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CN118632372B - Bandwidth allocation method and system in wireless communication network - Google Patents

Bandwidth allocation method and system in wireless communication network Download PDF

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CN118632372B
CN118632372B CN202411097140.5A CN202411097140A CN118632372B CN 118632372 B CN118632372 B CN 118632372B CN 202411097140 A CN202411097140 A CN 202411097140A CN 118632372 B CN118632372 B CN 118632372B
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wireless communication
communication network
transmission data
bandwidth
network user
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CN118632372A (en
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颉斌
赵燕
惠绍明
周鹏
傅金玲
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Chinacomm Design & Consulting Co ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/50—Allocation or scheduling criteria for wireless resources
    • H04W72/56—Allocation or scheduling criteria for wireless resources based on priority criteria
    • H04W72/566—Allocation or scheduling criteria for wireless resources based on priority criteria of the information or information source or recipient
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G06N20/10—Machine learning using kernel methods, e.g. support vector machines [SVM]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/004—Artificial life, i.e. computing arrangements simulating life
    • G06N3/006—Artificial life, i.e. computing arrangements simulating life based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/16—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0457—Variable allocation of band or rate
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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Abstract

The invention relates to the technical field of wireless communication, in particular to a bandwidth allocation method and a system in a wireless communication network, wherein the system comprises a data acquisition module, a final SVM model construction module, a wireless communication network user service grade division module, an optimal threshold bandwidth setting module, a wireless communication network user real-time required bandwidth prediction module and a wireless communication user bandwidth allocation module, wherein the wireless communication network user is divided according to the corresponding wireless communication network user service grade, the optimal threshold bandwidth is allocated to each service grade, the real-time required bandwidth of the wireless communication network user is predicted through the final SVM model obtained through training, the bandwidth is allocated to all wireless communication network users according to the wireless communication network user service grade, the network requirements of the users are guaranteed, and meanwhile, unnecessary consumption of bandwidth resources is avoided.

Description

Bandwidth allocation method and system in wireless communication network
Technical Field
The invention relates to the technical field of wireless communication, in particular to a bandwidth allocation method and a bandwidth allocation system in a wireless communication network.
Background
With the rapid development of internet technology, the number of users of wireless communication networks is rapidly increasing, so that it is important to ensure the experience of users while reasonably and effectively distributing wireless communication network resources.
In the prior art, network usage information fed back to a system by a wireless communication network user is often received, a bandwidth required by the wireless communication network user is calculated according to the network usage information and a wireless communication resource allocation technology, and simultaneously, the required bandwidth is allocated to each wireless communication network user according to the bandwidth requirements of all the wireless communication network users, so that unnecessary consumption of bandwidth resources is easily caused, and unused bandwidth resources cannot be timely recovered.
Disclosure of Invention
(One) solving the technical problems
In order to solve the defects in the background technology, the invention provides a bandwidth allocation method and a bandwidth allocation system in a wireless communication network, which are used for allocating optimal threshold bandwidths for each service level by dividing wireless communication network users according to corresponding wireless communication network user service levels, predicting the bandwidth required by the wireless communication network users in real time through a final SVM model obtained by training, and allocating bandwidths for all the wireless communication network users according to the wireless communication network user service levels.
(II) technical scheme
A method of bandwidth allocation in a wireless communication network, the method comprising the steps of:
S1, setting a wireless communication network user set and a transmission data volume acquisition period set, and acquiring transmission data volumes of all wireless communication network users in the transmission data volume acquisition period set in the wireless communication network user set to obtain a transmission data volume matrix;
s2, constructing an initial SVM model, a transmission data quantity training matrix and a transmission data quantity testing matrix, and training and testing the initial SVM model through the transmission data quantity training matrix and the transmission data quantity testing matrix to obtain a final SVM model;
S3, setting a wireless communication network user service grade set, and dividing each wireless communication network user in the wireless communication network user set according to the corresponding wireless communication network user service grade to obtain a wireless communication network user grading matrix;
S4, setting an optimal threshold bandwidth for each wireless communication network user service level in the wireless communication network user service level set through an intelligent optimization algorithm to obtain an optimal threshold bandwidth set;
S5, acquiring transmission data quantity of each wireless communication network user in the wireless communication network user grading matrix in real time to obtain a real-time transmission data quantity matrix, setting a basic energy consumption transmission data quantity threshold value to correct the real-time transmission data quantity matrix to obtain a real-time transmission data quantity correction matrix, and predicting the bandwidth required by the wireless communication network user in real time through a final SVM model;
S6, allocating bandwidth for each wireless communication user in turn from high to low according to the service level of the wireless communication network user.
The method comprises the steps of acquiring a large amount of data, training and testing an initial SVM model to obtain a final SVM model, ensuring the accuracy of the final SVM model, providing a prediction tool for subsequent operation, dividing wireless communication network users according to corresponding wireless communication network user service levels, distributing optimal threshold bandwidths for each service level, meeting basic bandwidth requirements, determining the sequence of bandwidth distribution, distributing bandwidths for all wireless communication network users according to the wireless communication network user service levels according to a predicted bandwidth matrix required by the users in real time, and realizing effective distribution of wireless communication network bandwidth resources.
Preferably, a wireless communication network user set and a transmission data volume acquisition period set are set, and the transmission data volume of each wireless communication network user in the wireless communication network user set is acquired according to the transmission data volume acquisition period set, so as to obtain a specific step of a transmission data volume matrix:
S11, setting a wireless communication network user set Wherein, the method comprises the steps of, wherein,Represent the firstA user of the wireless communication network,Representing the total number of wireless communication network users;
s12, setting a transmission data quantity acquisition period set Wherein, the method comprises the steps of, wherein,Represent the firstA data volume acquisition period of the transmission,Representing the total number of transmission data quantity acquisition cycles;
S13, collecting wireless communication network user set In which each wireless communication network user is transmitting data quantity collection period setThe transmission data quantity of each transmission data quantity acquisition period in the network system is used for obtaining a transmission data quantity matrixThe following are provided:
Wherein, Represent the firstThe user of the wireless communication network is in the first placeThe amount of transmission data in each transmission data amount acquisition period.
The transmission data quantity of each wireless communication network user is acquired by setting the transmission data quantity acquisition period, so that the universality of the acquired data is ensured, and a data basis is provided for subsequent operation.
Preferably, an initial SVM model, a transmission data quantity training matrix and a transmission data quantity testing matrix are constructed, and training and testing are carried out on the initial SVM model through the transmission data quantity training matrix and the transmission data quantity testing matrix, so that a final SVM model is obtained, wherein the specific steps are as follows:
s21, constructing an initial SVM model, and setting penalty factor parameters as The radial basis parameters areAnd the kernel function of the initial parameter space in the operation process of the initial SVM model is a Gaussian radial basis function, wherein the Gaussian radial basis function has the following formula:
Wherein, Representing a gaussian radial basis function,Representing the corresponding support vectors for the two training samples,Representation ofAndA Euclidean distance between them;
S22, setting the training data proportion And test data ratioCarrying out data division on the transmission data quantity matrix through the training data proportion and the test data proportion to respectively obtain a transmission data quantity training matrix and a transmission data quantity test matrix;
s23, setting a training error threshold as Inputting the transmission data quantity training matrix into an initial SVM model to train the initial SVM model until the training error of the initial SVM model is smaller than or equal toWhen the training is stopped, a trained SVM model is obtained;
s24, setting a test accuracy threshold Inputting the transmission data measurement matrix into a trained SVM model for testing to obtain the bandwidth required by a wireless communication network user in real time, and calculating the accuracy of a test resultWhen testing accuracyGreater than or equal to the test accuracy thresholdIf not, searching the optimal penalty factor parameter and the optimal radial basis kernel parameter by using a grid search algorithm, and retesting the trained SVM model according to the optimal penalty factor parameter and the optimal radial basis kernel parameter until the test accuracy is reachedGreater than or equal to the test accuracy threshold;
S241, setting search ranges of penalty factor parameters and radial basis kernel parameters, and constructing a two-dimensional search grid;
S242, a group of penalty factor parameters and radial basis kernel parameters with highest testing accuracy are selected through large-step rough searching on the two-dimensional searching grid, and a two-dimensional optimal parameter searching grid is obtained;
S243, calculating the test accuracy of each group of penalty factor parameters and radial basis kernel parameters in the two-dimensional optimal parameter search grid according to a cross verification method, and selecting a pair of penalty factor parameters and radial basis kernel parameters with highest test accuracy as the optimal penalty factor parameters and the optimal radial basis kernel parameters.
Training and testing the initial SVM model through a large amount of acquired data to obtain a final SVM model, searching the optimal penalty factor parameters and the optimal radial basis kernel parameters by using a grid search algorithm, ensuring the accuracy of the prediction result of the final SVM model, and providing a prediction tool for subsequent operation.
Preferably, a service class set of wireless communication network users is set, each wireless communication network user in the wireless communication network user set is divided according to the corresponding service class of the wireless communication network user, and the specific steps for obtaining the wireless communication network user grading matrix are as follows:
S31, arranging the service grades of the wireless communication network users from high to low, and constructing a service grade set of the wireless communication network users Wherein, the method comprises the steps of, wherein,Represent the firstThe service level of a user of the wireless communication network,Representing the total number of service levels of the wireless communication network users;
S32, collecting the service grades of all the wireless communication network users, and grading according to the service grades of the wireless communication network users in the service grade set of the wireless communication network users to obtain a wireless communication network user grading matrix The following are provided:
Wherein, Represent the firstUser service level of wireless communication networkA user of the wireless communication network,Represent the firstThe total number of wireless communication network users in the individual wireless communication network user traffic class.
The wireless communication network users are divided according to the corresponding service levels of the wireless communication network users, the sequence of bandwidth allocation is determined, and a data base is provided for reasonable allocation of subsequent bandwidths.
Preferably, the method sets an optimal threshold bandwidth for each wireless communication network user service level in the wireless communication network user service level set through an intelligent optimization algorithm, and the specific steps for obtaining the optimal threshold bandwidth set are as follows:
S41, constructing an artificial bee colony, and setting the maximum honey source searching times Maximum number of iterationsCurrent iteration numberPopulation number;
S42, randomly generating in the search space of the artificial bee colonyThe formula for randomly generating the honey sources is as follows:
Wherein, Represent the firstThe honey source is at the firstThe location of the individual dimensions is such that,Representation ofA random number between the two random numbers,AndRespectively represent the firstUpper and lower limits of the vitamin honey source search space;
s43, calculating fitness function values of all randomly generated honey sources, wherein the fitness function formula is as follows:
Wherein, The function value of the fitness is represented,Representing the proportion of bandwidth that satisfies the use of the wireless communication network subscriber's underlying network,Representing the correction value;
s44, starting iteration, and selecting from the artificial bee population Each hiring bee is distributed with one hiring bee, each hiring bee searches for a new honey source nearby the current honey source, the fitness function value of the new honey source is calculated after the new honey source is found, if the fitness function value of the new honey source is higher than the fitness function value of the original honey source, the new honey source is used for replacing the original honey source, and the honey source position is updated, otherwise, the original honey source is reserved, and the current honey source is increased by one honey source search times, and the formula of the hiring bee search honey source is as follows:
Wherein, Indicating the location of the honey source after the update,Representation ofA random number between the two random numbers,Representation ofIs not equal toIs a random integer of (a) and (b),Represent the firstThe honey source is at the firstThe position of the individual dimensions;
S45, taking the rest artificial bees in the artificial bee population as following bees, selecting the honey source position of an employment bee through a roulette strategy, searching a new honey source nearby the current honey source according to a formula of searching the honey source by the following bees after the following bees reach the selected honey source position, calculating the fitness function value of the new honey source after finding the new honey source, replacing the original honey source by the new honey source if the fitness function value of the new honey source is higher than the fitness function value of the original honey source, and updating the honey source position, otherwise, retaining the original honey source, and increasing the honey source searching times once by the current honey source, wherein the probability calculation formula of selecting the employment bee is as follows:
Wherein, Represent the firstFitness function values of individual honey sources;
s46, recording the searching times of each honey source, wherein the searching times of the honey source reach the maximum honey source searching times When the honey source is abandoned, and the employment bees at the honey source location re-randomly generate new honey sources in the search space according to the step in S44;
s47, judging the current iteration times Whether or not the maximum number of iterations is reachedIf not, returning to S44, if so, calculating the fitness function value of all the current honey sources, selecting the honey source with the highest fitness function value as the current global optimal solution, and outputting the optimal threshold bandwidth of each wireless communication network user service level to obtain an optimal threshold bandwidth set.
Setting the optimal threshold bandwidth of each wireless communication network user service level by using an artificial bee colony algorithm, and establishing a mathematical model by simulating the foraging behavior of the bee colony in the nature, so as to ensure the speed and accuracy of the optimizing process and improve the efficiency of the convergence process.
Preferably, the method comprises the specific steps of acquiring the transmission data quantity of each wireless communication network user in the wireless communication network user grading matrix in real time to obtain a real-time transmission data quantity matrix, setting a basic energy consumption transmission data quantity threshold value to correct the real-time transmission data quantity matrix to obtain a real-time transmission data quantity correction matrix, and predicting the bandwidth required by the wireless communication network user in real time through a final SVM model as follows:
s51, acquiring wireless communication network user grading matrix in real time The transmission data quantity of each wireless communication network user in the network is obtained to obtain a real-time transmission data quantity matrixThe following are provided:
Wherein, Represent the firstUser service level of wireless communication networkReal-time transmission data volume of individual wireless communication network users;
s52, setting a basic energy consumption transmission data quantity threshold value Each real-time transmission data quantity in the real-time transmission data quantity matrix is corrected one by one through a basic energy consumption transmission data quantity threshold value to obtain a real-time transmission data quantity correction matrixThe correction process is as follows:
S521, if Then (1)User service level of wireless communication networkReal-time transmission data volume of individual wireless communication network usersRemain unchanged;
If it is Will be the firstUser service level of wireless communication networkReal-time transmission data volume of individual wireless communication network usersCorrecting to 0;
s53, correcting matrix for real-time transmission data quantity The corrected real-time transmission data quantity is input into a final SVM model to predict the bandwidth required by each wireless communication network user in real time, and a bandwidth matrix required by the user in real time is obtainedThe following are provided:
Wherein, Represent the firstUser service level of wireless communication networkThe bandwidth required in real time by the individual wireless communication network users.
The transmission data quantity of the wireless communication network user acquired in real time is corrected by setting the basic energy consumption transmission data quantity threshold value, and the bandwidth required by the wireless communication network user in real time is predicted by utilizing the final SVM model, so that the network demand of the user is ensured, and the additional consumption of bandwidth resources is avoided.
Preferably, the specific steps of allocating bandwidth to each wireless communication user in turn from high to low according to the service level of the wireless communication network user are as follows:
S61, distributing the optimal threshold bandwidth corresponding to the optimal threshold bandwidth set for each wireless communication network user with the corrected real-time transmission data volume not being 0;
s62, distributing bandwidth matrix needed by user in real time to all wireless communication network users from high to low according to the high-low sequence of the service level of the wireless communication network users The corresponding user needs bandwidth in real time;
S621, if the total amount of the residual bandwidth can distribute the bandwidth matrix required by the user in real time to all the wireless communication network users If the corresponding user needs bandwidth in real time, finishing bandwidth allocation operation after completing real-time bandwidth allocation of all wireless communication network users in the lowest wireless communication network user service level;
S622, if the total amount of residual bandwidth is being allocated to the first When the wireless communication network user service level is adopted, the bandwidth matrix required by the user in real time cannot be distributed to all wireless communication network users in the wireless communication network user service levelThe corresponding user in the network needs bandwidth in real time, and the rest bandwidth is equally distributed to the first networkAnd ending the bandwidth allocation operation after all wireless communication network users in the service level of each wireless communication network user.
And distributing bandwidth to all wireless communication network users according to the predicted bandwidth matrix required by the first user in real time and the service level of the wireless communication network users, so as to realize the effective distribution of the wireless communication network bandwidth resources.
The invention also discloses a bandwidth allocation system in the wireless communication network, which comprises a data acquisition module, a final SVM model construction module, a wireless communication network user service grade division module, an optimal threshold bandwidth setting module, a wireless communication network user real-time required bandwidth prediction module and a wireless communication user bandwidth allocation module;
The data acquisition module acquires the transmission data quantity of each wireless communication network user by setting a transmission data quantity acquisition period to obtain a transmission data quantity matrix;
The final SVM model construction module trains and tests the constructed initial SVM model through a transmission data quantity training matrix and a transmission data quantity measuring matrix which are obtained through the transmission data quantity matrix to obtain a final SVM model;
The wireless communication network user service grade dividing module is used for arranging the service grades of the wireless communication network users from high to low, constructing a wireless communication network user service grade set, dividing the wireless communication network users according to the corresponding wireless communication network user service grades, and obtaining a wireless communication network user grading matrix;
the optimal threshold bandwidth setting module sets the optimal threshold bandwidth of each wireless communication network user service level through a manual bee colony algorithm to obtain an optimal threshold bandwidth set;
the wireless communication network user real-time required bandwidth prediction module corrects the real-time acquired wireless communication network user transmission data quantity by setting a basic energy consumption transmission data quantity threshold value to obtain a real-time transmission data quantity correction matrix, and predicts the wireless communication network user real-time required bandwidth by a final SVM model to obtain a user real-time required bandwidth matrix;
The wireless communication user bandwidth allocation module allocates the optimal threshold bandwidth corresponding to the service level of the wireless communication network user to each wireless communication network user with the real-time transmission data volume not being 0 after correction, and allocates the real-time required bandwidth to all the wireless communication network users in sequence from high to low according to the high-low sequence of the service level of the wireless communication network user.
(III) beneficial effects
The invention provides a bandwidth allocation method and a bandwidth allocation system in a wireless communication network, which have the following beneficial effects:
1. The invention sets a data acquisition module, a final SVM model construction module, a wireless communication network user service grade division module, an optimal threshold bandwidth setting module, a wireless communication network user real-time required bandwidth prediction module and a wireless communication user bandwidth allocation module, trains and tests the initial SVM model by acquiring a large amount of data to obtain a final SVM model, ensures the accuracy of the final SVM model, provides a prediction tool for subsequent operation, divides the wireless communication network user according to the corresponding wireless communication network user service grade, allocates the optimal threshold bandwidth for each service grade, meets the basic bandwidth requirement, and determines the sequence of bandwidth allocation at the same time;
2. Correcting the transmission data quantity of the wireless communication network user acquired in real time by setting a basic energy consumption transmission data quantity threshold value, and predicting the bandwidth required by the wireless communication network user in real time by utilizing a final SVM model, thereby ensuring the network demand of the user and simultaneously avoiding the extra consumption of bandwidth resources;
3. Setting the optimal threshold bandwidth of each wireless communication network user service level by using an artificial bee colony algorithm, and establishing a mathematical model by simulating the foraging behavior of the bee colony in the nature, so as to ensure the speed and accuracy of the optimizing process and improve the efficiency of the convergence process.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the invention, the drawings that are needed for the description of the embodiments will be briefly introduced below, it being obvious that the drawings in the following description are only some embodiments of the invention, and that it is also possible for a person skilled in the art to obtain the drawings from these drawings without inventive effort.
Fig. 1 is a flowchart of a bandwidth allocation method in a wireless communication network according to the present invention;
Fig. 2 is a schematic block diagram of a bandwidth allocation system in a wireless communication network according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the description of the present invention, it should be understood that the terms "open," "upper," "lower," "top," "middle," "inner," and the like indicate an orientation or positional relationship, merely for convenience of description and to simplify the description, and do not indicate or imply that the components or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus should not be construed as limiting the invention.
An embodiment of the bandwidth allocation method and system in a wireless communication network is as follows:
Referring to fig. 1, a bandwidth allocation method in a wireless communication network, the method includes the steps of:
S1, setting a wireless communication network user set and a transmission data volume acquisition period set, and acquiring transmission data volumes of all wireless communication network users in the transmission data volume acquisition period set in the wireless communication network user set to obtain a transmission data volume matrix;
S11, setting a wireless communication network user set Wherein, the method comprises the steps of, wherein,Represent the firstA user of the wireless communication network,Representing the total number of wireless communication network users;
s12, setting a transmission data quantity acquisition period set Wherein, the method comprises the steps of, wherein,Represent the firstA data volume acquisition period of the transmission,Representing the total number of transmission data quantity acquisition cycles;
S13, collecting wireless communication network user set In which each wireless communication network user is transmitting data quantity collection period setThe transmission data quantity of each transmission data quantity acquisition period in the network system is used for obtaining a transmission data quantity matrixThe following are provided:
Wherein, Represent the firstThe user of the wireless communication network is in the first placeThe amount of transmission data in each transmission data amount acquisition period.
S2, constructing an initial SVM model, a transmission data quantity training matrix and a transmission data quantity testing matrix, and training and testing the initial SVM model through the transmission data quantity training matrix and the transmission data quantity testing matrix to obtain a final SVM model;
s21, constructing an initial SVM model, and setting penalty factor parameters as The radial basis parameters areAnd the kernel function of the initial parameter space in the operation process of the initial SVM model is a Gaussian radial basis function, wherein the Gaussian radial basis function has the following formula:
Wherein, Representing a gaussian radial basis function,Representing the corresponding support vectors for the two training samples,Representation ofAndA Euclidean distance between them;
S22, setting the training data proportion And test data ratioCarrying out data division on the transmission data quantity matrix through the training data proportion and the test data proportion to respectively obtain a transmission data quantity training matrix and a transmission data quantity test matrix;
s23, setting a training error threshold as Inputting the transmission data quantity training matrix into an initial SVM model to train the initial SVM model until the training error of the initial SVM model is smaller than or equal toWhen the training is stopped, a trained SVM model is obtained;
s24, setting a test accuracy threshold Inputting the transmission data measurement matrix into a trained SVM model for testing to obtain the bandwidth required by a wireless communication network user in real time, and calculating the accuracy of a test resultWhen testing accuracyGreater than or equal to the test accuracy thresholdIf not, searching the optimal penalty factor parameter and the optimal radial basis kernel parameter by using a grid search algorithm, and retesting the trained SVM model according to the optimal penalty factor parameter and the optimal radial basis kernel parameter until the test accuracy is reachedGreater than or equal to the test accuracy threshold;
S241, setting search ranges of penalty factor parameters and radial basis kernel parameters, and constructing a two-dimensional search grid;
S242, a group of penalty factor parameters and radial basis kernel parameters with highest testing accuracy are selected through large-step rough searching on the two-dimensional searching grid, and a two-dimensional optimal parameter searching grid is obtained;
S243, calculating the test accuracy of each group of penalty factor parameters and radial basis kernel parameters in the two-dimensional optimal parameter search grid according to a cross verification method, and selecting a group of penalty factor parameters and radial basis kernel parameters with highest test accuracy as the optimal penalty factor parameters and the optimal radial basis kernel parameters.
S3, setting a wireless communication network user service grade set, and dividing each wireless communication network user in the wireless communication network user set according to the corresponding wireless communication network user service grade to obtain a wireless communication network user grading matrix;
S31, arranging the service grades of the wireless communication network users from high to low, and constructing a service grade set of the wireless communication network users Wherein, the method comprises the steps of, wherein,Represent the firstThe service level of a user of the wireless communication network,Representing the total number of service levels of the wireless communication network users;
S32, collecting the service grades of all the wireless communication network users, and grading according to the service grades of the wireless communication network users in the service grade set of the wireless communication network users to obtain a wireless communication network user grading matrix The following are provided:
Wherein, Represent the firstUser service level of wireless communication networkA user of the wireless communication network,Represent the firstThe total number of wireless communication network users in the individual wireless communication network user traffic class.
S4, setting an optimal threshold bandwidth for each wireless communication network user service level in the wireless communication network user service level set through an intelligent optimization algorithm to obtain an optimal threshold bandwidth set;
S41, constructing an artificial bee colony, and setting the maximum honey source searching times Maximum number of iterationsCurrent iteration numberPopulation number;
S42, randomly generating in the search space of the artificial bee colonyThe formula for randomly generating the honey sources is as follows:
Wherein, Represent the firstThe honey source is at the firstThe location of the individual dimensions is such that,Representation ofA random number between the two random numbers,AndRespectively represent the firstUpper and lower limits of the vitamin honey source search space;
s43, calculating fitness function values of all randomly generated honey sources, wherein the fitness function formula is as follows:
Wherein, The function value of the fitness is represented,Representing the proportion of bandwidth that satisfies the use of the wireless communication network subscriber's underlying network,Representing the correction value;
s44, starting iteration, and selecting from the artificial bee population Each hiring bee is distributed with one hiring bee, each hiring bee searches for a new honey source nearby the current honey source, the fitness function value of the new honey source is calculated after the new honey source is found, if the fitness function value of the new honey source is higher than the fitness function value of the original honey source, the new honey source is used for replacing the original honey source, and the honey source position is updated, otherwise, the original honey source is reserved, and the current honey source is increased by one honey source search times, and the formula of the hiring bee search honey source is as follows:
Wherein, Indicating the location of the honey source after the update,Representation ofA random number between the two random numbers,Representation ofIs not equal toIs a random integer of (a) and (b),Represent the firstThe honey source is at the firstThe position of the individual dimensions;
S45, taking the rest artificial bees in the artificial bee population as following bees, selecting the honey source position of an employment bee through a roulette strategy, searching a new honey source nearby the current honey source according to a formula of searching the honey source by the following bees after the following bees reach the selected honey source position, calculating the fitness function value of the new honey source after finding the new honey source, replacing the original honey source by the new honey source if the fitness function value of the new honey source is higher than the fitness function value of the original honey source, and updating the honey source position, otherwise, retaining the original honey source, and increasing the honey source searching times once by the current honey source, wherein the probability calculation formula of selecting the employment bee is as follows:
Wherein, Represent the firstFitness function values of individual honey sources;
s46, recording the searching times of each honey source, wherein the searching times of the honey source reach the maximum honey source searching times When the honey source is abandoned, and the employment bees at the honey source location re-randomly generate new honey sources in the search space according to the step in S44;
s47, judging the current iteration times Whether or not the maximum number of iterations is reachedIf not, returning to S44, if so, calculating the fitness function value of all the current honey sources, selecting the honey source with the highest fitness function value as the current global optimal solution, and outputting the optimal threshold bandwidth of each wireless communication network user service level to obtain an optimal threshold bandwidth set.
S5, acquiring transmission data quantity of each wireless communication network user in the wireless communication network user grading matrix in real time to obtain a real-time transmission data quantity matrix, setting a basic energy consumption transmission data quantity threshold value to correct the real-time transmission data quantity matrix to obtain a real-time transmission data quantity correction matrix, and predicting the bandwidth required by the wireless communication network user in real time through a final SVM model;
s51, acquiring wireless communication network user grading matrix in real time Real-time transmission data quantity of each wireless communication network user in the network to obtain a real-time transmission data quantity matrixThe following are provided:
Wherein, Represent the firstUser service level of wireless communication networkReal-time transmission data volume of individual wireless communication network users;
s52, setting a basic energy consumption transmission data quantity threshold value Each real-time transmission data quantity in the real-time transmission data quantity matrix is corrected one by one through a basic energy consumption transmission data quantity threshold value to obtain a real-time transmission data quantity correction matrixThe correction process is as follows:
S521, if Then (1)User service level of wireless communication networkReal-time transmission data volume of individual wireless communication network usersRemain unchanged;
If it is Will be the firstUser service level of wireless communication networkReal-time transmission data volume of individual wireless communication network usersCorrecting to 0;
s53, correcting matrix for real-time transmission data quantity The corrected real-time transmission data quantity is input into a final SVM model to predict the bandwidth required by each wireless communication network user in real time, and a bandwidth matrix required by the user in real time is obtainedThe following are provided:
Wherein, Represent the firstUser service level of wireless communication networkThe bandwidth required in real time by the individual wireless communication network users.
S6, allocating bandwidth for each wireless communication user in sequence from high to low according to the service level of the wireless communication network user;
S61, distributing the optimal threshold bandwidth corresponding to the optimal threshold bandwidth set for each wireless communication network user with the corrected real-time transmission data volume not being 0;
s62, distributing bandwidth matrix needed by user in real time to all wireless communication network users from high to low according to the high-low sequence of the service level of the wireless communication network users The corresponding user needs bandwidth in real time;
S621, if the total amount of the residual bandwidth can distribute the bandwidth matrix required by the user in real time to all the wireless communication network users The corresponding user in the network user service class is allocated with the real-time required bandwidth, and then the bandwidth allocation operation is finished after the real-time required bandwidth allocation of all the wireless communication network users in the lowest wireless communication network user service class is completed;
S622, if the total amount of residual bandwidth is being allocated to the first When the wireless communication network user service level is adopted, the bandwidth matrix required by the user in real time cannot be distributed to all wireless communication network users in the wireless communication network user service levelThe corresponding user in the network needs bandwidth in real time, and the rest bandwidth is equally distributed to the first networkAnd ending the bandwidth allocation operation after all wireless communication network users in the service level of each wireless communication network user.
An embodiment two of the bandwidth allocation method and system in the wireless communication network is as follows:
referring to fig. 2, a bandwidth allocation system in a wireless communication network includes a data acquisition module, a final SVM model building module, a wireless communication network user service class division module, an optimal threshold bandwidth setting module, a wireless communication network user real-time required bandwidth prediction module, and a wireless communication user bandwidth allocation module;
The data acquisition module acquires the transmission data quantity of each wireless communication network user by setting a transmission data quantity acquisition period to obtain a transmission data quantity matrix;
The final SVM model construction module trains and tests the constructed initial SVM model through a transmission data quantity training matrix and a transmission data quantity measuring matrix which are obtained through the transmission data quantity matrix to obtain a final SVM model;
The wireless communication network user service grade dividing module is used for arranging the service grades of the wireless communication network users from high to low, constructing a wireless communication network user service grade set, dividing the wireless communication network users according to the corresponding wireless communication network user service grades, and obtaining a wireless communication network user grading matrix;
the optimal threshold bandwidth setting module sets the optimal threshold bandwidth of each wireless communication network user service level through a manual bee colony algorithm to obtain an optimal threshold bandwidth set;
the wireless communication network user real-time required bandwidth prediction module corrects the real-time acquired wireless communication network user transmission data quantity by setting a basic energy consumption transmission data quantity threshold value to obtain a real-time transmission data quantity correction matrix, and predicts the wireless communication network user real-time required bandwidth by a final SVM model to obtain a user real-time required bandwidth matrix;
The wireless communication user bandwidth allocation module allocates the optimal threshold bandwidth corresponding to the service level of the wireless communication network user to each wireless communication network user with the real-time transmission data volume not being 0 after correction, and allocates the real-time required bandwidth to all the wireless communication network users in sequence from high to low according to the high-low sequence of the service level of the wireless communication network user.
In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The above disclosed preferred embodiments of the invention are merely intended to help illustrate the invention. The preferred embodiments are not exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention.

Claims (4)

1. A bandwidth allocation method in a wireless communication network, comprising the steps of:
S1, setting a wireless communication network user set and a transmission data volume acquisition period set, and acquiring transmission data volumes of all wireless communication network users in the transmission data volume acquisition period set in the wireless communication network user set to obtain a transmission data volume matrix;
S2, constructing an initial SVM model, a transmission data quantity training matrix and a transmission data quantity testing matrix, and training and testing the initial SVM model through the transmission data quantity training matrix and the transmission data quantity testing matrix to obtain a final SVM model;
S3, setting a wireless communication network user service grade set, and dividing each wireless communication network user in the wireless communication network user set according to the corresponding wireless communication network user service grade to obtain a wireless communication network user grading matrix;
S4, setting an optimal threshold bandwidth for each wireless communication network user service level in the wireless communication network user service level set through an intelligent optimization algorithm to obtain an optimal threshold bandwidth set;
S5, acquiring transmission data quantity of each wireless communication network user in the wireless communication network user grading matrix in real time to obtain a real-time transmission data quantity matrix, setting a basic energy consumption transmission data quantity threshold value to correct the real-time transmission data quantity matrix to obtain a real-time transmission data quantity correction matrix, and predicting the bandwidth required by the wireless communication network user in real time through a final SVM model;
S6, allocating bandwidth for each wireless communication user in sequence from high to low according to the service level of the wireless communication network user;
The step S1 comprises the following steps:
s11, setting a wireless communication network user set A= { a 1,a2,…,ai,…,ak},ai to represent the ith wireless communication network user, and k to represent the total number of the wireless communication network users;
s12, a transmission data quantity acquisition period set B= { B 1,b2,…,bi,…,bl},bi is set to represent an ith transmission data quantity acquisition period, and l represents the total number of transmission data quantity acquisition periods;
S13, acquiring transmission data quantity of each transmission data quantity acquisition period in a transmission data quantity acquisition period set B= { B 1,b2,…,bi,…,bl } of each wireless communication network user in a wireless communication network user set A= { a 1,a2,…,ai,…,ak } to obtain a transmission data quantity matrix C;
the step S2 comprises the following steps:
S21, constructing an initial SVM model, setting a penalty factor parameter as V, a radial basis kernel parameter as gamma, and setting a kernel function of an initial parameter space in the operation process of the initial SVM model as a Gaussian radial basis kernel function;
S22, setting a training data proportion alpha and a test data proportion 1-alpha, and carrying out data division on a transmission data quantity matrix through the training data proportion and the test data proportion to respectively obtain a transmission data quantity training matrix and a transmission data quantity test matrix;
S23, setting a training error threshold value as eta 1, inputting a transmission data quantity training matrix into an initial SVM model to train the initial SVM model, and stopping training until the training error of the initial SVM model is smaller than or equal to eta 1 to obtain a trained SVM model;
S24, setting a test accuracy threshold value eta 2, inputting a transmission data quantity test matrix into a trained SVM model for testing, obtaining a bandwidth required by a wireless communication network user in real time, calculating the accuracy m of a test result, and taking the trained SVM model as a final SVM model when m is more than or equal to eta 2;
the step of searching the optimal penalty factor parameter and the optimal radial basis function parameter by using the grid in the step S24 comprises the following steps:
S241, setting search ranges of penalty factor parameters and radial basis kernel parameters, and constructing a two-dimensional search grid;
S242, a group of penalty factor parameters and radial basis kernel parameters with highest testing accuracy are selected through large-step rough searching on the two-dimensional searching grid, and a two-dimensional optimal parameter searching grid is obtained;
S243, calculating the test accuracy of each group of penalty factor parameters and radial basis kernel parameters in the two-dimensional optimal parameter search grid according to a cross verification method, and selecting a group of penalty factor parameters and radial basis kernel parameters with highest test accuracy as optimal penalty factor parameters and optimal radial basis kernel parameters;
The step S3 comprises the following steps:
S31, arranging the service levels of the wireless communication network users from high to low, constructing a service level set A '= { a' 1,a'2,…,a'i,…,a'p},a'i of the wireless communication network users to represent the service levels of the ith wireless communication network user, and p represents the total number of the service levels of the wireless communication network users;
S32, collecting service grades of all wireless communication network users, and grading according to the service grades of the wireless communication network users in the service grade set of the wireless communication network users to obtain a wireless communication network user grading matrix D;
the step S4 comprises the following steps:
S41, constructing an artificial bee colony, and setting a maximum honey source searching frequency limit, a maximum iteration frequency t max, a current iteration frequency t and a colony number N;
s42, randomly generating N honey sources in a search space of the artificial bee colony to serve as initial solutions;
s43, calculating the fitness of all randomly generated honey sources, wherein the fitness function formula is as follows:
Wherein fit (x) represents a fitness function value, x represents a bandwidth proportion meeting the use of a wireless communication network user base network, and λ represents a correction value;
S44, starting iteration, selecting N employment bees from the artificial bee population, distributing one employment bee for each honey source, searching a new honey source near the current honey source by each employment bee, calculating the adaptability of the new honey source after finding the new honey source, and replacing the original honey source by the new honey source if the adaptability of the new honey source is higher than that of the original honey source, otherwise, increasing the searching times of the original honey source by one time;
S45, taking the rest artificial bees in the artificial bee population as following bees, selecting the honey source position of an employed bee by the following bees through a roulette strategy, searching a new honey source nearby the current honey source according to a formula of searching the honey source by the employed bees after the following bees reach the selected honey source position, and calculating the adaptability of the new honey source after the new honey source is found, wherein if the adaptability of the new honey source is higher than that of the original honey source, the original honey source is used for replacing the original honey source, otherwise, the original honey source is increased by one honey source search times;
S46, recording the searching times of each honey source, discarding the honey source when the searching times of the honey source reach the maximum honey source searching times limit, and randomly generating new honey sources in the searching space by adopting bees at the honey source position according to the step in S44;
S47, judging whether the current iteration times t reach the maximum iteration times t max, if not, returning to S44, if so, calculating the fitness of all the current honey sources, selecting the honey source with the highest fitness as the current global optimal solution, and outputting the optimal threshold bandwidth of each wireless communication network user service level to obtain an optimal threshold bandwidth set;
the step S5 comprises the following steps:
S51, acquiring real-time transmission data quantity of each wireless communication network user in the wireless communication network user grading matrix D in real time to obtain a real-time transmission data quantity matrix D' as follows:
wherein d' ij represents the real-time transmission data amount of the jth wireless communication network user in the ith wireless communication network user service level, and d i represents the total number of wireless communication network users in the ith wireless communication network user service level;
s52, correcting each real-time transmission data quantity in the real-time transmission data quantity matrix one by one to obtain a real-time transmission data quantity correction matrix D';
s53, inputting each corrected real-time transmission data quantity in the real-time transmission data quantity correction matrix D' into a final SVM model to predict the bandwidth required by each wireless communication network user in real time, and obtaining a bandwidth matrix required by the user in real time
2. The bandwidth allocation method in a wireless communication network according to claim 1, wherein the step of correcting each real-time transmission data amount in the real-time transmission data amount matrix in S52 comprises the steps of:
Setting a basic energy consumption transmission data quantity threshold value n, and correcting the real-time transmission data quantity in the real-time transmission data quantity matrix one by one through the basic energy consumption transmission data quantity threshold value;
If d 'ij > n, the real-time transmission data amount d' ij of the jth wireless communication network user in the ith wireless communication network user service level is kept unchanged;
if d 'ij is less than or equal to n, correcting the real-time transmission data quantity d' ij of the jth wireless communication network user in the ith wireless communication network user service level to be 0.
3. A method of bandwidth allocation in a wireless communication network according to claim 2, wherein said S6 comprises the steps of:
S61, distributing the optimal threshold bandwidth corresponding to the optimal threshold bandwidth set for each wireless communication network user with the corrected real-time transmission data volume not being 0;
s62, distributing bandwidth matrix needed by user in real time to all wireless communication network users from high to low according to the high-low sequence of the service level of the wireless communication network users The corresponding user needs bandwidth in real time;
S621, if the total amount of the residual bandwidth can distribute the bandwidth matrix required by the user in real time to all the wireless communication network users If the corresponding user needs bandwidth in real time, finishing bandwidth allocation operation after completing real-time bandwidth allocation of all wireless communication network users in the lowest wireless communication network user service level;
S622, if the total amount of the remaining bandwidth is allocated to the ith wireless communication network user service level, the real-time user required bandwidth matrix cannot be allocated to all wireless communication network users in the ith wireless communication network user service level And (3) the corresponding user in the ith wireless communication network user service level is required to have bandwidth in real time, and after all the rest bandwidth is averagely distributed to all wireless communication network users in the ith wireless communication network user service level, the bandwidth distribution operation is finished.
4. A system for implementing a bandwidth allocation method in a wireless communication network according to any one of claims 1-3, comprising a data acquisition module, a final SVM model building module, a wireless communication network user traffic class classification module, an optimal threshold bandwidth setting module, a wireless communication network user real-time required bandwidth prediction module, and a wireless communication user bandwidth allocation module.
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