CN108093443B - Multi-service vehicle-ground communication bandwidth distribution system and method - Google Patents
Multi-service vehicle-ground communication bandwidth distribution system and method Download PDFInfo
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- 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]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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- H04L47/70—Admission control; Resource allocation
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/70—Admission control; Resource allocation
- H04L47/80—Actions related to the user profile or the type of traffic
- H04L47/801—Real time traffic
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/70—Admission control; Resource allocation
- H04L47/80—Actions related to the user profile or the type of traffic
- H04L47/805—QOS or priority aware
Abstract
The invention discloses a multi-service vehicle-ground communication bandwidth distribution system, which comprises: the train-ground communication bandwidth resource detection unit is used for monitoring the total bandwidth of the system and the bandwidth of each service in real time; the train-ground communication service bearing unit is used for transmitting the communication of train-ground multi-service; and the train-ground communication bandwidth resource management and allocation unit is used for performing bandwidth allocation according to the total bandwidth and the requirement of train-ground multi-service communication and optimizing the bandwidth allocation by using a particle swarm algorithm. The embodiment of the invention provides a multi-service train-ground communication bandwidth allocation system and method, aiming at the problem of management of high-speed train-ground wireless communication bandwidth resources, a 'safe priority and dynamic allocation' strategy is adopted to dynamically allocate energy, so that the bandwidth can be dynamically allocated according to index requirements such as the priority of transmission data, the real-time requirement and the like, and the reliability of transmission of critical safety information of a train and the overall utilization efficiency of the system bandwidth are effectively improved.
Description
Technical Field
The invention relates to the technical field of high-speed train-ground wireless communication, in particular to a multi-service train-ground communication bandwidth allocation system and method.
Background
The high-speed train becomes one of the main efficient and energy-saving modes for passenger travel, and with the increase of the operating mileage of the high-speed train, the increase of the operating speed and the rapid development of information technology, a special broadband train-ground wireless communication system is needed to provide an efficient wireless broadband communication system for train operation control, operation scheduling, infrastructure service state monitoring and passenger information service, so that the operation safety of the high-speed train and the passenger riding experience are ensured. However, the currently adopted GSM-R, LTE-R train-ground wireless communication technology has limited bandwidth resources, and is difficult to meet the information transmission bandwidth requirements of all services.
In a high-speed train-ground wireless communication system, train-ground communication service types are various and the characteristics of data transmission of each service are different. All the services of train-ground communication participate in bandwidth allocation together, and the utilization efficiency of system bandwidth resources is effectively improved on the premise of ensuring the running safety of trains. However, the train running speed is high, the environment is complex, the total bandwidth of the train-ground communication system changes dynamically, and new challenges are brought to the allocation of the high-speed train-ground communication bandwidth.
The Nash negotiation game theory based on cooperation solves the problem of global optimization, the purpose of cooperation is maximization of system effectiveness, and the cooperation process explains fairness and efficiency of each part. Most of the utility functions of the cooperative Nash game system are composed of the sum of the utility functions of all services, and the utility of part of the services can be sacrificed in the process of maximizing the utility of the system, so that the basic transmission of the services is interrupted. An asymmetric Nash game bandwidth allocation model becomes a hotspot of research in recent years, and well distinguishes the contribution degree of the utility of each service to the system utility to ensure the high efficiency of bandwidth allocation, however, in most documents, the selection of a weight function is generally a preset fixed value, but the weight is dynamically changed in the actual bandwidth allocation process.
The invention aims at the problem that the stability of the performance of each service transmitted by the train and the ground is influenced due to the insufficient bandwidth of the train and the ground wireless communication, researches a reasonable and effective bandwidth allocation system and method based on the combination of the asymmetric cooperative Nash negotiation game theory and the particle swarm algorithm, researches the bandwidth allocation of the train and the ground wireless communication, realizes the stability and the reliability of the train and the ground wireless communication of the high-speed train under the condition that the train and the ground communication bandwidth are limited and dynamically change, and ensures the running safety of the high-speed railway and the riding comfort of passengers.
Disclosure of Invention
The invention aims to provide a multi-service train-ground communication bandwidth allocation system and method, which meet the maximization of the utilization efficiency of system bandwidth on the premise of ensuring the running safety of trains.
In order to achieve the purpose, the invention adopts the following technical scheme:
a multi-service vehicle-to-ground communication bandwidth allocation system, comprising: the train-ground communication bandwidth resource detection unit is used for monitoring the total bandwidth of the system and the bandwidth of each service in real time; the train-ground communication service bearing unit is used for transmitting the communication of train-ground multi-service; and the train-ground communication bandwidth resource management and allocation unit is used for performing bandwidth allocation according to the total bandwidth and the requirement of train-ground multi-service communication and optimizing the bandwidth allocation by using a particle swarm algorithm.
Further, the vehicle-ground communication bandwidth resource detection unit transmits the total system bandwidth to the vehicle-ground communication bandwidth allocation unit of the vehicle-ground communication bandwidth resource management allocation unit in real time.
Further, the train-ground communication service bearing unit comprises a transmission unit of each service, the transmission unit comprises a detection unit and a function unit, and the bandwidth requirements and the data characteristics of each service are transmitted to the train-ground communication bandwidth resource management and allocation unit in real time. Further, the detection unit monitors the bandwidth requirements of each service in real time, including the lowest bandwidth requirement and the maximum bandwidth requirement.
Further, the vehicle-ground communication bandwidth resource management and allocation unit comprises: the service utility module is used for establishing a proper utility function for each service; the service weight module is used for establishing a proper weight function for each service; the system utility module is used for establishing a system utility function according to the business utility module and the business weight module and the unbalanced cooperative Nash game theory; and the system fitness module is used for establishing a fitness function by using a particle swarm optimization algorithm according to the system utility function and optimizing bandwidth allocation.
A multi-service vehicle-ground communication bandwidth allocation method utilizing the bandwidth allocation system comprises the following steps:
s11: a vehicle-ground communication bandwidth resource detection unit monitors the total bandwidth of the system in real time;
s13: the vehicle-ground communication service bearing unit monitors the bandwidth requirement and the data characteristics of each service in real time and transmits the bandwidth requirement and the data characteristics to the vehicle-ground communication bandwidth resource management and distribution unit;
s15: the vehicle-ground communication bandwidth resource management allocation unit establishes a proper utility function and a proper weight function for each service;
s17: the vehicle-ground communication bandwidth resource management and allocation unit establishes a system utility function according to the utility function and the weight function of each service and the unbalanced cooperative Nash game theory;
s19: and the vehicle-ground communication bandwidth resource management and allocation unit establishes a fitness function by using a particle swarm optimization algorithm according to the system utility function and optimizes the bandwidth allocation.
Further, step S19 further includes:
s191: allocating initial bandwidth values to all services in the train-ground communication system;
s193: calculating the fitness value of each service and setting an optimal bandwidth allocation result;
s195: optimizing the bandwidth allocation value of each service and judging the optimal bandwidth allocation result;
s197: and judging whether the updating is finished or not and outputting the optimal bandwidth allocation result.
Further, the step S193 further includes:
s931: calculating the applicability value of each service according to the fitness function of each service and the allocated initial bandwidth value;
s933: and setting the calculated fitness value as the optimal bandwidth allocation result of each corresponding service.
Further, the step S195 includes:
s951: optimizing the bandwidth allocation value of each service by adopting a particle swarm algorithm;
s953: calculating the fitness value of each service according to the updated bandwidth distribution value of each service;
s955: and judging whether the fitness value of each service is better than the corresponding optimal bandwidth allocation result, if so, updating the optimal bandwidth allocation result, and if not, not changing the optimal bandwidth allocation result.
Further, the step S197 further includes:
s971: judging whether the optimization times are preset optimization times, if so, turning to S973, otherwise, turning to S195;
s973: and outputting the optimal bandwidth allocation result.
The invention has the following beneficial effects:
the bandwidth allocation system designed by the invention solves the problem of bandwidth allocation of the high-speed train, and adopts a multi-service negotiation cooperation mode from the final target of highest system safety and bandwidth utilization efficiency; the method comprises the steps that the characteristics of transmission information of each service are considered, and a weight coefficient of contribution degree of each service utility to the system utility is established in a targeted manner; the finally established cooperative asymmetric Nash game bandwidth allocation model can well ensure the reasonability and the high efficiency of bandwidth resource allocation on the premise of meeting the basic service data transmission requirement and ensuring the system stability; meanwhile, the high-efficiency optimization algorithm is adopted, the bandwidth allocation is rapidly completed, the characteristic that the communication bandwidth of the train and the ground of the high-speed train is rapidly changed is met, and the real-time requirement of the bandwidth allocation is met.
The self-adaptive weight coefficient function designed by the invention ensures the dynamic change of the weight system and the dynamic fairness and rationality of bandwidth allocation. Meanwhile, the bandwidth allocation optimization is carried out by adopting a particle swarm optimization algorithm, so that the optimal bandwidth can be quickly allocated to each service in the global range, and the optimization of the system performance is realized.
Drawings
The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.
FIG. 1 shows a schematic block diagram of a multi-service vehicle-to-ground communication bandwidth allocation system of the present invention;
fig. 2 is a schematic structural diagram of a communication bandwidth allocation system according to an embodiment of the present invention;
FIG. 3 illustrates a flow diagram of a multi-service vehicle-to-ground communication bandwidth allocation method according to an embodiment of the invention;
FIG. 4 illustrates a flow diagram of a method of optimizing bandwidth allocation according to one embodiment of the invention;
FIG. 5 illustrates a flow chart of calculating an initialization applicability value according to an embodiment of the present invention;
FIG. 6 illustrates a flow diagram for optimizing bandwidth allocation using a particle swarm algorithm, according to an embodiment of the invention;
fig. 7 shows a flowchart for determining whether the particle swarm optimization bandwidth allocation is finished according to an embodiment of the present invention.
Detailed Description
In order to more clearly illustrate the invention, the invention is further described below in connection with preferred embodiments and the accompanying drawings. Similar parts in the figures are denoted by the same reference numerals. It is to be understood by persons skilled in the art that the following detailed description is illustrative and not restrictive, and is not to be taken as limiting the scope of the invention.
One embodiment of the present invention provides a multi-service vehicle-ground communication bandwidth allocation system, as shown in fig. 1, including: the train-ground communication bandwidth resource detection unit is used for monitoring the total bandwidth of the system and the bandwidth of each service in real time; the train-ground communication service bearing unit is used for transmitting the communication of train-ground multi-service; and the train-ground communication bandwidth resource management and allocation unit is used for performing bandwidth allocation according to the total bandwidth and the requirement of train-ground multi-service communication and optimizing the bandwidth allocation by using a particle swarm algorithm.
In the running process of the high-speed train, the bandwidth of the train-ground communication system and the demand of the multi-service bandwidth are dynamically fluctuated, so that the train-ground communication bandwidth resource detection unit of the multi-service train-ground communication bandwidth allocation system needs to monitor the total bandwidth of the system in real time, and further, as shown in fig. 2, the total bandwidth of the system is transmitted to the train-ground communication bandwidth allocation unit of the train-ground communication bandwidth resource management allocation unit in real time to serve as the basis for real-time bandwidth allocation.
The train-ground communication service bearing unit is a transmission main body of the train-ground communication service and ensures that stable and efficient communication bandwidth is provided for each service in the running process of a train, and further comprises a transmission unit, wherein the transmission unit comprises a detection unit and a function unit, the detection unit and the function unit comprise a detection unit and a function unit, and bandwidth requirements and data characteristics of each service are transmitted to the train-ground communication bandwidth resource management and distribution unit in real time; the bandwidth requirement represents the requirement on the bandwidth when each service transmits data, and comprises the lowest bandwidth requirement and the maximum bandwidth requirement of each service; wherein the data characteristics are expressed by the real-time requirement and the importance of each service for transmitting data.
The vehicle-ground communication bandwidth resource management and allocation unit receives the real-time bandwidth of the system, allocates the bandwidth according to the bandwidth requirement and the data characteristics of data transmission of each service, and optimizes the bandwidth allocation by using a particle swarm algorithm, so that the optimal bandwidth is quickly allocated to each service according to the consideration of the global scope, and the optimization of the system performance is realized. Further, the vehicle-ground communication bandwidth resource management allocation unit comprises: the service utility module is used for establishing a proper utility function for each service; the service weight module is used for establishing a proper weight function for each service; the system utility module is used for establishing a system utility function according to the business utility module and the business weight module and the unbalanced cooperative Nash game theory; and the system fitness module is used for establishing a fitness function by using a particle swarm optimization algorithm according to the system utility function and optimizing bandwidth allocation.
The business utility module establishes monotonically increasing and bounded business utility functions based on a bandwidth allocation principle according to train-ground communication total bandwidth and business bandwidth requirements, and the business utility functions are designed to be nonlinear to ensure that the lowest bandwidth requirements of all businesses are preferentially met when the total bandwidth is small; and when the total bandwidth is larger, the bandwidth is allocated fairly according to the characteristics of each service.
The service weight module is used for establishing each service weight function by integrating three factors of bandwidth allocation unsatisfied degree fairness among services, transmission data characteristic fairness and weight adaptive dynamic change, wherein the bandwidth allocation unsatisfied degree fairness among the services is established on the basis of the relative unsatisfied degree of the bandwidth currently allocated by the services to the service bandwidth requirement, the transmission data characteristic fairness is established on the basis of the relative real-time requirement and the importance parameter among service transmission data, and the weight adaptive dynamic change is used for balancing the bandwidth allocation unsatisfied degree and the data characteristics of different services.
And the system utility module integrates the difference characteristics of the bandwidth allocation of the train-ground communication system jointly participated by each service and the data transmission of each service according to the service utility function and the weight function of each service, and adopts the unbalanced cooperative Nash game theory to establish the system utility function.
The system fitness module defines a fitness function according to the system utility function to dynamically allocate the bandwidth to each service, and the system utility function is a nonlinear function, the bandwidth allocation is a nonlinear optimization process, and the multi-service participation bandwidth allocation optimization process is very similar to a Particle Swarm Optimization (PSO) process, so that the bandwidth allocation is optimized by adopting a particle swarm algorithm to maximize the bandwidth utilization efficiency.
Another embodiment of the present invention provides a method for allocating multi-service vehicle-ground communication bandwidth by using the bandwidth allocation system, as shown in fig. 3, including:
s11: a vehicle-ground communication bandwidth resource detection unit monitors the total bandwidth of the system in real time;
and monitoring the total system bandwidth phi in real time, and transmitting the total system bandwidth to a vehicle-ground communication bandwidth allocation unit of a vehicle-ground communication bandwidth resource management allocation unit in real time to serve as a basis for bandwidth real-time allocation.
S13: the vehicle-ground communication service bearing unit monitors the bandwidth requirement and the data characteristics of each service in real time and transmits the bandwidth requirement and the data characteristics to the vehicle-ground communication bandwidth resource management and distribution unit;
the bandwidth requirement is expressed as the real-time requirement of data transmission of each service, and comprises the lowest bandwidth requirement and the maximum bandwidth requirement of each service; wherein the data characteristics are expressed as the importance of each service transmitting data.
S15: the vehicle-ground communication bandwidth resource management allocation unit establishes a proper utility function and a proper weight function for each service;
establishing a monotonously increasing and bounded business utility function based on a bandwidth allocation principle according to the total bandwidth of train-ground communication and the bandwidth requirements of each business:
wherein x isiThe bandwidth allocated to each service; mu.siMinimum bandwidth requirements for each service; x is the number ofaiMaximum bandwidth requirements for each service; x is the number ofmiThe bandwidth requirement when the service utility value is 0.5, and ξ is a function gradient adjusting coefficient used for adjusting the influence degree of the bandwidth allocation on the utility function.
Three factors of unsatisfied fairness of bandwidth allocation among all services, fairness of transmission data characteristics and weight self-adaption dynamic change are integrated to establish a weight function of each service:
λ'i＝α*Ωi+(1-α)Γi,i＝1,2,...,n (2)
wherein omegaiRepresenting the degree that the service bandwidth allocation does not meet; gamma-shapediThe data transmission characteristics of each service are represented, wherein 0- α -1 is an adaptive adjustment parameter, the more important weight is represented when the data transmission is more than or equal to 0 and less than or equal to α and less than or equal to 0.5, and the more important weight is represented when the data transmission is more than or equal to 0.5 and less than or equal to α and less than or equal to 1, the higher weight is represented when the bandwidth unsatisfied degree is;
bandwidth allocation unsatisfied with degree omegaiIs determined by the bandwidth requirement and the allocated bandwidth of each service:
traffic transmission data characteristic ΓiIs the real-time requirement T of data transmission by each serviceiAnd importance WiJointly deciding that:
Γi＝β*Ti+(1-β)*Wi,i＝1,2,...,n (4)
wherein, 0 is equal to or less than β and is an adaptive adjustment parameter, the more important weight of the transmission data is represented when 0 is equal to or less than β and is less than 0.5, the more important weight of the transmission data is represented when 0.5 is greater than β and is less than 1, the higher weight is represented when the real-time requirement is higher, and the real-time requirement T of the transmission data of each service is representediAnd importance WiIs determined by the characteristics of the data transmitted by each service and is determined according to the transmission content set by the system, so that the W of each serviceiAnd TiThe relative values of (A) are all constant values, and satisfy:
each service bandwidth is assigned a weight lambdaiAfter the normalization process, we can get:
s17: the vehicle-ground communication bandwidth resource management and allocation unit establishes a system utility function according to the utility function and the weight function of each service and the unbalanced cooperative Nash game theory;
and (3) integrating the difference characteristics of the bandwidth allocation of the train-ground communication system and the data transmission of each service, which are commonly participated in by each service, and establishing a system utility function by adopting an unbalanced cooperative Nash game theory:
where Φ is the total bandwidth.
S19: and the vehicle-ground communication bandwidth resource management and allocation unit establishes a fitness function by using a particle swarm optimization algorithm according to the system utility function and optimizes the bandwidth allocation.
And according to the service utility functions and the weight functions, the difference characteristics of the bandwidth allocation of the train-ground communication system and the data transmission of each service which are commonly participated by each service are synthesized, and the system utility functions are established by adopting the unbalanced cooperative Nash game theory.
Definable Lagrangian polynomial
Wherein
Wherein
And deltaiAre coefficients of lagrange polynomials.
Because the system utility function is a nonlinear function, the bandwidth allocation is a nonlinear optimization process, the multi-service participation bandwidth allocation optimization process is very similar to a Particle Swarm Optimization (PSO) process, and a particle swarm algorithm can be adopted for optimization.
Furthermore, the bandwidth allocation optimization is carried out by adopting a particle swarm optimization, m particles participate in the bandwidth allocation for the n-type services, and each particle corresponds to a group of bandwidth allocation results X after being updated oncej＝(x1j,...,xij,...,xnj) Indicating the bandwidth allocated to each service of particle j. Calculating corresponding service and system utility according to the bandwidth allocation value,
represents the maximum utility value, p, of the particle j so fargbestRepresenting the maximum utility of all particles so far. And updating the particle swarm bandwidth allocation once, updating the system utility once until the set updating times are finished, and finding out the optimal allocation result.
The particle velocity and bandwidth allocation updating method is defined as follows:
xij(t+1)＝xij(t)+vij(t+1) (11)
where ω represents the inertial weight used to adjust the global and local optimization capability of the PSO algorithm, r1,r2Random numbers uniformly distributed in the interval (0, 1); c. C1,c2The influence of the experience of the particles and the experience of the group on the motion trail of the particles is determined for learning the factors.
tmaxIs the maximum iteration number; t represents the current iteration number; omegastart,ωendRepresenting the initial inertial weight and the terminating inertial weight, respectively. And (4) continuously updating the positions of the particle swarm to perform bandwidth allocation optimization, and searching for a bandwidth allocation result which enables the utility function to reach the maximum value after the set optimization times, so that the utilization efficiency of the bandwidth is the highest.
As shown in fig. 4, the method specifically includes:
s191: allocating initial bandwidth values to all services in the train-ground communication system;
for the situation that m particles participate in bandwidth allocation for n types of services, firstly, the optimized speed and position of each particle are initialized, and the initialized bandwidth value is allocated for each service.
S193: calculating the fitness value of each service and setting an optimal bandwidth allocation result;
further, as shown in fig. 5, the method includes:
s931: calculating the applicability value of each service according to the fitness function of each service and the allocated initial bandwidth value;
s933: and setting the calculated fitness value as the optimal bandwidth allocation result of each corresponding service.
That is, according to the fitness function of each service, the fitness value of each particle is calculated through the initial bandwidth allocation value, and the fitness value is set as the optimal bandwidth allocation result of the particle
And finding out the optimal bandwidth allocation result p of all the particles by comparisongbest。
S195: optimizing the bandwidth allocation value of each service and judging the optimal bandwidth allocation result;
further, as shown in fig. 6, the method includes:
s951: optimizing the bandwidth allocation value of each service by adopting a particle swarm algorithm;
i.e. updating the optimized speed and position of the particle, i.e. updating the bandwidth allocation value of the particle.
S953: calculating the fitness value of each service according to the updated bandwidth distribution value of each service;
that is, the fitness value of each particle is calculated according to the updated bandwidth allocation value.
S955: and judging whether the fitness value of each service is better than the corresponding optimal bandwidth allocation result, if so, updating the optimal bandwidth allocation result, and if not, not changing the optimal bandwidth allocation result.
I.e. the sum of the calculated fitness values of each particle
Making comparison if it is better than
Taking the current distribution result as the optimal distribution result, otherwise, keeping the original distribution result as the optimal distribution result; and updates p in the same mannergbest。
S197: and judging whether the updating is finished or not and outputting the optimal bandwidth allocation result.
Further, as shown in fig. 7, the method includes:
s971: judging whether the optimization times are preset optimization times, if so, turning to S973, otherwise, turning to S195;
judging whether the end condition is met, namely whether the updating times reach the set maximum times, if not, continuing to update, and turning to S195; otherwise, ending the updating, and turning to S973, otherwise.
S973: and outputting the optimal bandwidth allocation result.
Namely, the optimal allocation result is output, so that the bandwidth allocation optimization of the multi-service train-ground communication based on the particle swarm optimization is completed.
It should be understood that the above-mentioned embodiments of the present invention are only examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention, and it will be obvious to those skilled in the art that other variations or modifications may be made on the basis of the above description, and all embodiments may not be exhaustive, and all obvious variations or modifications may be included within the scope of the present invention.
Claims (9)
1. A multi-service vehicle-to-ground communication bandwidth allocation system, comprising:
the train-ground communication bandwidth resource detection unit is used for monitoring the total bandwidth of the system and the bandwidth of each service in real time;
the train-ground communication service bearing unit is used for transmitting the communication of train-ground multi-service;
the vehicle-ground communication bandwidth resource management and allocation unit is used for establishing a fitness function by using a particle swarm algorithm according to the total bandwidth and the requirements of vehicle-ground multi-service communication and optimizing bandwidth allocation, and comprises the following steps:
the train-ground communication bandwidth resource allocation and allocation unit is used for receiving and allocating real-time system bandwidth;
the service utility module is used for establishing a proper utility function for each service:
wherein x isiThe bandwidth allocated to each service; mu.siMinimum bandwidth requirements for each service; x is the number ofaiMaximum bandwidth requirements for each service; x is the number ofmiξ is function gradient adjusting coefficient used to adjust the influence degree of bandwidth allocation on utility function;
the service weight module is used for establishing a proper weight function for each service:
λi′＝α*Ωi+(1-α)Γi,i＝1,2,...,n
wherein omegaiRepresenting the degree that the service bandwidth allocation does not meet; gamma-shapediCharacterizing the data transmission characteristics of each service, 0- α -1 is adaptive adjustment parameter, 0- α <When the weight is more important, the weight is more important when the data is transmitted at 0.5, and when the weight is more important when the bandwidth is more important and less important than 0.5 and less than or equal to α, the weight is more important when the bandwidth is less satisfied;
the system utility module establishes a system utility function according to the business utility module and the business weight module and the non-equilibrium cooperative Nash game theory:
xi≥μi,i＝1,2,...,n
xi≥0,i＝1,2,...,n
wherein Φ is the total bandwidth;
the system fitness module is used for establishing a fitness function by using a particle swarm optimization algorithm according to the system utility function;
and the bandwidth allocation optimization module optimizes the bandwidth allocation by using a particle swarm optimization algorithm.
2. The bandwidth allocation system according to claim 1, wherein the train-ground communication bandwidth resource detection unit transmits the total system bandwidth to the train-ground communication bandwidth allocation unit of the train-ground communication bandwidth resource management allocation unit in real time.
3. The bandwidth allocation system according to claim 1, wherein the car-to-ground communication service bearer unit comprises a transmission unit of each service, and the transmission unit comprises a detection unit and a function unit, and transmits the bandwidth requirement and the data characteristic of each service to the car-to-ground communication bandwidth resource management allocation unit in real time.
4. The system according to claim 3, wherein the detection unit monitors the bandwidth requirement of each service in real time, including the minimum bandwidth requirement and the maximum bandwidth requirement.
5. A method for allocating multi-service vehicular-to-ground communication bandwidth using the bandwidth allocation system of any one of claims 1-4, comprising:
s11: a vehicle-ground communication bandwidth resource detection unit monitors the total bandwidth of the system in real time;
s13: the vehicle-ground communication service bearing unit monitors the bandwidth requirement and the data characteristics of each service in real time and transmits the bandwidth requirement and the data characteristics to the vehicle-ground communication bandwidth resource management and distribution unit;
s15: the vehicle-ground communication bandwidth resource management allocation unit establishes a proper utility function and a proper weight function for each service;
s17: the vehicle-ground communication bandwidth resource management and allocation unit establishes a system utility function by using an unbalanced cooperative Nash game theory according to the utility function and the weight function of each service;
s19: and the vehicle-ground communication bandwidth resource management and allocation unit establishes a fitness function by using a particle swarm optimization algorithm according to the system utility function and optimizes the bandwidth allocation.
6. The method according to claim 5, wherein step S19 further comprises:
s191: allocating initial bandwidth values to all services in the train-ground communication system;
s193: calculating the fitness value of each service and setting an optimal bandwidth allocation result;
s195: optimizing the bandwidth allocation value of each service and judging the optimal bandwidth allocation result;
s197: and judging whether the updating is finished or not and outputting the optimal bandwidth allocation result.
7. The method according to claim 6, wherein the step S193 further comprises:
s931: calculating the applicability value of each service according to the fitness function of each service and the allocated initial bandwidth value;
s933: and setting the calculated fitness value as the optimal bandwidth allocation result of each corresponding service.
8. The method according to claim 6, wherein the step S195 further comprises:
s951: optimizing the bandwidth allocation value of each service by adopting a particle swarm algorithm;
s953: calculating the fitness value of each service according to the updated bandwidth distribution value of each service;
s955: and judging whether the fitness value of each service is better than the corresponding optimal bandwidth allocation result, if so, updating the optimal bandwidth allocation result, and if not, not changing the optimal bandwidth allocation result.
9. The method according to claim 6, wherein the step S197 further comprises:
s971: judging whether the optimization times are preset optimization times, if so, turning to S973, otherwise, turning to S195;
s973: and outputting the optimal bandwidth allocation result.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8787873B1 (en) * | 2011-11-04 | 2014-07-22 | Plusn Llc | System and method for communicating using bandwidth on demand |
| CN105072685A (en) * | 2015-07-13 | 2015-11-18 | 南京理工大学 | Cooperation-based heterogeneous wireless network disperse resource allocation method |
| CN105282746A (en) * | 2015-09-11 | 2016-01-27 | 华东交通大学 | Cognitive radio network frequency spectrum distribution method based on embedded particle swarm gaming |
| CN106604283A (en) * | 2017-01-17 | 2017-04-26 | 重庆大学 | Token-based cognitive wireless network business bandwidth distribution method |
-
2017
- 2017-11-29 CN CN201711220635.2A patent/CN108093443B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8787873B1 (en) * | 2011-11-04 | 2014-07-22 | Plusn Llc | System and method for communicating using bandwidth on demand |
| CN105072685A (en) * | 2015-07-13 | 2015-11-18 | 南京理工大学 | Cooperation-based heterogeneous wireless network disperse resource allocation method |
| CN105282746A (en) * | 2015-09-11 | 2016-01-27 | 华东交通大学 | Cognitive radio network frequency spectrum distribution method based on embedded particle swarm gaming |
| CN106604283A (en) * | 2017-01-17 | 2017-04-26 | 重庆大学 | Token-based cognitive wireless network business bandwidth distribution method |
Non-Patent Citations (1)
| Title |
|---|
| A bandwidth allocation strategy for train-to-ground communication networks;Tian Yin等;《IEEE》;20141231;第1432-1436页 * |
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