CN112243254B - Adaptive access control method for satellite-ground integrated communication - Google Patents
Adaptive access control method for satellite-ground integrated communication Download PDFInfo
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- CN112243254B CN112243254B CN202011068364.5A CN202011068364A CN112243254B CN 112243254 B CN112243254 B CN 112243254B CN 202011068364 A CN202011068364 A CN 202011068364A CN 112243254 B CN112243254 B CN 112243254B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/02—Arrangements for optimising operational condition
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W28/00—Network traffic management; Network resource management
- H04W28/16—Central resource management; Negotiation of resources or communication parameters, e.g. negotiating bandwidth or QoS [Quality of Service]
- H04W28/18—Negotiating wireless communication parameters
- H04W28/20—Negotiating bandwidth
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W48/00—Access restriction; Network selection; Access point selection
- H04W48/08—Access restriction or access information delivery, e.g. discovery data delivery
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/02—Hierarchically pre-organised networks, e.g. paging networks, cellular networks, WLAN [Wireless Local Area Network] or WLL [Wireless Local Loop]
- H04W84/04—Large scale networks; Deep hierarchical networks
- H04W84/06—Airborne or Satellite Networks
Abstract
The invention discloses a satellite-ground integrated communication self-adaptive access control method, which is characterized in that a system model is constructed based on comprehensive integrated scheduling of satellite-ground resources, and a corresponding coding modulation mode is determined and selected by utilizing a group intelligent optimization algorithm according to channel characteristic change, error code performance requirements, transmission rate requirements, received signal-to-noise ratio requirements and the like, so that an adaptive flow of self-adaptive access control and QoS (quality of service) guarantee is constructed, and the group intelligent optimization algorithm is further introduced into coding combination selection of a self-adaptive access control system. The invention can improve the global configuration and optimization capability of the system to the bandwidth resources, enables the use of the resources to be adapted to the requirements of users, and is particularly suitable for solving the problem of resource configuration and optimization in a broadband satellite communication network. The method has the advantage of low calculation complexity, and can realize rapid optimization convergence.
Description
Technical Field
The invention relates to the field of satellite communication, in particular to a satellite-ground integrated communication self-adaptive access control method.
Background
The continuous development of broadband satellite communication technology, especially multi-spot beam satellite communication technology, brings about the increase of various multimedia services and the number of users, which requires the establishment of satellite-ground integrated adaptive access control technology adapted to such scenes, and requires the access control technology to have the characteristics of flexibility and high efficiency, wherein the main problem to be solved is the joint optimization of satellite-ground resources. In the satellite-ground integrated access control technology, a corresponding coding modulation mode is determined and selected according to channel characteristic change, error code performance requirements, transmission rate requirements, received signal-to-noise ratio requirements and the like. Because the coded modulation mode and the QoS class have a corresponding relationship, a corresponding bandwidth needs to be applied according to different QoS requirements, and the following conditions should be met:
(1) there is sufficient bandwidth to accommodate the new connection;
(2) new QoS requirements such as connection bandwidth and time delay can be guaranteed;
(3) the QoS of the existing connection is not disrupted and continues to be guaranteed.
If the access request bandwidth of the new link is smaller than the available residual bandwidth of the system, the link can obtain service with the maximum required bandwidth; if the new link access request bandwidth is larger than the available residual bandwidth of the system or the link leaves the system, the system performance function is recalculated, and the QoS level of some links is allowed to be dynamically changed and the bandwidth is reallocated, thereby ensuring higher link access success rate and system bandwidth utilization rate. If the link is disconnected, the bandwidth occupied by the link is released, the available bandwidth of the system is increased, the performance function of the system is recalculated, the QoS level of some links is allowed to be dynamically changed, and the bandwidth is reallocated, so that the system is ensured to have higher bandwidth utilization rate. In order to better optimize and configure resources, the algorithm of the adaptive access control system has rapid and flexible optimization capacity, the invention applies the group intelligent optimization algorithm to carry out multi-objective optimization configuration, thereby realizing flexible service access capacity.
Disclosure of Invention
The invention aims to improve the self-adaptive access control capability of satellite-ground integrated communication and improve the adaptability of resources and the access control capability. The invention constructs the adaptive flow of the self-adaptive access control and the QoS guarantee, further introduces the group intelligent optimization algorithm in the coding combination selection of the self-adaptive access control system, and rapidly converges to the global optimal solution by utilizing the characteristics of the algorithm on convergence speed and stability.
The invention discloses a satellite-ground integrated communication self-adaptive access control method, which comprises the following steps:
s1, when a new link access request arrives in the satellite-ground integrated communication channel, calculating the current available bandwidth value of the satellite-ground integrated communication system;
s2, if the request bandwidth of the new link access is less than or equal to the current available bandwidth of the satellite-ground integrated communication system, the step S3 is carried out, otherwise, the step S4 is carried out;
s3, calculating the optimized value of the group intelligent optimization algorithm of the satellite-ground integrated communication system before and after the new link is accessed, if the optimized value of the system after the access is greater than or equal to the optimized value before the access, allowing the new link to be accessed, allocating corresponding bandwidth for the new access link, and going to step S7, otherwise, refusing the access of the new link, going to step S7;
s4, calculating the optimized value of the group intelligent optimization algorithm of the satellite-ground integrated communication system before and after the new link is accessed, if the optimized value of the system after the access is larger than or equal to the optimized value before the access, turning to the step S5, otherwise, rejecting the access of the new link, and turning to the step S7;
s5, if the priority of the new link requested to be accessed is lower than or equal to the priority of the existing access link, the system bandwidth is allocated to the new link again, the access is allowed, and then the step S7 is executed, otherwise the step S6 is executed;
s6, redistributing the bandwidth of the existing low-priority link to the new access link, keeping the bandwidth of the new access link, and then allowing the new link to access;
and S7, completing the self-adaptive access control decision of satellite-ground integrated communication.
The calculating of the group intelligent algorithm optimization value of the satellite-ground integrated communication system in step S1 specifically includes:
the method comprises the steps of adopting a self-adaptive access control system coding combination parameter to represent QoS requirements of users, specifically comprising QoS requirements on communication system parameters such as channel characteristic change, error code performance requirements, transmission rate requirements, power consumption requirements and received signal to noise ratio, and determining scheduling strategies, adjusting coefficient parameters, resource reallocation strategies and the like of the users based on a group intelligent optimization algorithm. The normalized objective functions based on the swarm intelligence optimization algorithm are independent of the application environment and share a common evaluation standard, all terminal users have an efficiency function, and the expression of the efficiency function of the terminal users is as follows:
wherein D isiI is more than or equal to 1 and less than or equal to n, n is the total number of system demand parameters, and delta is the grade of the service level when the system demand is iiA correction factor representing a QoS priority correction degree for a system demand i of an end user in a current communication network state; the optimization objective of the satellite-ground integrated communication system is to maximize the efficiency function of all users, and the mathematical expression of the optimization objective function of the satellite-ground integrated communication system is as follows:
wherein g is an optimization objective function of the satellite-ground integrated communication system, m is the total number of users, j represents the jth user, j is more than or equal to 1 and less than or equal to m, and U isjA function of the performance of the user j is represented,
representing the correction factor for user j when the system demand is i,
representing the service level grade of the user j when the system requirement is i; and (2) under the condition of a given efficiency function and a given correction factor, calculating to obtain the maximum value of the global optimization of the optimization objective function of the satellite-ground integrated communication system based on the swarm intelligence optimization algorithm by adaptively adjusting parameters such as a scheduling strategy, an adjusting coefficient parameter, a resource reallocation strategy and the like of a user, wherein the obtained maximum value of the global optimization is the optimization value of the swarm intelligence optimization algorithm.
The method for determining the scheduling strategy, the adjustment coefficient parameter, the resource reallocation strategy and the like of the users based on the swarm intelligent optimization algorithm optimizes the coding combination parameters of the adaptive access control system by utilizing the particle swarm optimization algorithm, and comprises the following specific steps of:
s101, establishing a normalized user efficiency function of each terminal user;
s102, acquiring coding combination parameter requirements of a self-adaptive access control system to be optimized, namely a system requirement parameter set, including channel characteristic variation, error code performance requirements, transmission rate requirements, power consumption requirements and received signal to noise ratio requirements;
s103, configuring corresponding correction factors for the normalized user performance function to represent different system requirement preferences, including requirements on error code performance, power consumption and the like;
s104, initializing a group of random particles, representing a self-adaptive access control system coding parameter combination, and initializing parameters such as the initialized positions and speeds of the particles, self-learning factors, social learning factors, inertial weights, iteration times and the like; after initialization is completed, performing iterative optimization calculation according to the initialized parameters;
s105, calculating a corresponding user efficiency function according to the positions of the particles; recording the individual extreme point of each particle in the population as the best solution of history; finding a global extreme point in the population as the best solution at present;
s106, iteratively updating the speed and the position of the particle by using the formula (3):
vid(k+1)＝αvid(k)+c1r1(pbestid(k)-xid(k))+c2r2(gbestgd(k)-xid(k))
xid(k+1)＝xid(k)+vid(k+1) (3)
wherein the velocity of the ith particle at the kth iteration is Vi(k)＝[vi1(k),vi2(k),...,viD(k)],vid(k) E.g. R, wherein vid(k) Represents the speed of the ith particle in the D-dimension of the kth iteration, D is 1,2, …, D; the position of the ith particle at the kth iteration is Xi(k)＝[xi1(k),xi2(k),…,xiD(k)]，xid(k) A value representing a d-dimensional position of the ith particle at a k-th iteration; the inertia weight coefficient is alpha; learning factor of c1And c2；pbestid(k) A d-dimension position value representing the history best solution of the ith particle after the kth iteration; gbestgd(k) Representing the value of the d-dimension position of the current best solution after the k-th iteration; r is1、r2Is the interval [0,1]A random number of (c);
s107, judging whether the iteration times are reached, if so, transferring to the step S108, and if not, transferring to the step S105;
and S108, finishing the group intelligent algorithm, and outputting the service level grade and the correction factor of the user under the condition that the best solution is required by each system at present, namely the scheduling strategy, the adjustment coefficient parameter, the resource reallocation strategy and the like of the user.
The invention has the following advantages:
1. compared with the prior art, the satellite-ground integrated communication resource utilization method is introduced, a simple and clear new link access flow of the satellite-ground integrated communication system is provided, and a group intelligent optimization algorithm is adopted based on the flow, so that the adaptive access problem modeling of the satellite-ground integrated communication becomes a global optimization problem, the adaptive access control capability is improved, the environment and the service characteristics are adapted, and the channel utilization efficiency is improved.
2. The group intelligent optimization algorithm has the characteristics of simple modeling and high optimization speed, can meet the optimization problem requirement of the service access scheduling method of the broadband satellite communication system, and improves the real-time performance of multi-user access of the system.
Drawings
FIG. 1 is a schematic diagram of an adaptive access control process of satellite-ground integrated communication;
fig. 2 is a schematic diagram of a preferred flow of encoding combination parameters based on a group intelligent optimization algorithm.
Detailed Description
A method for controlling adaptive access of satellite-ground integrated communication, a flow chart of which is shown in fig. 1, includes the following steps:
s1, when a new link access request arrives in the satellite-ground integrated communication channel, calculating the current available bandwidth value of the satellite-ground integrated communication system;
s2, if the request bandwidth of the new link access is less than or equal to the available bandwidth of the satellite-ground integrated communication system, the step is shifted to S3, otherwise, the step is shifted to S4;
s3, calculating the optimized value of the group intelligent optimization algorithm of the satellite-ground integrated communication system before and after the new link is accessed, if the optimized value of the system after the access is greater than or equal to the optimized value before the access, allowing the new link to be accessed, allocating corresponding bandwidth for the new access link, and going to step S7, otherwise, refusing the access of the new link, going to step S7;
s4, calculating the optimized value of the group intelligent optimization algorithm of the satellite-ground integrated communication system before and after the new link is accessed, if the optimized value of the system after the access is larger than or equal to the optimized value before the access, turning to the step S5, otherwise, rejecting the access of the new link, and turning to the step S7;
s5, if the priority of the new link requested to be accessed is lower than or equal to the priority of the existing access link, the system bandwidth is allocated to the new link again, the access is allowed, and then the step S7 is executed, otherwise the step S6 is executed;
s6, redistributing the bandwidth of the existing low-priority link to the new access link, keeping the bandwidth of the new access link, and then allowing the new link to access;
and S7, completing the self-adaptive access control decision of satellite-ground integrated communication.
The calculating of the optimized value of the current group intelligence algorithm of the satellite-ground integrated communication system in step S1 specifically includes:
the method comprises the steps of adopting a self-adaptive access control system coding combination parameter to represent QoS requirements of users, specifically comprising QoS requirements on communication system parameters such as channel characteristic change, error code performance requirements, transmission rate requirements, power consumption requirements and received signal to noise ratio, and determining scheduling strategies, adjusting coefficient parameters, resource reallocation strategies and the like of the users based on a group intelligent optimization algorithm. The normalized objective function based on the group intelligent optimization algorithm is independent of the application environment and shares a common evaluation standard, and all terminal users have an efficiency function. The expression for the end-user's performance function is:
wherein D isiI is more than or equal to 1 and less than or equal to n, n is the total number of system demand parameters, and delta is the grade of the service level when the system demand is iiIs a correction factor representing the QoS priority correction degree for the end user's system demand i under the current network state; the optimization objective of the satellite-ground integrated communication system is to maximize the efficiency function of all users, and the mathematical expression of the optimization objective function of the satellite-ground integrated communication system is as follows:
wherein g is an optimization objective function of the satellite-ground integrated communication system, m is the total number of users, j represents the jth user, j is more than or equal to 1 and less than or equal to m, and U isjA function of the performance of the user j is represented,
representing the correction factor for user j when the system demand is i,
representing the service level grade of the user j when the system requirement is i; and (2) under the condition of a given efficiency function and a given correction factor, calculating to obtain a global optimization maximum value through parameters such as a self-adaptive adjustment user scheduling strategy, an adjustment coefficient parameter, a resource reallocation strategy and the like based on a group intelligent optimization algorithm, wherein the global optimization maximum value is an NP-HARD discrete resource allocation problem, and the obtained global optimization maximum value is an optimized value of the group intelligent optimization algorithm. When the optimization objective function of the satellite-ground integrated communication system obtains the optimized value of the group intelligent optimization algorithm, the parameters corresponding to each user are globally optimal.
The method for determining the scheduling strategy, the adjustment coefficient parameter, the resource reallocation strategy and the like of the users based on the swarm intelligent optimization algorithm is to optimize the coding combination parameters of the adaptive access control system by utilizing the particle swarm optimization algorithm, and a schematic flow chart of the optimization flow of the coding combination parameters based on the swarm intelligent optimization algorithm is shown in fig. 2, which comprises the following specific steps:
s101, establishing a normalized user efficiency function of each terminal user;
s102, acquiring coding combination parameter requirements of a self-adaptive access control system to be optimized, namely a system requirement parameter set, including channel characteristic variation, error code performance requirements, transmission rate requirements, power consumption requirements and received signal to noise ratio requirements;
s103, configuring corresponding correction factors for the normalized user performance function to represent different system requirement preferences, such as requirements on error code performance, power consumption and the like;
s104, initializing a group of random particles to represent a required coding parameter combination of a self-adaptive access control system, and initializing parameters such as the initialized positions and speeds of the particles, self-learning factors, social learning factors, inertial weights, iteration times and the like; after initialization is completed, performing iterative optimization calculation according to the initialized parameters;
s105, calculating a corresponding user efficiency function according to the positions of the particles; recording the individual extreme point of each particle in the population as the best solution of history; the population finds a global extreme point as the best solution at present;
s106, iteratively updating the speed and the position of the particle by using the formula (3):
vid(k+1)＝αvid(k)+c1r1(pbestid(k)-xid(k))+c2r2(gbestgd(k)-xid(k))
xid(k+1)＝xid(k)+vid(k+1) (3)
wherein the initialization velocity of the particles is Vi(k)＝[vi1(k),vi2(k),...,viD(k)],vid(k) E.g. R, wherein vid(k) Representing the velocity of the ith particle in the d-dimension of the kth iteration; xi(k)＝[xi1(k),xi2(k),…,xiD(k)]，xid(k) A value representing a d-dimensional position of the ith particle at a k-th iteration; the inertia weight coefficient is alpha; learning factor of c1And c2；pbestid(k) A d-dimension position value representing the history best solution of the ith particle after the kth iteration; gbestgd(k) Representing the value of the d-dimension position of the current best solution after the k-th iteration; r is1、r2Is the interval [0,1]A random number of (c);
s107, judging whether the iteration times are reached, if so, transferring to the step S108, and if not, transferring to the step S105;
and S108, finishing the group intelligent algorithm, and outputting the service level grade and the correction factor of the user under the condition that the best solution is required by each system at present, namely the scheduling strategy, the adjustment coefficient parameter, the resource reallocation strategy and the like of the user.
The above description is only an example of the present application and is not intended to limit the present application; various modifications and changes may occur to those skilled in the art; any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (3)
1. A self-adaptive access control method for satellite-ground integrated communication is characterized by comprising the following steps:
s1, when a new link access request arrives in the satellite-ground integrated communication channel, calculating the current available bandwidth value of the satellite-ground integrated communication system;
s2, if the request bandwidth of the new link access is less than or equal to the current available bandwidth of the satellite-ground integrated communication system, the step S3 is carried out, otherwise, the step S4 is carried out;
s3, calculating the optimized value of the group intelligent optimization algorithm of the satellite-ground integrated communication system before and after the new link is accessed, if the optimized value of the system after the access is greater than or equal to the optimized value before the access, allowing the new link to be accessed, allocating corresponding bandwidth for the new access link, and going to step S7, otherwise, refusing the access of the new link, going to step S7;
s4, calculating the optimized value of the group intelligent optimization algorithm of the satellite-ground integrated communication system before and after the new link is accessed, if the optimized value of the system after the access is larger than or equal to the optimized value before the access, turning to the step S5, otherwise, rejecting the access of the new link, and turning to the step S7;
s5, if the priority of the new link requested to be accessed is lower than or equal to the priority of the existing access link, the system bandwidth is allocated to the new link again, the access is allowed, and then the step S7 is executed, otherwise the step S6 is executed;
s6, redistributing the bandwidth of the existing low-priority link to the new access link, keeping the bandwidth of the new access link, and then allowing the new link to access;
and S7, completing the self-adaptive access control decision of satellite-ground integrated communication.
2. The adaptive access control method for integrated satellite-ground communication according to claim 1, wherein the calculating of the group intelligent algorithm optimization value of the integrated satellite-ground communication system specifically includes:
adopting a self-adaptive access control system coding combination parameter to represent the QoS requirement of a user, wherein the QoS requirement of the user specifically comprises the QoS requirements on channel characteristic change, error code performance requirement, transmission rate requirement, power consumption requirement and received signal noise ratio communication system parameter, and determining a scheduling strategy, an adjusting coefficient parameter and a resource reallocation strategy of the user based on a group intelligent optimization algorithm; the normalized objective functions based on the swarm intelligence optimization algorithm are independent of the application environment and share a common evaluation standard, all terminal users have an efficiency function, and the expression of the efficiency function of the terminal users is as follows:
wherein D isiI is more than or equal to 1 and less than or equal to n, n is the total number of system demand parameters, and delta is the grade of the service level when the system demand is iiA correction factor representing a QoS priority correction degree for a system demand i of an end user in a current communication network state; the optimization objective of the satellite-ground integrated communication system is to maximize the efficiency function of all users, and the mathematical expression of the optimization objective function of the satellite-ground integrated communication system is as follows:
wherein g is an optimization objective function of the satellite-ground integrated communication system, m is the total number of users, j represents the jth user, j is more than or equal to 1 and less than or equal to m, and U isjA function of the performance of the user j is represented,
representing the correction factor for user j when the system demand is i,
representing the service level grade of the user j when the system requirement is i; and (2) under the condition of a given efficiency function and a given correction factor, calculating to obtain the maximum value of the global optimization of the optimization objective function of the satellite-ground integrated communication system based on the swarm intelligence optimization algorithm by adaptively adjusting the scheduling strategy, the adjustment coefficient parameter and the reallocation resource strategy parameter of the user, wherein the obtained maximum value of the global optimization is the optimization value of the swarm intelligence optimization algorithm.
3. A satellite-ground integrated communication adaptive access control method according to claim 2, wherein the determining of the scheduling policy, the adjusting coefficient parameter, and the resource reallocation policy of the user based on the swarm optimization algorithm is to optimize the coding combination parameter of the adaptive access control system by using a particle swarm optimization algorithm, and the method comprises the following specific steps:
s101, establishing a normalized user efficiency function of each terminal user;
s102, acquiring coding combination parameter requirements of a self-adaptive access control system to be optimized, namely a system requirement parameter set, including channel characteristic variation, error code performance requirements, transmission rate requirements, power consumption requirements and received signal to noise ratio requirements;
s103, configuring corresponding correction factors for the normalized user performance function to represent different system requirement preferences, including requirements on error code performance and power consumption;
s104, initializing a group of random particles, representing a self-adaptive access control system coding parameter combination, and initializing the initialized positions and speeds of the particles, a self-learning factor, a social learning factor, an inertial weight and an iteration number parameter; after initialization is completed, performing iterative optimization calculation according to the initialized parameters;
s105, calculating a corresponding user efficiency function according to the positions of the particles; recording the individual extreme point of each particle in the population as the best solution of history; finding a global extreme point in the population as the best solution at present;
s106, iteratively updating the speed and the position of the particle by using the formula (3):
vid(k+1)＝αvid(k)+c1r1(pbestid(k)-xid(k))+c2r2(gbestgd(k)-xid(k))
xid(k+1)＝xid(k)+vid(k+1) (3)
wherein the velocity of the ith particle at the kth iteration is Vi(k)＝[vi1(k),vi2(k),...,viD(k)],vid(k) E.g. R, wherein vid(k) Represents the speed of the ith particle in the D-dimension of the kth iteration, D is 1,2, …, D; the position of the ith particle at the kth iteration is Xi(k)＝[xi1(k),xi2(k),…,xiD(k)]，xid(k) A value representing a d-dimensional position of the ith particle at a k-th iteration; the inertia weight coefficient is alpha; learning factor of c1And c2；pbestid(k) A d-dimension position value representing the history best solution of the ith particle after the kth iteration; gbestgd(k) Representing the value of the d-dimension position of the current best solution after the k-th iteration; r is1、r2Is the interval [0,1]A random number of (c);
s107, judging whether the iteration times are reached, if so, transferring to the step S108, and if not, transferring to the step S105;
and S108, finishing the group intelligent algorithm, and outputting the service level grade and the correction factor of the user under the condition that the best solution is required by each system at present, namely the scheduling strategy, the adjustment coefficient parameter and the resource reallocation strategy of the user.
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