CN102256260B - Method for configuring independent resources based on resource flow - Google Patents

Abstract

The invention discloses a method for configuring independent resources based on s resource flow in the field of wireless communication resource management control. Regarding the problems of low convergence speed and various resource treating unsuitability in the prior art, a resource configuring method with higher convergence speed of various resources, suitable for treating a wireless communication system, is provided. In the method, a concept based on the resource flow in the wireless communication system is adopted, requests of multiple users to resources are planned to be changes of spatial intensity of a resource field, and the resource configuration realized based on the resource flow does not require interaction. Meanwhile, a closed-form solution of an optimal resource configuration strategy is deduced, so that high-efficiency independent resource configuration is realized to ensure the existence and the optimality of an optimal solution. The problem of more interaction times and the problems that the existence, the optimality and the like of the optimal solution cannot be ensured in the prior art are solved, and the high-efficiency independent resource configuration is realized to ensure the existence and the optimality of the optimal solution.

Description

Autonomous Resource Allocation Method Based on Resource Flow

technical field

The invention belongs to the field of communication technology, and further relates to a resource flow-based autonomous resource configuration method in the field of wireless communication resource management and control. The method can realize efficient dynamic autonomous configuration of multiple multi-dimensional resources in the wireless communication system, and effectively improve resource utilization in the wireless communication system.

Background technique

Resource management and control has become one of the key technologies that determine the performance of current wireless communication systems. It effectively ensures the service quality requirements of multiple users through efficient allocation of resources, and effectively improves resource utilization efficiency. In the current environment where heterogeneous networks are highly converged and developed, how to achieve efficient utilization of various resources, whether it is for operators to further reduce operation and Both transmission rate and business requirements have serious challenges.

Existing wireless networks are undergoing tremendous development. Various forms of networks are emerging one after another. Multiple network coverage scenarios appear in the same geographical area. Effective allocation of resources plays a decisive role in improving user experience and wireless communication system performance. At present, in terms of dynamic resource management and allocation technology, it basically includes the following technologies: dynamic resource management technology based on optimization technology, resource adaptive allocation technology using learning algorithm and non-cooperative resource allocation method based on game theory. In the current heterogeneous network environment and the background of highly diversified resources, the above three technical methods are based on optimization, learning and game theory to realize resource allocation.

Tsinghua University's patent application document "Joint Optimization Method for Power Allocation, Channel Allocation and Relay Node Selection" (public number CN 101483911A, application number 200910077817.8, application date 2009.1.22) discloses a method for realizing power, channel and relay node selection. A joint optimization method for resources such as nodes. The method adopts the iterative method of power allocation and channel allocation to realize the joint optimization of power allocation and channel allocation. The disadvantage of this method is that the convergence speed is slow and it is not suitable for dealing with more different resource allocations. At the same time, resource management and allocation methods based on optimization techniques cannot meet the needs of dynamic and autonomous allocation of resources in the current network environment.

The patent application document of Beijing University of Posts and Telecommunications "Autonomous Joint Wireless Resource Management System and Method Based on Reinforcement Learning" (publication number CN 101132363A, application number 200710120182.6, application date 2007.8.10) discloses an autonomous joint wireless resource based on reinforcement learning Management systems and methods. This method can reconfigure the mobile terminal to initiate a channel request, and the wireless reconfiguration support function module collects the information of the local wireless resource manager, uses the reinforcement learning method to perform "trial and error" interaction according to various network performance parameter indicators, and decides according to the corresponding judgment criteria Whether to admit new sessions immediately. Compared with the traditional optimization-based resource allocation scheme, reinforcement learning is a "trial and error" online learning technology with autonomous learning ability. Learners gain learning experience through continuous interaction with the environment, and then gradually improve their behavior strategies. Reinforcement learning has certain flexibility and adaptability. However, the disadvantage of this method is that reinforcement learning technology generally requires a large number of interactions between the learner and the environment, so it cannot guarantee the real-time requirements in scenarios such as time-varying wireless data services and dynamic wireless channel fading. .

The patent application document of Nanjing University of Posts and Telecommunications "Power Control Method Based on Normalized Game Model in Cognitive Radio Technology" (publication number CN 101359941A, application number 200810195893.4, application date 2008.9.12) discloses a non-cooperative game theory based A power control method is proposed, which is an implementation scheme especially for power control of the transmitter in cognitive radio. The disadvantage of this method is that in the design process based on game theory, the utility function design is one of the key factors affecting the design and final performance of the power control method. Serious impact. In addition, in the specific game power control process, the first-order partial derivative needs to be solved, and the calculation is complicated. It also cannot meet the requirements of self-configuration.

Contents of the invention

The purpose of the present invention is to overcome the deficiencies of the prior art, and propose a method for autonomous resource configuration based on resource flow, which realizes autonomous resource configuration and self-management by describing multi-dimensional resources in various communication scenarios through resource flow.

The specific idea of the present invention to achieve the above object is to firstly calculate the initial strength of the resource space according to the total amount of resources of the base station; then, realize the optimal allocation based on the resource flow. Considering the heterogeneous communication network environment, base stations installed in the heterogeneous communication network are responsible for constructing, managing and maintaining resource flows to achieve efficient allocation and utilization of resources. The resource dissipation of the resource flow in the process of operation and management is not considered, and the user's resource request causes the amplitude of the resource flow to attenuate without affecting its direction.

The concrete steps that the present invention realizes above-mentioned object are as follows:

(1) The base station updates the neighbor list

After the base station is turned on, determine the resource flow supply list and the resource flow request list according to the distribution of the initialized base station;

(2) Determine the total amount of resources

2a) The base station determines the total amount of resource supply and resource expenditure respectively from the resource flow supply and request list;

2b) The base station calculates the total amount of resource requests of the current user from the total number of service users;

2c) The base station calculates the total net resources of the current base station by summing the total amount of resource supply, expenditure, and user resource requests;

(3) Calculate the initial intensity of each point in the resource space according to the total amount of resources and the distance from the base station.

(4) Determine whether the base station is in motion, if there is a base station in motion, go to step (1), otherwise, perform the following steps;

(5) Judging whether there is a new user arrival, if there is a new user arrival, go to step 2c), otherwise, perform the following steps;

(6) Calculate the total strength of the resource space point according to the average resource field strength in the small area felt at the resource space point;

(7) According to the resource upper limit of the base station, the total strength of the resource field at the resource space point and its partial derivative function relative to a certain direction, etc., calculate the optimal weight function;

(8) Calculate the optimal resource field strength according to the optimal weight function and the total amount of resources that the current base station has;

(9) According to the optimal resource field strength, realize the optimal allocation of resource flow;

(10) END.

Compared with the prior art, the present invention has the following advantages:

First, the present invention provides a resource allocation method suitable for dealing with multiple resources in a wireless communication system with a fast convergence speed, aiming at the problem of slow convergence speed and unsuitability for dealing with multiple resource allocations in the prior art.

Second, the present invention aims at the problem of many interactions in the prior art, adopts the concept of resource flow based on the wireless communication system, plans multi-user requests for resources as changes in the spatial intensity of the resource field itself, and implements resource allocation based on resource flow , without interaction.

Thirdly, the present invention starts from the global system, and aims at the problem that the existence and optimality of the optimal solution cannot be guaranteed in the prior art, and derives the closed-form solution of the optimal resource allocation strategy, so as to realize the efficient and autonomous allocation of resources to ensure the optimal solution existence and optimality.

Description of drawings

Fig. 1 is a flowchart of the present invention;

Fig. 2 is the effect drawing that the present invention completes the resource field space construction;

Fig. 3 is an effect diagram of the present invention realizing independent and efficient allocation of resources.

Detailed ways:

The present invention considers the heterogeneous communication network environment, and the base station installed in the heterogeneous communication network is responsible for constructing, managing and maintaining the resource flow to realize efficient configuration and utilization of resources. The resource dissipation of the resource flow in the process of operation and management is not considered, and the user's resource request causes the amplitude of the resource flow to attenuate without affecting its direction.

The present invention will be further described below in conjunction with accompanying drawing 1.

Step 1, the base station updates the neighbor list

After the base station is turned on, the resource flow supply list and the resource flow request list are determined according to the distribution of the initialized base stations.

Step 2, the base station determines the total amount of resources

2a) The base station determines the corresponding total amount of resource supply and resource expenditure from the resource flow supply and request lists.

2b) The base station calculates the total amount of resource requests of the current user from the total number of service users.

2c) The base station calculates the total amount of net resources of the current base station from the total amount of resource replenishment, resource expenditure, and user resource requests.

Step 3, calculate the initial strength of the resource space

The base station calculates the initial intensity of the resource space point according to the following formula

${\mathrm{<span\; class="notranslate">\; E.</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; \&dtri;</span><span\; class="notranslate">\; \{</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; \&kappa;</span>}{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \}</span>$

表示梯度运算符号，M是当前基站的净资源矢量，κ是常数。Among them, E _i is the intensity of the resource space point with a distance of d _i from the base station,

Indicates the sign of the gradient operation, M is the net resource vector of the current base station, and κ is a constant.

Step 4, judging whether the base station is moving. If there is base station movement, go to step (1), otherwise, perform the following steps;

Step 5, judging whether there is a new user arrival. If a new user arrives, go to step 2c), otherwise, perform the following steps;

Step 6, calculate the total intensity of resource space points

Calculate the total strength of the resource field of the resource space point according to the following formula

是资源空间点d_i处的资源场总强度，E′_i是空间点i感受到的来自不同基站的资源场平均强度，

是微小面积。in,

is the total strength of the resource field at the resource space point d _i , E′ _i is the average strength of the resource field from different base stations felt by the space point i,

is a small area.

Step 7, calculate the optimal weight function

The base station calculates the optimal weight function according to the following formula

${\mathrm{<span\; class="notranslate">\; \&omega;</span>}}_{{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}<span\; class="notranslate">\; =</span>\frac{<span\; class="notranslate">\; \&PartialD;</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}}{<span\; class="notranslate">\; \&PartialD;</span>{\mathrm{<span\; class="notranslate">\; E.</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; \&lambda;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}\mathrm{<span\; class="notranslate">\; \&kappa;</span>}{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; S</span>}}_{{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{{\mathrm{<span\; class="notranslate">\; d</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}<span\; class="notranslate">\; )</span>}$

是最优权重函数，

是资源场总强度

相对于E_i的偏导数，λ_i是满足λ_i(M-M_max)＝o的变量，M_max为基站资源量上限，

是资源空间点d_i处的资源场总强度，κ是常数。in,

is the optimal weight function,

is the total strength of the resource field

Relative to the partial derivative of E _i , λ _i is a variable that satisfies λ _i (MM _max )=o, M _max is the upper limit of the resource amount of the base station,

is the total strength of the resource field at point d _i in the resource space, and κ is a constant.

Step 8, calculate the optimal resource field strength

The base station calculates the optimal resource field strength at the resource space point d _i according to the following formula

是资源空间点d_i处的最优资源场强度，

最优权重函数，M是基站具有资源总量。in,

is the optimal resource field strength at point d _i in the resource space,

The optimal weight function, M is the total amount of resources that the base station has.

Step 9, optimal configuration of resource flow

The base station calculates the optimal resource flow allocation strategy according to the following formula

是资源流最优配置策略，

是资源空间点d_i处的最优资源场强度，更新资源场空间。in,

is the optimal resource flow allocation strategy,

is the optimal resource field strength at point d _i in the resource space, and updates the resource field space.

Step 10, end.

The effect of the present invention will be further described in conjunction with accompanying drawings 2 and 3 below.

Fig. 2 is the effect diagram of the space construction of the resource field completed by the present invention, where a simple wireless communication scenario of three base stations is given, and it is assumed that the total resource requirements of multi-users who send resource requests to the three base stations are respectively: 50, 25, 100 units. The first five steps of the method of the present invention are used to realize the construction of the resource field space, that is, to calculate the resource field strength of each point in the resource field space. On the basis of FIG. 2 , FIG. 3 is an effect diagram of realizing autonomous and efficient allocation of resources in the present invention. Assuming that the total amount of multi-user resource requirements to the three base stations changes, the schematic diagram of the autonomous control process of the method of the present invention. For example, when the total amount of multi-user resource requirements to three base stations changes to 10, 8, and 200 units respectively, that is, the resource request sent to base station 3 requests more resources in the initial resource field space, as shown in Figure 2 resource. At this time, the optimal field strength of the resource field space at this time is calculated by using the last five steps of the present invention. Theoretically, the resources of base stations 1 and 2 will flow towards base station 3, so as to satisfy the current excessive requests of multiple users on base station 3. Comparing Figure 2 and Figure 3, it is found that when the resource request for base station 3 is greatly increased, compared with Figure 2, the optimal resource flow direction of each point in the resource field space in Figure 3 is biased towards base station 3, and even the direction of resource flow is reversed. Therefore, the base station 1 and the base station 2 implement the control of the method of the present invention to realize that the resource flow continuously flows to the base station 3 with a large amount of resources, thus realizing autonomous and efficient allocation of resources based on the resource flow.

Claims (1)

1. An autonomous resource allocation method based on resource flow, the steps of which include the following: (1) The base station updates the neighbor list After the base station is powered on, determine the resource flow supply list and resource flow request list according to the distribution of the initialized base station; (2) Determine the total amount of resources 2a) The base station determines the total amount of resource supply and resource expenditure respectively from the resource flow supply and request list; 2b) The base station calculates the total amount of resource requests of the current user from the total number of service users; 2c) The base station calculates the total net resources of the current base station by summing the total amount of resource supply, expenditure and user resource requests; (3) According to the total amount of resources and the location information of the distance from the base station, the initial strength of each point in the resource space is calculated according to the following formula:

Among them, E _i is the intensity of the resource space point with a distance of d _i from the base station,

Indicates the gradient operation symbol, M is the net resource vector of the current base station, and κ is a constant; (4) Determine whether the base station is moving, if there is a base station moving, go to step (1); otherwise, perform the following steps; (5) Judging whether there is a new user arrival, if there is a new user arrival, go to step 2c); otherwise, perform the following steps; (6) According to the average resource field intensity in the small area felt at the resource space point, the total intensity of the resource space point is calculated according to the following formula: in,

is the total strength of the resource field at the resource space point d _i , E′ _i is the average strength of the resource field from different base stations felt by the space point i,

is a small area; (7) According to the resource upper limit of the base station, the total strength of the resource field at the resource space point and its partial derivative function relative to a certain direction, the optimal weight function is calculated according to the following formula:

in,

is the optimal weight function, is the total strength of the resource field

Relative to the partial derivative of E _i , E _i is the strength of the resource space point at a distance of d _i from the base station, λ _i is a variable satisfying λ _i (MM _max )=o, M _max is the upper limit of the resource amount of the base station,

is the total strength of the resource field at point d _i in the resource space, and κ is a constant; (8) According to the optimal weight function and the total resources of the current base station, calculate the optimal resource field strength at the resource space point d _i according to the following formula:

in,

is the optimal resource field strength at point d _i in the resource space,

The optimal weight function, ln is the natural logarithm symbol, M is the total amount of resources of the base station; (9) According to the optimal resource field strength, calculate the optimal resource flow allocation strategy according to the following formula:

in,

is the optimal resource flow allocation strategy,

is the optimal resource field strength at the resource space point d _i ; (10) END. the

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