CN114301516A - Method and system for pre-configuring switching matrix of multi-beam satellite communication flexible transponder - Google Patents
Method and system for pre-configuring switching matrix of multi-beam satellite communication flexible transponder Download PDFInfo
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Abstract
The invention discloses a method and a system for pre-configuring a switching matrix of a multi-beam satellite communication flexible repeater, which comprises the following steps: acquiring equipment information, service flow information, resource state information and terminal position track information in the current time period; evaluating the service communication quality in the time period according to the service flow information in the current time period to obtain a communication quality evaluation result; analyzing equipment information, service flow information, resource state information and terminal position track information in the current time period, predicting service flow and resource demand in the next time period, and generating time-sharing resource demand information; and generating a load configuration parameter set of the next time period according to the evaluation and prediction results of the time-sharing communication quality evaluation module and the time-sharing prediction module. The generation process of the pre-configured parameters does not need manual intervention, evaluation is carried out based on the historical running state, the stability and the reliability of the system are improved, and the resource utilization rate and the communication quality are improved.
Description
Technical Field
The invention belongs to the field of satellite communication, and particularly relates to a method and a system for pre-configuring a switching matrix of a multi-beam satellite communication flexible transponder.
Background
The satellite communication has the advantages of wide service coverage, high system reliable transmission, no influence of the ground environment state on the system and the like, along with the increasingly diversified application of the satellite communication, the satellite communication system gradually develops from single service, single beam and single frequency point to complex tasks, multiple beams, wide frequency bands and multiple channels, the development trend prompts a flexible repeater which is flexibly and fittable for an on-satellite switching matrix to gradually become a mainstream, the flexible repeater can realize information interaction and cross-beam interaction between any bandwidth and any frequency band on the satellite, and the flexibility and the reliability of the ground communication system are improved by the repeater.
Because the service flow of satellite communication has peaks and valleys at different time intervals, and the positions of a plurality of service terminals can move continuously, and the number of terminals under different beams at different times is different, if the switching matrix is configured in real time when the service communication is applied, because satellite communication has space time delay, and the configuration adjustment of the switching matrix can also cause certain time delay, the problems of prolonging the communication connection, reducing the call completing rate and the like are easily caused, and the full utilization of the communication quality and the satellite resources is influenced.
Disclosure of Invention
The invention aims to provide a method and a system for pre-configuring a switching matrix of a multi-beam satellite communication flexible repeater, which can predict the service flow and the terminal position distribution in the next time period according to the historical service flow and the terminal position distribution and generate a pre-configured parameter of the switching matrix in the next time period.
The technical scheme for realizing the purpose of the invention is as follows:
a multi-beam satellite communication flexible transponder switching matrix pre-configuration method comprises the following steps:
acquiring equipment information, service flow information, resource state information and terminal position track information in the current time period;
evaluating the service communication quality in the time period according to the service flow information in the current time period to obtain a communication quality evaluation result;
analyzing equipment information, service flow information, resource state information and terminal position track information in the current time period, predicting service flow and resource demand in the next time period, and generating time-sharing resource demand information;
and generating a load configuration parameter set of the next time period according to the evaluation and prediction results of the time-sharing communication quality evaluation module and the time-sharing prediction module.
A multi-beam satellite communication flexible transponder switching matrix pre-configuration system is disclosed, wherein the multi-beam satellite communication flexible transponder switching matrix pre-configuration method comprises a database module, a time-sharing communication quality evaluation module, a time-sharing prediction module and a pre-configuration parameter generation module; the database module is connected with the time-sharing communication quality evaluation module and the time-sharing prediction module and comprises an equipment information base, a service flow information base, a resource state base and a terminal position track base; the time-sharing prediction module and the time-sharing communication quality evaluation module are connected with the pre-configuration parameter generation module; wherein the content of the first and second substances,
the time-sharing communication quality evaluation module is used for reading the service flow information data from the database module for analysis and evaluating the service communication quality in a certain period according to parameters such as the service communication quantity, the service connection time delay, the call completion rate and the like in the certain period;
the time-sharing prediction module is used for reading current in-network equipment information, service flow information, resource state information and terminal position track information in a certain time period from the database for analysis, predicting service flow and resource requirements in the next time period and generating time-sharing resource requirement information;
and the pre-configuration parameter generation module is used for integrating the evaluation and prediction results of the time-sharing communication quality evaluation module and the time-sharing prediction module and generating a load configuration parameter set of the next time interval.
Furthermore, the database module consists of an equipment information base, a service flow information base, a resource state base and a terminal position track base, and is connected with the time-sharing communication quality evaluation module and the time-sharing prediction module. The system comprises a time-sharing communication quality evaluation module, a time-sharing prediction module, a resource state information storage module and a terminal position information storage module, wherein the time-sharing communication quality evaluation module is used for evaluating time-sharing communication service quality and the time-sharing prediction module is used for predicting resource demand to provide data support and store equipment information, service flow information, resource state information and terminal position information; wherein the content of the first and second substances,
the equipment information base is used for storing all equipment information participating in networking, including the station type, the network entering and exiting state, the network entering and exiting time, the network on-line time and the like of the terminal;
the service flow information base is used for storing service communication data, including calling and called addresses of service communication, communication time, service types, service connection time delay and the like;
the resource state library is used for storing state data of current networking resources, and comprises current in-network total available resources, used resources, residual resources and the like;
the terminal position track library is used for storing the position track information of the terminal;
further, the time-sharing communication quality evaluation module is connected with the database module and the pre-configuration parameter generation module, and is used for reading the service flow data from the database for analysis, evaluating the service communication quality at a certain time interval, and sending the evaluation result to the pre-configuration parameter generation module;
furthermore, the time-sharing prediction module consists of a service flow prediction module, a terminal distribution prediction module and a resource allowance analysis module, is connected with the database module and the pre-configuration parameter generation module, and is used for reading the equipment information, the service flow information, the resource state information and the terminal position track information data from the database for analysis and predicting and generating the service flow information and the resource demand information of the next time period; wherein the content of the first and second substances,
the terminal distribution prediction module is used for analyzing by adopting a Support Vector Regression (SVR) and combining a fuzzy information granulation algorithm according to the equipment information and the terminal position track information, and predicting the terminal running track and the distribution information in the next time period;
the service flow prediction module is used for analyzing by adopting a Support Vector Regression (SVR) and combining a fuzzy information granulation algorithm according to the equipment information and the service flow information provided by the database module body, predicting the service flow of the next time period, and generating resource demand data by combining with the terminal distribution information generated by the terminal distribution prediction module;
the resource allowance analysis module is used for analyzing the allowance condition of the resource in the next time period according to the resource demand data and the real-time state information of the resource generated by the service flow prediction module and sending the resource allowance condition and the demand data to the pre-configuration parameter generation module;
further, the pre-configuration parameter generating module is configured to generate a switching matrix pre-configuration parameter in a next time period according to the confidence weighting parameter generated by the time-sharing communication quality evaluation module and the resource requirement and resource margin parameter generated by the time-sharing prediction module, compare the generated switching matrix pre-configuration parameter with the currently used switching matrix configuration parameter, and determine whether to perform the switching matrix pre-configuration again.
Compared with the prior art, the invention has the following remarkable effects: according to the equipment information, the service communication information, the resource state information and the terminal position track information in the network, the equipment information, the service flow range, the resource occupation trend and the terminal position distribution in the network in the next time period are predicted, the resource demand information in the next time period is evaluated according to the predicted information, the generation process of the preconfigured parameters does not need manual intervention, evaluation is carried out based on the historical running state, the stability and the reliability of the system are improved, and the resource utilization rate and the communication quality are improved.
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Fig. 1 is a schematic diagram of module components of the multi-beam satellite communication flexible repeater switch matrix pre-configuration method according to the present invention.
FIG. 2 is a schematic diagram of the operation of the time-sharing prediction module according to the present invention.
FIG. 3 is a block diagram of an overall model of the time-sharing prediction algorithm of the present invention.
Fig. 4 is a schematic diagram of the working flow of the transponder pre-configuration parameter generation module according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, the method for pre-configuring the switching matrix of the multi-beam satellite communication flexible repeater of the present invention includes a database module 1, a time-sharing communication quality evaluation module 2, a time-sharing prediction module 3, and a pre-configuration parameter generation module 4; wherein the content of the first and second substances,
and the database module 1 is used for storing all equipment information participating in networking, service communication data, networking resource state data and terminal position track data and providing data support for the time-sharing communication quality evaluation module 2 and the time-sharing prediction module 3.
And the time-sharing communication quality evaluation module 2 is used for reading the service flow information data from the database module for analysis, evaluating the service communication quality in a certain period by using a fuzzy analytic hierarchy process according to parameters such as the service communication quantity, the service connection delay, the call completing rate and the like in a certain period, and sending an evaluation result to the pre-configuration parameter generation module 4.
And the time-sharing prediction module 3 is used for reading current in-network equipment information, service flow information, resource state information and terminal position track information in a certain period of time from the database for analysis, predicting service flow and resource requirements in the next period of time, generating time-sharing resource requirement information, and sending the requirement information to the pre-configuration parameter generation module 4.
And the pre-configuration parameter generation module 4 is used for integrating the evaluation and prediction results of the time-sharing communication quality evaluation module and the time-sharing prediction module and generating the load configuration parameters of the next time period.
In short, the method for pre-configuring the switching matrix of the multi-beam satellite communication flexible repeater evaluates the service communication quality by time intervals, generates the resource demand information of each beam in the next time interval by combining the prediction results of the service flow, the resource state information and the terminal position information in the next time interval, and compares the resource demand information with the current resource state information to generate the on-satellite switching matrix pre-configuration parameters. In addition, the generation process of the pre-configuration parameters of the switching matrix pre-configuration method of the repeater in the multi-beam satellite communication flexible repeater switching matrix pre-configuration method does not need manual intervention, and evaluation is carried out based on the historical running state, so that the stability and reliability of the system are improved, and the resource utilization rate and the communication quality are improved.
As shown in fig. 2, the time-sharing prediction module 3 reads equipment information, service traffic information, resource state information and terminal position trajectory information from a database, predicts the service traffic and resource demand of the next time period by using a support vector regression in combination with a fuzzy information granulation algorithm, performs fitting prediction on the range of the next time period by using the support vector machine, and sends the prediction result to the preconfigured parameter generation module as a basis for generating preconfigured parameters of the next time period; wherein the content of the first and second substances,
as shown in fig. 3, the parameter sets to be predicted are the equipment information, the traffic information, the resource status information and the terminal location trajectory information read from the database, the parameter sets are respectively subjected to fuzzy information granulation to obtain range set information of each parameter set, the granulated range sets are respectively divided into a training set and a prediction set to be used as the input of a fitting model support vector machine, parameter range prediction of each set time division is obtained through fitting training, and the range of each parameter in the next time period is predicted; wherein the content of the first and second substances,
the support vector linear regression function is shown in equation (1).
Wherein, betai,αiIs Lagrange multiplier, K (x)gxi) For the kernel function of the support vector machine, n is the number of samples, and the types of commonly used kernel functions are as follows:
linear kernel function: k (x, x)i)＝xTxi
Polynomial kernel function: k (x, x)i)＝(gxTxi+r)p,r＞0
Radial basis kernel function:
two layers of perceptron kernels: k (x, x)i)＝tanh(gxTxi+r)
Wherein g, r and p are core parameters.
The polynomial kernel function has poor computing capability in high-dimensional samples, and the radial basis kernel function has good generalization performance in large sample data and the number of related parameters is relatively small, so that the polynomial kernel function has certain advantages in parameter optimization. Hence the radial basis kernel function is employed herein.
The fuzzy information granulation algorithm adopts triangular fuzzy particles with the simplest form, and the functional formula is shown as formula (2).
Wherein a, m and b are threshold ranges of the granulation variable x.
The fuzzy information granulation process specifically comprises the following steps:
parameter value { x for the same granulation window1,x2,…xmArrange according to ascending order, and the sequence after ordering is marked as { o }1,o2…om}。
Calculating granulation parameter R according to formula (3)
Wherein o ismFor the above ordered sequence o1,o2…omAnd n is a natural number.
Calculating the granulation parameter Low according to the formula (4)
Wherein o iskFor the above ordered sequence o1,o2…omR is the granulation parameter R in the formula (3), and m is the parameter value serial number.
Calculating a granulation parameter Up according to the formula (5)
Wherein o iskFor the above ordered sequence o1,o2…omR is the granulation parameter R in the formula (3), and m is the parameter value serial number.
As shown in fig. 4, the pre-configuration parameter generation module 4 receives parameter inputs of the time-sharing communication quality evaluation module and the time-sharing prediction module, normalizes the communication quality evaluation result, uses the normalized result as a confidence weight of resource allocation, uses a predicted range result of the time-sharing prediction module as a confidence interval of parameter prediction, obtains a weighted average value of values of the confidence interval as a final prediction result, and uses the weighted weight as the confidence weight value. And calculating the flow information and the switching matrix configuration requirement of the next time period according to the final prediction result, and comparing the flow information and the switching matrix configuration requirement with the switching matrix configuration condition at the current time to generate final pre-configuration parameters.
Claims (10)
1. A multi-beam satellite communication flexible transponder switching matrix pre-configuration method is characterized by comprising the following steps:
acquiring equipment information, service flow information, resource state information and terminal position track information in the current time period;
evaluating the service communication quality in the time period according to the service flow information in the current time period to obtain a communication quality evaluation result;
analyzing equipment information, service flow information, resource state information and terminal position track information in the current time period, predicting service flow and resource demand in the next time period, and generating time-sharing resource demand information;
and generating a load configuration parameter set of the next time period according to the evaluation and prediction results of the time-sharing communication quality evaluation module and the time-sharing prediction module.
2. The method of claim 1, wherein the service communication quality over the time period is assessed using a fuzzy analytic hierarchy process.
3. The method according to claim 1, wherein a support vector regression is used in combination with fuzzy information granulation to predict traffic flow and resource demand in the next time period.
4. The method for pre-configuring the switching matrix of the multi-beam satellite communication flexible repeater according to claim 3, wherein the predicting the traffic flow and the resource demand in the next period by using the support vector regression in combination with the fuzzy information granulation algorithm is specifically: and respectively carrying out fuzzy information granulation processing on equipment information, service flow information, resource state information and terminal position track information in the current time period by adopting a fuzzy information granulation algorithm to obtain range set information of each parameter set, respectively dividing the granulated range set into a training set and a prediction set, and carrying out fitting training by a support vector regression machine to obtain the time-sharing parameter range of each set in the next time period.
5. The multi-beam satellite communication flexible transponder switching matrix provisioning method of claim 4, wherein said fuzzy information granulation algorithm employs triangular fuzzy particles as:
wherein a, m and b are threshold ranges of the granulation variable x.
6. The method for pre-configuring the switching matrix of the multi-beam satellite communication flexible repeater according to claim 5, wherein the performing fuzzy information granulation processing on the equipment information, the traffic information, the resource status information and the terminal location track information in the current time slot by using the fuzzy information granulation algorithm respectively comprises:
parameter value { x for the same granulation window1,x2,…xmArrange according to ascending order, and the sequence after ordering is marked as { o }1,o2…om}；
The granulation parameters R were:
wherein o ismFor the above ordered sequence o1,o2…omTaking the value of n as a natural number;
carrying out granulation parameter Low calculation:
wherein o iskFor the ordered sequence o1,o2…omA () is a fuzzy information granulation algorithm function;
calculating a granulation parameter Up:
7. the multi-beam satellite communication flexible transponder switch matrix provisioning method of claim 4, wherein said support vector regression machine function is:
wherein, betai,αiAre respectively Lagrange multipliers, K (x)gxi) And n is the kernel function of the support vector regression machine and is the number of samples.
8. The multi-beam satellite communication flexible repeater switch matrix pre-configuration method according to claim 4, wherein the load configuration parameter set for generating the next time period according to the evaluation and prediction results of the time-sharing communication quality evaluation module and the time-sharing prediction module is specifically:
normalizing the evaluation result to be used as confidence weight of resource allocation;
taking the resource demand and the resource margin parameter generated by the time-sharing prediction module as a confidence interval of prediction;
weighting the confidence interval value to obtain a weighted average value based on the confidence weighting, and generating a switching matrix pre-configuration parameter of the next time period;
and comparing with the current switch matrix pre-configuration parameters to determine whether to re-perform the switch matrix pre-configuration.
9. A multi-beam satellite communication flexible transponder switching matrix pre-configuration system is characterized by comprising a database module, a time-sharing communication quality evaluation module, a time-sharing prediction module and a pre-configuration parameter generation module; wherein:
the database module is used for providing data for the time-sharing communication quality evaluation module and the time-sharing prediction module and storing equipment information, service flow information, resource state information and terminal position track information;
the time-sharing communication quality evaluation module is used for reading and analyzing data from the database module, evaluating the service communication quality in a set time period according to the service flow information in the time period, and sending an evaluation result to the pre-configuration parameter generation module;
the time-sharing prediction module is used for reading current in-network equipment information, service flow information, resource state information and terminal position track information in a set time period from a database for analysis, predicting service flow and resource requirements in the next time period, generating time-sharing resource requirement information and sending the time-sharing resource requirement information to the pre-configuration parameter generation module;
and the pre-configuration parameter generation module is used for integrating the evaluation and prediction results of the time-sharing communication quality evaluation module and the time-sharing prediction module and generating a load configuration parameter set of the next time interval.
10. The multi-beam satellite communication flexible transponder switch matrix pre-configuration system of claim 1, wherein the database module includes an equipment information base, a traffic flow information base, a resource status base, and a terminal location trajectory base, wherein:
the equipment information base is used for storing all equipment information participating in networking, and the equipment information comprises the station type, the network entering and exiting state, the network entering and exiting time and the network on-line time of the terminal;
the service flow information base is used for storing service communication data, including the service communication quantity, calling and called addresses, call completing rate, communication time length, service types and service connection time delay of service communication;
the resource state library is used for storing state data of current networking resources, and comprises current in-network total available resources, used resources and residual resources;
the terminal position track library is used for storing terminal position track information;
the time-sharing prediction module comprises a service flow prediction module, a terminal distribution prediction module and a resource margin analysis module, wherein:
the terminal distribution prediction module is used for analyzing by adopting a support vector regression machine and combining a fuzzy information granulation algorithm according to the equipment information and the terminal position track information, and predicting the terminal position track and the distribution information in the next time period;
the service flow prediction module is used for analyzing by adopting a support vector regression machine and combining a fuzzy information granulation algorithm according to the equipment information and the service flow information, predicting the service flow of the next time period, and generating resource demand data by combining with the terminal distribution information generated by the terminal distribution prediction module;
the resource allowance analysis module is used for analyzing the allowance condition of the resource in the next time period according to the resource demand data and the real-time state information of the resource generated by the service flow prediction module, and sending the resource allowance condition and the demand data to the pre-configuration parameter generation module.
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Effective date of registration: 20230721 Address after: No. 3, Lianhe Village, Qinhuai District, Nanjing, Jiangsu 210007 Applicant after: NANJING PANDA HANDA TECHNOLOGY Co.,Ltd. Address before: No. 3, Lianhe village, Qinhuai District, Nanjing, Jiangsu 210014 Applicant before: CEC Defense Technology Co.,Ltd. |
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Effective date of registration: 20231008 Address after: No. 3, Lianhe Village, Qinhuai District, Nanjing, Jiangsu 210007 Applicant after: CEC Defense Technology Co.,Ltd. Address before: No. 3, Lianhe Village, Qinhuai District, Nanjing, Jiangsu 210007 Applicant before: NANJING PANDA HANDA TECHNOLOGY Co.,Ltd. |