target networking area).

Step S52, clustering the NB-IoT terminals by adopting a K-means++ algorithm, and remotely upgrading the NB-IoT by a customized outdoor station (such as a target macro base station) positioned at the cluster head, so as to provide services for the NB-IoT terminals in the clustered cluster.

Step S53, carrying out subcarrier allocation on each NB-IoT terminal in the cluster according to the TDD mode.

And step S54, performing power distribution on subcarriers by using a gradient descent method to the NB-IoT terminals in each cluster to obtain the optimal system throughput.

Step S55, judging whether the optimization target is converged, if so, stopping, otherwise, returning to step S52.

Optionally, the step S51 includes the following steps:

step S511, generating an LTE terminal, an NR terminal and an NB-IoT terminal in a target area, and inputting a minimum SINR requirement (such as a first signal to noise ratio threshold);

Step S512, a customized outdoor station (e.g., a dual mode macro base station) is deployed according to the LTE terminal and the NR terminal and the NB-IoT terminal.

It should be noted that, in the dual-mode customized outdoor station based on NB-IoT, since the NB-IoT coverage area has a link budget improvement of 20dB compared to LTE, deploying the outdoor station only considering LTE needs causes NB-IoT resource waste, and the NB-IoT repeated coverage problem causes NB-IoT terminals to have neighbor station interference. While the outdoor station is deployed only considering NB-IoT requirements, the communication requirements of the LTE terminals cannot be met. Therefore, when the signals of the three systems of LTE/NR and NB-IoT exist in the same base station at the same time, how to perform base station networking deployment according to coverage difference, so as to provide communication services for the NB-IoT terminal, the LTE terminal and the NR terminal at the same time, and the problems of avoiding interference and efficiently distributing resources are to be further solved.

As an optional embodiment, the above embodiment of the present application is clearly deployed in the field in combination with the connection networking of the 800MHz customized outdoor station, and considers that the minimum signal to noise ratio of the non-internet of things terminal is satisfied, that is, the base station is deployed according to the coverage area of LTE/NR, then the K-means++ clustering algorithm is adopted to cluster NB-IoT terminals, the NB-IoT is upgraded for supporting NB-IoT terminals for the base station at the cluster head, then the subcarrier allocation is performed according to the number of terminals of the narrowband internet of things terminal in each cluster, and finally the power allocation is performed for the terminal in the service range of each upgraded NB-IoT base station. Since this problem is a convex optimization problem, a gradient descent method is used to find the optimal power allocation value for each base station to NB-IoT terminals to maximize system throughput.

As an alternative example, the NB-IoT deployment algorithm in combination with the algorithm of power and carrier allocation is as follows:

"INPUT:The LTE,NR and NB-IoT users position,The MBSs position and transmit power.The min SINR requirement for LTE,NR and NB-IoT.

OUTPUT:the MBSs with deploying NB-IoT,the optimized power allocation to maximizing system throughput;

1:Initialize:initialize thethe constraint of C1～C9,the maximum number of iterationsτ_max and iteration numberτ＝0；

2:

3:random

4:K-Means++clustering algorithm for NB-IoT users full coverage；

5:carrier allocation design with the number of NB-IoT users via TDD mode in each cluster head；

6:power allocation to obtainvia gradient descent method；

7:end”。

The above algorithm is an algorithm for deploying NB-IoT with the goal of taking as input the location of LTE, NR and NB-IoT terminals and the location and transmission power of the base station MBS, and outputting the MBS for deploying NB-IoT and optimized power allocation for maximizing system throughput. The main steps of the algorithm include initializing various parameters and then implementing the deployment of NB-IoT by iteratively optimizing power allocation. In the iterative process, the K-means++ clustering algorithm is used for carrying out complete coverage clustering on NB-IoT users, and then carrier allocation and power allocation are designed to obtain optimal system throughput.

As an alternative embodiment, the problem of repeated coverage and non-coverage caused by different coverage of signals of different systems is formulated, and the problem is expressed as that the maximum throughput is targeted: The constraints are as follows:

“Subject to：

C1:

C2:

C3

C4:

C5:

C6/>

C7:

C8:

C9:

Wherein C1 represents that the customized outdoor station MBS-i (e.g. dual-mode macro base station) meets the minimum signal to noise ratio constraint (e.g. first signal to noise ratio threshold) of the non-internet of things terminal NO-IoT-UE access, C2 represents that the customized outdoor station MBS-i (e.g. dual-mode macro base station) meets the minimum signal to noise ratio constraint of the narrowband internet of things terminal NB-IoT access, C3 represents that the sum of terminal received power in the coverage area of the customized outdoor station MBS-i (e.g. dual-mode macro base station) meets the base station transmit power constraint (for the narrowband internet of things channel power), C4, C5 represents that the power of the customized outdoor station MBS-i (e.g. dual-mode macro base station) at each subcarrier and each narrowband internet of things terminal NB-IoT (e.g. narrowband internet of things channel power) is constrained, C6 represents that the customized outdoor station system meets the full coverage constraint of the narrowband internet of things terminal NB-IoT in the range, C7 represents that the customized outdoor station MBS-i (e.g. dual-mode macro base station) received by the narrowband internet of things terminal NB-IoT-j has the useful signal, and C8, C9 represents that the customized outdoor station MBS-i (e.g. dual-base station) and the access constraint of the narrowband internet of terminal NB-IoT-j.

As an alternative embodiment, a dual-mode customized outdoor station may be deployed based on SINR requirements of terminals of different standards, which specifically includes: custom outdoor stations (e.g., dual mode macro base stations) for LTE and NR are deployed to guarantee SINR for LTE and NR terminals, taking into account the different coverage areas of the three cellular technologies LTE, NR and NB-IoT. And then clustering the NB-IoT terminals according to the SINR requirement of each terminal by using a K-means++ algorithm, upgrading the dual-mode macro base station MBS at the cluster head to support the NB-IoT, wherein each narrowband internet of things terminal in the cluster is served by the dual-mode macro base station MBS.

Alternatively, the maximum throughput may be expressed as: constraint s.t. is: c3, C4, C5, C7, C9; wherein/> And const is specifically expressed as follows:

const＝69.55+26.16lg(f_c)-13.82lg(h_b)-α(h_m)+C_cell+C_te。

As an alternative embodiment, carrier allocation may be performed based on TDD mode, specifically including: in the system model, the maximum number of subcarriers per NB-IoT is 12. In order to reduce the complexity of the solution, in each cluster, NB-IoT end users access NB-IoT outdoor stations (e.g., target macro base stations) for data transmission in a TDD manner. Thus, the maximum throughput can be expressed as:

Constraint s.t. is: c3, C4, C5, C7.

As an alternative embodiment, the power allocation may be performed based on throughput maximization, specifically including: throughput per NB-IoT terminal can be verified by lagrangian median theoremAs a convex function, the constraint is also a convex function, so that each terminal can obtain a power distribution factor through convex optimization to obtain the throughput maximum value. From the above equation, the system throughput is the sum of the data rates of all terminals, and is defined by a convex function, and is also the power allocation factor/>The present application therefore uses a gradient descent method to find the optimal power division factor to maximize system throughput.

Table 1 is a schematic table of system simulation parameters according to an embodiment of the present application, and as shown in table 1, the technical solution provided by the present application is compared with two other assumed comparison algorithms based on the system simulation parameters.

TABLE 1

Optionally, according to the simulation parameters of table 1, LTE, NR and NB-IoT terminals are distributed in rural scenarios of 10km by 10km, and the distribution mode adopts poisson distribution. The base station height is 25m and the terminal height is neglected to be 0 m.

As an alternative embodiment, two hypothetical comparison algorithms are described below:

Comparison algorithm 1: the macro base stations MBS of NB-IoT, which are deployed separately under the same scenario according to NB-IoT coverage, are labeled "only_nb_no_cluster".

Comparison algorithm 2: and clustering NB-IoT users under the same scene by using a K-means++ algorithm, and directly deploying base stations which normally provide NB-IoT, LTE and NR signal coverage at the CLUSTER head position, wherein the base stations are marked as 'NB/LTE/NR_CLUSTER'.

Fig. 6 is a schematic diagram of two-dimensional distribution of a scenario according to an embodiment of the present invention, as shown in fig. 6, considering a rural area scenario of 10km by 10km, LTE/NR terminals and NB-IoT terminals in the scenario obey poisson distribution, where densities are respectively: and lambda _a,λ_b, deploying the dual-mode outdoor base station according to the coverage of LTE/NR.

Fig. 7 is a schematic diagram of three-dimensional distribution of a scene considering the height of a dual mode outdoor base station according to an embodiment of the present invention, and as shown in fig. 7, the dual mode outdoor base station is fixed 25m high, and the user height is ignored as 0.

Fig. 8 is a schematic diagram of a dual-mode outdoor base station for deploying NB-IoT, as shown in fig. 8, in which a K-means++ clustering algorithm is adopted, a scene setting and a coverage range of the NB-IoT base station are combined, a reasonable number of cluster heads are set, an SINR value (such as a second signal to noise ratio threshold) of an NB terminal is used as a clustering condition, the NB terminal is clustered, and each cluster head after clustering is the dual-mode outdoor base station for deploying NB-IoT.

Fig. 9 is a schematic diagram of a relationship between a number of deployed NB-IoT base stations, a number of NB-IoT terminals, and system throughput, as shown in fig. 9, as the number of NB-IoT terminals increases, the need to connect NB-IoT base stations increases, and the overall system throughput increases, in accordance with an embodiment of the present invention. As the number of cluster heads of the cluster increases, the number of base stations deploying NB-IoT increases, the path loss between the terminal and the base stations decreases, and the system throughput increases.

As an optional embodiment, two deployment modes (i.e. the comparison algorithm 1 and the comparison algorithm 2) are selected to compare with the technical solution provided by the present application, and the deployment mode corresponding to the comparison algorithm 1 is equivalent to: in the same scene, an NB-IoT base station is deployed independently in a poisson distribution mode according to the coverage of the NB-IoT, the deployment mode is marked as 'ONLY_NB_NO_CLUSTER', and the deployment mode corresponding to the comparison algorithm 2 is equivalent to: and clustering the NB-IoT terminals by adopting a K-means++ algorithm in the same scene, and then only deploying outdoor base stations supporting the NB-IoT and LTE/NR in the CLUSTER head, wherein the outdoor base stations are marked as 'NB/LTE/NR_CLUSTER'.

Fig. 10 is a schematic diagram of comparing throughput performance of the above three algorithms in different NB-IoT terminals and NB-IoT base station numbers, as shown in fig. 10, and it can be seen that, under the condition that the base station resources are the same, as the NB-IoT terminal number increases, the system throughput of the three algorithms increases, where the system throughput performance of only deploying NB-IoT base stations is better than the scheme of the present application, and the scheme of the present application is better than the scheme of only supporting three systems for cluster head deployment; namely, after the target macro base station is selected, the sub-carriers of the internet of things are allocated for each narrowband internet of things terminal, and the narrow-band internet of things channel power for transmitting each sub-carrier of the allocated internet of things is allocated by adopting a gradient descent method with the maximum throughput as a target, so that better communication effect can be obtained compared with the method of directly upgrading NB-IoT for the target macro base station.

Fig. 11 is a schematic diagram comparing access rates of LTE users according to an embodiment of the present application, as shown in fig. 11, comparing access rates of LTE terminals of three algorithms, it can be seen that an algorithm supporting only NB-IoT base stations cannot provide services for LTE terminals, and the LTE access rate is 0, and as the number of base station deployments in a scene increases, the LTE terminal access rate increases only for algorithms supporting three systems in a cluster head deployment, but the growth trend slows down, and full coverage is not achieved, and the algorithm proposed by the scheme of the present application can achieve full coverage for LTE terminals. The system throughput and the coverage rate of terminal access are comprehensively considered, and the performance proposed by the scheme of the application is superior to that of a comparison algorithm.

According to the embodiment of the invention, through a high-efficiency outdoor macro base station networking deployment mode based on SINR requirements, the problem that NB-IoT is introduced into an 800MHz dual-mode customized outdoor base station system, and the coverage area of LTE, NR, NB-IoT signals in the same network is different is solved, meanwhile, the full coverage of an Internet of things terminal (NB-IoT) and non-Internet of things terminals (LTE, NR) is met, and the method is favorable for low-cost rapid network construction and networking optimization in low-value scenes such as rural areas, frontier sentry posts and the like.

In the above embodiment of the present invention, by using a throughput-maximized joint coverage optimization, power and carrier resource allocation algorithm, a dual-mode customized outdoor station (i.e., a dual-mode macro base station) is deployed based on SINR requirements of LTE and NR terminals, then a K-means++ algorithm is used to cluster NB-IoT terminals, and NB-IoT is upgraded for the dual-mode customized outdoor station at the cluster head position to access the NB-IoT terminals, and finally a gradient descent method is used to maximize system throughput.

Compared with the scheme of only deploying an 800MHz dual-mode customized outdoor station based on NB-IoT at a cluster head, the embodiment of the invention is beneficial to meeting the coverage requirement of non-internet of things terminals (namely LTE, NR terminals), and compared with the scheme of independently deploying NB-IoT, the embodiment of the invention is beneficial to meeting the communication requirements of users of three different systems at low cost, improves the resource utilization efficiency of a base station in low-value scenes such as rural areas, frontier sentry sites and the like, and realizes better balance in terms of solving the problem of full coverage of LTE terminals, NR terminals and NB-IoT terminals and optimizing the communication resource allocation mode.

According to the embodiment of the present invention, a macro base station networking device is further provided, and it should be noted that the macro base station networking device may be used to execute the macro base station networking method in the embodiment of the present invention, and the macro base station networking method in the embodiment of the present invention may be executed in the macro base station networking device.

Fig. 12 is a schematic diagram of a networking device of a macro base station according to an embodiment of the present invention, as shown in fig. 12, the device may include: a first determining module 1202, configured to determine a target networking area, where the target networking area includes: a plurality of narrowband thing networking terminals, a plurality of non-thing networking terminals and a plurality of bimodulus macro base station, non-thing networking terminal includes: the dual-mode macro base station is used for providing communication services for the long-term evolution technology terminal and the new air interface terminal; the clustering module 1204 is configured to cluster a plurality of narrowband internet of things terminals in the target networking area to obtain a plurality of clusters; a second determining module 1206, configured to determine, from the plurality of dual-mode macro base stations, a dual-mode macro base station that is closest to a cluster head of each cluster, and determine, as a target macro base station corresponding to the cluster, the dual-mode macro base station that is closest to the cluster head of each cluster; the control module 1208 is configured to control the target macro base station to provide a communication service for the narrowband internet of things terminal in the cluster corresponding to the target macro base station.

It should be noted that, the first determining module 1202 in this embodiment may be used to perform step S102 in the embodiment of the present application, the clustering module 1204 in this embodiment may be used to perform step S104 in the embodiment of the present application, the second determining module 1206 in this embodiment may be used to perform step S106 in the embodiment of the present application, and the control module 1208 in this embodiment may be used to perform step S108 in the embodiment of the present application. The above modules are the same as examples and application scenarios implemented by the corresponding steps, but are not limited to what is disclosed in the above embodiments.

As an alternative embodiment, the apparatus further comprises: the acquisition sub-module is used for acquiring the area to be networked and the area parameters of the area to be networked before determining the target networking area, wherein the area parameters at least comprise: a first preset parameter and a first signal to noise ratio threshold; the first deployment submodule is used for deploying a plurality of non-internet-of-things terminals in the area to be networked according to a first preset parameter, wherein the first preset parameter is used for indicating the non-internet-of-things terminals to present poisson distribution in the area to be networked, and the non-internet-of-things terminals are distributed in the area to be networked according to a first density; the second deployment submodule is used for deploying the dual-mode macro base station in the area to be networked according to a first signal-to-noise ratio threshold, wherein the first signal-to-noise ratio between the dual-mode macro base station and the non-internet-of-things terminal is larger than the first signal-to-noise ratio threshold; the first determining submodule is used for determining a to-be-networked area where the non-internet-of-things terminal and the dual-mode macro base station are arranged as a pre-networked area.

As an alternative embodiment, the second deployment sub-module comprises: the first evaluation unit is used for evaluating a non-Internet of things channel between the non-Internet of things terminal and the dual-mode macro base station by using a preset path loss model to obtain a first channel coefficient, wherein the preset path loss model describes the first channel coefficient by using a path loss constant, a path loss index, a large effect gain and a small effect gain; the second evaluation unit is used for evaluating a first subcarrier channel coefficient of the non-internet of things terminal and the dual-mode macro base station on subcarriers of the non-internet of things channel based on the first channel noise in combination with the first channel coefficient, wherein the non-internet of things channel is divided into a plurality of non-internet of things subchannels by using an orthogonal frequency division multiple access technology, each non-internet of things subchannel comprises at least one non-internet of things subcarrier for transmitting a modulation signal, and the first channel noise represents that the channel noise in the non-internet of things channel is additive Gaussian white noise; the first determining unit is used for determining a first signal-to-noise ratio based on the first subcarrier channel coefficient and non-internet-of-things channel power of a non-internet-of-things channel provided by the dual-mode macro base station; the adjusting unit is used for adjusting the deployment position of the dual-mode macro base station in the area to be networked so that the first signal-to-noise ratio is larger than the first signal-to-noise ratio threshold.

As an alternative embodiment, the apparatus further comprises: the identification sub-module is used for identifying a second preset parameter of the area to be networked after determining that the area to be networked of the non-internet of things terminal and the dual-mode macro base station is the pre-networking area, wherein the area parameter further comprises: a second preset parameter; the third deployment submodule is used for deploying a plurality of narrowband internet of things terminals in the pre-networking area according to second preset parameters, wherein the second preset parameters are used for indicating the narrowband internet of things terminals to present poisson distribution in the pre-networking area, and the narrowband internet of things terminals are distributed in the pre-networking area according to second density; and the second determining submodule is used for determining a pre-networking area where the narrowband internet of things terminal is arranged as a target networking area.

As an alternative embodiment, the clustering module includes: the second determining unit is configured to determine a known cluster center selected in the target networking area, where the known cluster center at least includes: an initial clustering center randomly selected in a target networking area for the first time; the selecting unit is used for randomly selecting a plurality of candidate clustering centers in the target networking area; a third determining unit configured to determine a known cluster center among a plurality of candidate cluster centers, wherein a cluster center distance between the candidate cluster center and the known cluster center is proportional to a probability that the candidate cluster center is selected as the known cluster center; and the clustering unit is used for clustering the plurality of narrowband internet of things terminals based on a plurality of known clustering centers to obtain a plurality of clustering clusters.

As an alternative embodiment, the second determining module includes: a fourth determining unit, configured to determine, at a plurality of narrowband internet of things terminals of each cluster, a narrowband internet of things terminal that represents a feature of the cluster as a cluster head; a fifth determining unit, configured to determine a base station distance between a cluster head of the cluster and each dual-mode macro base station; and the sixth determining unit is used for determining the dual-mode macro base station with the closest base station distance as the target macro base station corresponding to the cluster.

As an alternative embodiment, the control module includes: the system comprises an upgrading unit, a target macro base station and a control unit, wherein the upgrading unit is used for remotely upgrading a narrowband Internet of things function for the target macro base station, the narrowband Internet of things function in the target macro base station is deployed in an independent mode, the target macro base station provides communication service for a narrowband Internet of things terminal based on a narrowband Internet of things channel, the narrowband Internet of things channel is divided into a plurality of Internet of things sub-channels by using an orthogonal frequency division multiple access technology, and each Internet of things sub-channel comprises at least one Internet of things sub-carrier for transmitting a modulation signal; the first distribution unit is used for controlling the target macro base station to distribute sub-carriers of the Internet of things for each narrowband Internet of things terminal in the cluster corresponding to the target macro base station; the second allocation unit is used for controlling the target macro base station to allocate and transmit the narrow-band Internet of things channel power of each allocated Internet of things subcarrier by adopting a gradient descent method with the maximum throughput as a target.

As an alternative embodiment, the apparatus further comprises: the third evaluation unit is used for evaluating the convergence of the gradient descent method under the condition that the narrow-band internet of things channel power is distributed by the gradient descent method, wherein the convergence represents whether an optimization result by the gradient descent method is converged or not; the first updating unit is used for updating the clustering quantity of the narrowband internet of things terminal under the condition that the convergence is not converged; and the second updating unit is used for updating the clustering of the plurality of narrowband internet of things terminals in the target networking area based on the updated clustering quantity.

As an alternative embodiment, the apparatus further comprises: a fourth evaluation unit, configured to, before controlling the target macro base station to use the throughput as a target, and using a gradient descent method to allocate and transmit the narrowband internet of things channel power of each allocated internet of things subcarrier, evaluate a narrowband internet of things channel between the narrowband internet of things terminal and the target macro base station by using a preset wireless coverage model to obtain a second channel coefficient, where the preset wireless coverage model describes the second channel coefficient by using propagation loss, a working frequency, an antenna height of the target macro base station, an antenna height of the narrowband internet of things terminal, a base station distance between the narrowband internet of things terminal and the target macro base station, an antenna correction function, a cell coverage type correction factor, and an environmental topography correction factor; a fifth evaluation unit, configured to evaluate a second subcarrier channel coefficient of the narrowband internet of things terminal and the target macro base station on the internet of things subcarrier based on a second channel noise in combination with the second channel coefficient, where the second channel noise represents that a channel noise in the narrowband internet of things channel is an additive gaussian white noise; a seventh determining unit, configured to determine a second signal-to-noise ratio based on the second subcarrier channel coefficient and narrowband internet of things channel power of the narrowband internet of things channel provided by the target macro base station; and a sixth evaluation unit for evaluating the throughput of the target macro base station based on the second signal-to-noise ratio.

Embodiments of the present invention may provide a computer terminal, which may be any one of a group of computer terminals. Alternatively, in the present embodiment, the above-described computer terminal may be replaced with a terminal device such as a mobile terminal.

Alternatively, in this embodiment, the above-mentioned computer terminal may be located in at least one network device among a plurality of network devices of the computer network.

In this embodiment, the above-mentioned computer terminal may execute the program code of the following steps in the networking method of the macro base station: determining a target networking region, wherein the target networking region comprises: a plurality of narrowband thing networking terminals, a plurality of non-thing networking terminals and a plurality of bimodulus macro base station, non-thing networking terminal includes: the dual-mode macro base station is used for providing communication services for the long-term evolution technology terminal and the new air interface terminal; clustering a plurality of narrowband internet of things terminals in a target networking area to obtain a plurality of clusters; determining a dual-mode macro base station closest to the cluster head of each cluster from a plurality of dual-mode macro base stations, and determining the dual-mode macro base station closest to the cluster head of each cluster as a target macro base station corresponding to the cluster; and controlling the target macro base station to provide communication service for the narrowband Internet of things terminals in the cluster corresponding to the target macro base station.

Fig. 13 is a block diagram of a computer terminal according to an embodiment of the present invention, and as shown in fig. 13, the computer terminal 1300 may include: one or more (only one is shown) processors 1302, and memory 1304.

The memory may be used to store software programs and modules, such as program instructions/modules corresponding to the macro base station networking method and apparatus in the embodiments of the present invention, and the processor executes the software programs and modules stored in the memory, thereby executing various functional applications and data processing, that is, implementing the macro base station networking method described above. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory may further include memory located remotely from the processor, which may be connected to the terminal 1300 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The processor may call the information and the application program stored in the memory through the transmission device to perform the following steps: determining a target networking region, wherein the target networking region comprises: a plurality of narrowband thing networking terminals, a plurality of non-thing networking terminals and a plurality of bimodulus macro base station, non-thing networking terminal includes: the dual-mode macro base station is used for providing communication services for the long-term evolution technology terminal and the new air interface terminal; clustering a plurality of narrowband internet of things terminals in a target networking area to obtain a plurality of clusters; determining a dual-mode macro base station closest to the cluster head of each cluster from a plurality of dual-mode macro base stations, and determining the dual-mode macro base station closest to the cluster head of each cluster as a target macro base station corresponding to the cluster; and controlling the target macro base station to provide communication service for the narrowband Internet of things terminals in the cluster corresponding to the target macro base station.

Optionally, the above processor may further execute program code for: acquiring an area to be networked and area parameters of the area to be networked, wherein the area parameters at least comprise: a first preset parameter and a first signal to noise ratio threshold; according to a first preset parameter, a plurality of non-Internet of things terminals are deployed in a region to be networked, wherein the first preset parameter is used for indicating that the non-Internet of things terminals are in poisson distribution in the region to be networked, and the non-Internet of things terminals are distributed in the region to be networked according to a first density; according to a first signal-to-noise ratio threshold, a dual-mode macro base station is deployed in an area to be networked, wherein the first signal-to-noise ratio between the dual-mode macro base station and a non-internet-of-things terminal is greater than the first signal-to-noise ratio threshold; and determining the area to be networked, in which the non-Internet of things terminal and the dual-mode macro base station are arranged, as a pre-networking area.

Optionally, the above processor may further execute program code for: estimating a non-Internet of things channel between a non-Internet of things terminal and a dual-mode macro base station by using a preset path loss model to obtain a first channel coefficient, wherein the preset path loss model describes the first channel coefficient by using a path loss constant, a path loss index, a large effect gain and a small effect gain; based on the first channel noise and the first channel coefficient, estimating a first subcarrier channel coefficient of the non-Internet of things terminal and the dual-mode macro base station on subcarriers of a non-Internet of things channel, wherein the non-Internet of things channel is divided into a plurality of non-Internet of things subchannels by using an orthogonal frequency division multiple access technology, each non-Internet of things subchannel comprises at least one non-Internet of things subcarrier transmitting a modulation signal, and the first channel noise represents that the channel noise in the non-Internet of things channel is additive Gaussian white noise; determining a first signal-to-noise ratio based on a first subcarrier channel coefficient and non-internet-of-things channel power of a non-internet-of-things channel provided by the dual-mode macro base station; and adjusting the deployment position of the dual-mode macro base station in the area to be networked to enable the first signal-to-noise ratio to be larger than a first signal-to-noise ratio threshold.

Optionally, the above processor may further execute program code for: identifying a second preset parameter of the area to be networked, wherein the area parameter further comprises: a second preset parameter; according to a second preset parameter, a plurality of narrowband internet of things terminals are deployed in a pre-networking area, wherein the second preset parameter is used for indicating that the narrowband internet of things terminals are in poisson distribution in the pre-networking area, and the narrowband internet of things terminals are distributed in the pre-networking area according to a second density; and determining a pre-networking area in which the narrowband internet of things terminal is arranged as a target networking area.

Optionally, the above processor may further execute program code for: determining a known cluster center selected in the target networking area, wherein the known cluster center at least comprises: an initial clustering center randomly selected in a target networking area for the first time; randomly selecting a plurality of candidate clustering centers in a target networking area; determining a known cluster center among a plurality of candidate cluster centers, wherein a cluster center distance between the candidate cluster center and the known cluster center is proportional to a probability that the candidate cluster center is selected as the known cluster center; and clustering a plurality of narrowband internet of things terminals based on a plurality of known clustering centers to obtain a plurality of clustering clusters.

Optionally, the above processor may further execute program code for: determining a narrow-band internet of things terminal representing the characteristics of the cluster as a cluster head at a plurality of narrow-band internet of things terminals of each cluster; determining the base station distance between the cluster head of the cluster and each dual-mode macro base station; and determining the dual-mode macro base station with the closest base station as a target macro base station corresponding to the cluster.

Optionally, the above processor may further execute program code for: the method comprises the steps that a narrowband Internet of things function is remotely upgraded for a target macro base station, wherein the narrowband Internet of things function in the target macro base station is deployed in an independent mode, the target macro base station provides communication service for a narrowband Internet of things terminal based on a narrowband Internet of things channel, the narrowband Internet of things channel is divided into a plurality of Internet of things sub-channels by using an orthogonal frequency division multiple access technology, and each Internet of things sub-channel comprises at least one Internet of things sub-carrier for transmitting a modulation signal; controlling a target macro base station to allocate sub-carriers of the Internet of things for each narrowband Internet of things terminal in a cluster corresponding to the target macro base station; control target macro base station the throughput is at a maximum of the target, and distributing and transmitting the narrow-band Internet of things channel power of each distributed Internet of things subcarrier by adopting a gradient descent method.

Optionally, the above processor may further execute program code for: under the condition that the narrow-band internet of things channel power is distributed by adopting a gradient descent method, evaluating the convergence of the gradient descent method, wherein the convergence indicates whether an optimization result adopting the gradient descent method is converged or not; updating the clustering quantity of the narrowband internet of things terminals under the condition that the convergence is not converged; and updating the clusters of the plurality of narrowband internet of things terminals in the target networking area based on the updated cluster number.

Optionally, the above processor may further execute program code for: estimating a narrowband internet of things channel between a narrowband internet of things terminal and a target macro base station by using a preset wireless coverage model to obtain a second channel coefficient, wherein the preset wireless coverage model describes the second channel coefficient by using propagation loss, working frequency, antenna height of the target macro base station, antenna height of the narrowband internet of things terminal, base station distance between the narrowband internet of things terminal and the target macro base station, an antenna correction function, a cell coverage type correction factor and an environmental topography correction factor; based on the second channel noise and the second channel coefficient, estimating the second subcarrier channel coefficient of the narrowband Internet of things terminal and the target macro base station on the Internet of things subcarrier, wherein the second channel noise represents that the channel noise in the narrowband Internet of things channel is additive Gaussian white noise; determining a second signal-to-noise ratio based on a second subcarrier channel coefficient and narrowband Internet of things channel power of a narrowband Internet of things channel provided by the target macro base station; and based on the second signal-to-noise ratio, evaluating the throughput of the target macro base station.

The embodiment of the invention provides a networking scheme of a macro base station. Determining a target networking area, wherein the target networking area comprises: a plurality of narrowband thing networking terminals, a plurality of non-thing networking terminals and a plurality of bimodulus macro base station, non-thing networking terminal includes: the dual-mode macro base station is used for providing communication services for the long-term evolution technology terminal and the new air interface terminal; clustering a plurality of narrowband internet of things terminals in a target networking area to obtain a plurality of clusters; determining a dual-mode macro base station closest to the cluster head of each cluster from a plurality of dual-mode macro base stations, and determining the dual-mode macro base station closest to the cluster head of each cluster as a target macro base station corresponding to the cluster; the target macro base station is controlled to provide communication service for the narrowband internet of things terminals in the cluster corresponding to the target macro base station, so that in a target networking area for providing communication service for the long-term evolution technology terminal and the new air interface terminal by utilizing the dual-mode macro base station, the cluster is obtained by clustering the narrowband internet of things terminals in the target networking area, and the dual-mode macro base station nearest to the cluster head of the cluster provides communication service for the narrowband internet of things terminals in the cluster, thereby achieving the purpose of signal coverage of the narrowband internet of things, the long-term evolution technology and the new air interface in the target networking area, enabling the signal coverage of the narrowband internet of things, the long-term evolution technology and the new air interface not to be overlapped and omitted, realizing the technical effect of improving the networking effect of the macro base station, and further solving the technical problem of poor networking effect of the macro base station for providing signals due to different coverage of signals of various systems.

It will be appreciated by those of ordinary skill in the art that the configuration shown in FIG. 13 is merely illustrative and that the computer terminal may be a smart phone (e.g., tablet, palm and Mobile Internet device (Mobile INTERNET DEVICES, MID), PAD, etc.) and that FIG. 13 is not intended to limit the configuration of the electronic device described above.

Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be implemented by a program for instructing a terminal device to execute on hardware associated with the terminal device, the program may be stored in a nonvolatile storage medium, and the nonvolatile storage medium may include: flash disk, read-Only Memory (ROM), random-access Memory (Random Access Memory, RAM), magnetic disk or optical disk, etc.

Embodiments of the present invention also provide a nonvolatile storage medium. Alternatively, in this embodiment, the above-mentioned nonvolatile storage medium may be used to store the program code executed by the networking method of the macro base station provided in the above-mentioned embodiment.

Alternatively, in this embodiment, the above-mentioned nonvolatile storage medium may be located in any one of the computer terminals in the computer terminal group in the computer network, or in any one of the mobile terminals in the mobile terminal group.

Optionally, in the present embodiment, the non-volatile storage medium is arranged to store program code for performing the steps of: determining a target networking region, wherein the target networking region comprises: a plurality of narrowband thing networking terminals, a plurality of non-thing networking terminals and a plurality of bimodulus macro base station, non-thing networking terminal includes: the dual-mode macro base station is used for providing communication services for the long-term evolution technology terminal and the new air interface terminal; clustering a plurality of narrowband internet of things terminals in a target networking area to obtain a plurality of clusters; determining a dual-mode macro base station closest to the cluster head of each cluster from a plurality of dual-mode macro base stations, and determining the dual-mode macro base station closest to the cluster head of each cluster as a target macro base station corresponding to the cluster; and controlling the target macro base station to provide communication service for the narrowband Internet of things terminals in the cluster corresponding to the target macro base station.

Optionally, in the present embodiment, the non-volatile storage medium is arranged to store program code for performing the steps of: acquiring an area to be networked and area parameters of the area to be networked, wherein the area parameters at least comprise: a first preset parameter and a first signal to noise ratio threshold; according to a first preset parameter, a plurality of non-Internet of things terminals are deployed in a region to be networked, wherein the first preset parameter is used for indicating that the non-Internet of things terminals are in poisson distribution in the region to be networked, and the non-Internet of things terminals are distributed in the region to be networked according to a first density; according to a first signal-to-noise ratio threshold, a dual-mode macro base station is deployed in an area to be networked, wherein the first signal-to-noise ratio between the dual-mode macro base station and a non-internet-of-things terminal is greater than the first signal-to-noise ratio threshold; and determining the area to be networked, in which the non-Internet of things terminal and the dual-mode macro base station are arranged, as a pre-networking area.

Optionally, in the present embodiment, the non-volatile storage medium is arranged to store program code for performing the steps of: estimating a non-Internet of things channel between a non-Internet of things terminal and a dual-mode macro base station by using a preset path loss model to obtain a first channel coefficient, wherein the preset path loss model describes the first channel coefficient by using a path loss constant, a path loss index, a large effect gain and a small effect gain; based on the first channel noise and the first channel coefficient, estimating a first subcarrier channel coefficient of the non-Internet of things terminal and the dual-mode macro base station on subcarriers of a non-Internet of things channel, wherein the non-Internet of things channel is divided into a plurality of non-Internet of things subchannels by using an orthogonal frequency division multiple access technology, each non-Internet of things subchannel comprises at least one non-Internet of things subcarrier transmitting a modulation signal, and the first channel noise represents that the channel noise in the non-Internet of things channel is additive Gaussian white noise; determining a first signal-to-noise ratio based on a first subcarrier channel coefficient and non-internet-of-things channel power of a non-internet-of-things channel provided by the dual-mode macro base station; and adjusting the deployment position of the dual-mode macro base station in the area to be networked to enable the first signal-to-noise ratio to be larger than a first signal-to-noise ratio threshold.

Optionally, in the present embodiment, the non-volatile storage medium is arranged to store program code for performing the steps of: identifying a second preset parameter of the area to be networked, wherein the area parameter further comprises: a second preset parameter; according to a second preset parameter, a plurality of narrowband internet of things terminals are deployed in a pre-networking area, wherein the second preset parameter is used for indicating that the narrowband internet of things terminals are in poisson distribution in the pre-networking area, and the narrowband internet of things terminals are distributed in the pre-networking area according to a second density; and determining a pre-networking area in which the narrowband internet of things terminal is arranged as a target networking area.

Optionally, in the present embodiment, the non-volatile storage medium is arranged to store program code for performing the steps of: determining a known cluster center selected in the target networking area, wherein the known cluster center at least comprises: an initial clustering center randomly selected in a target networking area for the first time; randomly selecting a plurality of candidate clustering centers in a target networking area; determining a known cluster center among a plurality of candidate cluster centers, wherein a cluster center distance between the candidate cluster center and the known cluster center is proportional to a probability that the candidate cluster center is selected as the known cluster center; and clustering a plurality of narrowband internet of things terminals based on a plurality of known clustering centers to obtain a plurality of clustering clusters.

Optionally, in the present embodiment, the non-volatile storage medium is arranged to store program code for performing the steps of: determining a narrow-band internet of things terminal representing the characteristics of the cluster as a cluster head at a plurality of narrow-band internet of things terminals of each cluster; determining the base station distance between the cluster head of the cluster and each dual-mode macro base station; and determining the dual-mode macro base station with the closest base station as a target macro base station corresponding to the cluster.

Optionally, in the present embodiment, the non-volatile storage medium is arranged to store program code for performing the steps of: the method comprises the steps that a narrowband Internet of things function is remotely upgraded for a target macro base station, wherein the narrowband Internet of things function in the target macro base station is deployed in an independent mode, the target macro base station provides communication service for a narrowband Internet of things terminal based on a narrowband Internet of things channel, the narrowband Internet of things channel is divided into a plurality of Internet of things sub-channels by using an orthogonal frequency division multiple access technology, and each Internet of things sub-channel comprises at least one Internet of things sub-carrier for transmitting a modulation signal; controlling a target macro base station to allocate sub-carriers of the Internet of things for each narrowband Internet of things terminal in a cluster corresponding to the target macro base station; and controlling the target macro base station to distribute and transmit the narrow-band Internet of things channel power of each distributed Internet of things subcarrier by adopting a gradient descent method with the maximum throughput as a target.

Optionally, in the present embodiment, the non-volatile storage medium is arranged to store program code for performing the steps of: under the condition that the narrow-band internet of things channel power is distributed by adopting a gradient descent method, evaluating the convergence of the gradient descent method, wherein the convergence indicates whether an optimization result adopting the gradient descent method is converged or not; updating the clustering quantity of the narrowband internet of things terminals under the condition that the convergence is not converged; and updating the clusters of the plurality of narrowband internet of things terminals in the target networking area based on the updated cluster number.

Optionally, in the present embodiment, the non-volatile storage medium is arranged to store program code for performing the steps of: estimating a narrowband internet of things channel between a narrowband internet of things terminal and a target macro base station by using a preset wireless coverage model to obtain a second channel coefficient, wherein the preset wireless coverage model describes the second channel coefficient by using propagation loss, working frequency, antenna height of the target macro base station, antenna height of the narrowband internet of things terminal, base station distance between the narrowband internet of things terminal and the target macro base station, an antenna correction function, a cell coverage type correction factor and an environmental topography correction factor; based on the second channel noise and the second channel coefficient, estimating the second subcarrier channel coefficient of the narrowband Internet of things terminal and the target macro base station on the Internet of things subcarrier, wherein the second channel noise represents that the channel noise in the narrowband Internet of things channel is additive Gaussian white noise; determining a second signal-to-noise ratio based on a second subcarrier channel coefficient and narrowband Internet of things channel power of a narrowband Internet of things channel provided by the target macro base station; and based on the second signal-to-noise ratio, evaluating the throughput of the target macro base station.

Embodiments of the present invention also provide a computer program product, including a computer program. Optionally, in this embodiment, the computer program when executed by a processor implements the steps of the networking method of the macro base station provided in the foregoing embodiment.

The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.

In the foregoing embodiments of the present invention, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.

In the several embodiments provided in the present application, it should be understood that the disclosed technology may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of the units, for example, may be a logic function division, and may be implemented in another manner, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a non-volatile storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a non-volatile storage medium, including instructions for causing a computer device (which may be a personal computer, a server, a network device, or the like) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned nonvolatile storage medium includes: a usb disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.

The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.

Claims

1. A method for networking a macro base station, comprising:

Determining a target networking region, wherein the target networking region comprises: the system comprises a plurality of narrowband internet of things terminals, a plurality of non-internet of things terminals and a plurality of dual-mode macro base stations, wherein the non-internet of things terminals comprise: the dual-mode macro base station is used for providing communication services for the long-term evolution technology terminal and the new air interface terminal;

clustering a plurality of narrowband internet of things terminals in the target networking region to obtain a plurality of clusters;

determining a dual-mode macro base station closest to the cluster head of each cluster from the plurality of dual-mode macro base stations, and determining the dual-mode macro base station closest to the cluster head of each cluster as a target macro base station corresponding to the cluster;

And controlling the target macro base station to provide communication service for the narrowband internet of things terminal in the cluster corresponding to the target macro base station.

2. The method of claim 1, wherein prior to determining the target networking region, the method further comprises:

acquiring an area to be networked and an area parameter of the area to be networked, wherein the area parameter at least comprises: a first preset parameter and a first signal to noise ratio threshold;

Deploying a plurality of non-internet of things terminals in the area to be networked according to the first preset parameters, wherein the first preset parameters are used for indicating the non-internet of things terminals to present poisson distribution in the area to be networked, and the non-internet of things terminals are distributed in the area to be networked according to a first density;

Deploying the dual-mode macro base station in the area to be networked according to the first signal-to-noise ratio threshold, wherein the first signal-to-noise ratio between the dual-mode macro base station and the non-internet of things terminal is larger than the first signal-to-noise ratio threshold;

and determining the area to be networked, in which the non-Internet of things terminal and the dual-mode macro base station are arranged, as a pre-networking area.

3. The method of claim 2, wherein deploying the dual mode macro base station in the area to be networked according to the first signal-to-noise ratio threshold comprises:

estimating a non-internet-of-things channel between the non-internet-of-things terminal and the dual-mode macro base station by using a preset path loss model to obtain a first channel coefficient, wherein the preset path loss model describes the first channel coefficient by using a path loss constant, a path loss index, a large effect gain and a small effect gain;

Estimating a first subcarrier channel coefficient of the non-internet of things terminal and the dual-mode macro base station on subcarriers of the non-internet of things channel based on a first channel noise in combination with the first channel coefficient, wherein the non-internet of things channel is divided into a plurality of non-internet of things subchannels by using an orthogonal frequency division multiple access technology, each non-internet of things subchannel comprises at least one non-internet of things subcarrier transmitting a modulation signal, and the first channel noise represents that the channel noise in the non-internet of things channel is additive Gaussian white noise;

determining the first signal-to-noise ratio based on the first subcarrier channel coefficient and non-internet-of-things channel power of the non-internet-of-things channel provided by the dual-mode macro base station;

And adjusting the deployment position of the dual-mode macro base station in the area to be networked to enable the first signal-to-noise ratio to be larger than the first signal-to-noise ratio threshold.

4. The method of claim 2, wherein after determining that the area to be networked in which the non-internet of things terminal and the dual-mode macro base station are arranged is a pre-networking area, the method further comprises:

Identifying a second preset parameter of the area to be networked, wherein the area parameter further comprises: the second preset parameters;

According to the second preset parameters, a plurality of narrowband internet of things terminals are arranged in the pre-networking area, wherein the second preset parameters are used for indicating the narrowband internet of things terminals to present poisson distribution in the pre-networking area, and the narrowband internet of things terminals are distributed in the pre-networking area according to a second density;

And determining the pre-networking area in which the narrowband internet of things terminal is arranged as the target networking area.

5. The method of claim 1, wherein clustering the plurality of narrowband internet of things terminals in the target networking region to obtain a plurality of clusters comprises:

Determining a known cluster center selected in the target networking area, wherein the known cluster center at least comprises: an initial cluster center randomly selected in the target networking area for the first time;

Randomly selecting a plurality of candidate clustering centers in the target networking area;

Determining a known cluster center among a plurality of the candidate cluster centers, wherein a cluster center distance between the candidate cluster center and the known cluster center is proportional to a probability that the candidate cluster center is selected as the known cluster center;

And clustering a plurality of narrowband internet of things terminals based on a plurality of known clustering centers to obtain a plurality of clustering clusters.

6. The method of claim 1, wherein determining, from the plurality of dual-mode macro base stations, a dual-mode macro base station closest to a cluster head of each of the clusters and determining a dual-mode macro base station closest to a cluster head of each of the clusters as a target macro base station corresponding to the cluster comprises:

Determining the narrowband internet of things terminals representing the characteristics of the cluster as the cluster head at a plurality of narrowband internet of things terminals of each cluster;

Determining the base station distance between the cluster head of the cluster and each dual-mode macro base station;

And determining the dual-mode macro base station with the closest base station distance as a target macro base station corresponding to the cluster.

7. The method of claim 1, wherein controlling the target macro base station to provide communication services for the narrowband internet of things terminals within the cluster corresponding to the target macro base station comprises:

remotely upgrading a narrowband internet of things function for the target macro base station, wherein the narrowband internet of things function in the target macro base station is deployed in an independent mode, the target macro base station provides communication service for the narrowband internet of things terminal based on a narrowband internet of things channel, the narrowband internet of things channel is divided into a plurality of internet of things sub-channels by using an orthogonal frequency division multiple access technology, and each internet of things sub-channel comprises at least one internet of things sub-carrier for transmitting a modulation signal;

Controlling the target macro base station to allocate sub-carriers of the internet of things for each narrowband internet of things terminal in the cluster corresponding to the target macro base station;

And controlling the target macro base station to distribute and transmit the narrow-band Internet of things channel power of each distributed Internet of things subcarrier by adopting a gradient descent method with the maximum throughput as a target.

8. The method of claim 7, wherein the method further comprises:

Under the condition that the narrow-band internet of things channel power is distributed by adopting the gradient descent method, evaluating the convergence of the gradient descent method, wherein the convergence represents whether an optimization result adopting the gradient descent method is converged or not;

Updating the clustering quantity of the narrowband internet of things terminal under the condition that the convergence is not converged;

And updating the clusters of the plurality of narrowband internet of things terminals in the target networking area based on the updated cluster number.

9. The method of claim 7, wherein prior to controlling the target macro base station to allocate narrowband internet of things channel power transmitting each of the allocated internet of things sub-carriers using a gradient descent method with throughput maximization as a target, the method further comprises:

Estimating a narrowband internet of things channel between the narrowband internet of things terminal and the target macro base station by using a preset wireless coverage model to obtain a second channel coefficient, wherein the preset wireless coverage model describes the second channel coefficient by using propagation loss, working frequency, antenna height of the target macro base station, antenna height of the narrowband internet of things terminal, base station distance between the narrowband internet of things terminal and the target macro base station, an antenna correction function, a cell coverage type correction factor and an environmental topography correction factor;

Based on second channel noise and the second channel coefficient, estimating second subcarrier channel coefficients of the narrowband internet of things terminal and the target macro base station on the internet of things subcarriers, wherein the second channel noise represents that channel noise in the narrowband internet of things channel is additive Gaussian white noise;

Determining the second signal-to-noise ratio based on the second subcarrier channel coefficient and narrowband internet of things channel power of the narrowband internet of things channel provided by the target macro base station;

and based on the second signal-to-noise ratio, evaluating the throughput of the target macro base station.

10. A networking device of a macro base station, comprising:

The first determining module is configured to determine a target networking area, where the target networking area includes: the system comprises a plurality of narrowband internet of things terminals, a plurality of non-internet of things terminals and a plurality of dual-mode macro base stations, wherein the non-internet of things terminals comprise: the dual-mode macro base station is used for providing communication services for the long-term evolution technology terminal and the new air interface terminal;

the clustering module is used for clustering a plurality of the narrowband internet of things terminals in the target networking area to obtain a plurality of clusters;

The second determining module is used for determining a dual-mode macro base station closest to the cluster head of each cluster from the plurality of dual-mode macro base stations, and determining the dual-mode macro base station closest to the cluster head of each cluster as a target macro base station corresponding to the cluster;

The control module is used for controlling the target macro base station to provide communication service for the narrowband internet of things terminal in the cluster corresponding to the target macro base station.

11. An electronic device, comprising: a memory and a processor for executing a program stored in the processor, wherein the program is executed to perform the networking method of the macro base station according to any one of claims 1 to 9.

12. A non-volatile storage medium, wherein the non-volatile storage medium is configured to store a program, and wherein the program, when executed, controls a device in which the non-volatile storage medium is located to perform the networking method of the macro base station according to any one of claims 1 to 9.

13. A computer program product comprising a computer program, characterized in that the computer program, when executed by a processor, implements the steps of the networking method of macro base stations according to any of claims 1 to 9.