CN101808366B - Cognitive-based heterogeneous network resource management system and management method thereof - Google Patents

Abstract

The invention discloses a cognitive-based heterogeneous network resource and a management method thereof. By introducing a dual cognition ring, the system adjusts the inter-network level and the network-level resource management policies according to the dynamic change of the network. The system comprises an inter-network wireless resource management module and a wireless resource management module, wherein the inter-network wireless resource management module is used for completing the resource management between heterogeneous networks and the maintenance of a history information base and providing resource management decision information for the wireless resource management module; and the wireless resource management module is used for completing the resource management in each wireless access network and providing the environment information of the wireless network for the inter-network wireless resource management module so as to form a network-level cognition ring; the inter-network wireless resource management module and the wireless resource management module mutually interact necessary decision information and network environment information so as to form an inter-network level cognition ring. The system and the method can adaptively adjust the network parameters according to the dynamic change of the network so as to make a full use of the network resources and maximize the network benefit.

Description

Heterogeneous network resource management system and management method thereof based on cognition

Technical field

The invention belongs to wireless communication technology field, relate to cognitive heterogeneous network resource management system and management method thereof, can be used for cognition wireless network.

Background technology

In recent years, the communication technology had obtained fast development, and the wireless communication system that emerges in an endless stream provides the network environment of isomery for the user; Comprise Wireless Personal Network, WLAN, wireless MAN; Public mobile network, satellite network, and Ad Hoc network, wireless sensor network etc.Numerous networks report to the leadship after accomplishing a task covering, the common covering; The maximizing the benefits of oneself is hoped in each operation commercial city; This has also just brought a problem that must solve: " each operator is Resources allocation how; and how to satisfy the desired QoS of user according to the resource of distributing, thereby make the maximizing the benefits of oneself ".In the document " A Noncooperative Game-Theoretic Framework for RadioResource Management in 4G Heterogeneous Wireless Access Networks " a kind of resource allocation methods based on the non-cooperative game opinion has been proposed; Network level in this method; Nash Equilibrium through finding the solution the non-cooperative game opinion is separated, and each operator's benefit of can sening as an envoy to reaches a maximum set of dispense scheme; Connection level in this method through finding the solution the capacity reserved value that Pareto optimality obtains to satisfy customer requirements, is admitted control.Can obtain the maximum of network benefit on the theoretical method in the document; And can satisfy user's QoS index; But because the network in the reality is constantly to change, the method for solving of this static state can not be made corresponding adjustment according to the variation of network, thereby makes the network benefit can not reach maximum; User QoS can not be met, and produces waste of network resources.

Summary of the invention

The objective of the invention is to avoid the shortcoming of above-mentioned prior art; Propose a kind of heterogeneous network resource management system and management method thereof,, obtain the predicted value of the operating position of a period of time resource in the future with dynamic change trend and existing historical conditions according to network based on cognition; Carry out the management of resource; Realization makes the benefit of operator reach maximum, and satisfies user's qos requirement the sufficient utilization of Internet resources.

Technical scheme of the present invention is achieved in that

One. the term explanation:

RRM:Radio Resource Management, RRM,

RAN:Radio Access Network, wireless access network,

Inter-RAN RRM: RRM between net,

N-RRM: RRM in the net,

L-RRM: the link level RRM,

RA:Resource Allocation, resource allocation,

RRP:Resource Request Prediction, the resource requirement prediction,

RR:Resource Reservation, resource reservation,

TAM:Traffic Allocation Management, the traffic assignments management,

AC:Admission Control admits control,

RMC:Resource Measurement collector, resource information measurement collection device,

L-RMC:Link Level RMC connects level resource information measurement collection device,

HID:Historic Information Database, the historical information storehouse.

Two. the heterogeneous network resource management system based on cognition of the present invention comprises with reference to Fig. 1:

RRM module between net constitutes the superstructure of network resource management system, is used to accomplish the management of resource between heterogeneous network and the maintenance in historical information storehouse, and resource management decision information is provided for the RRM module;

The RRM module, the understructure of formation network resource management system is used to accomplish the resource management of each wireless access network internal, and for RRM module between netting the environmental information of each wireless network is provided;

Described superstructure; Through each network environment information that understructure provides, set up and the renewal historical data base, and business is in the future predicted according to the environmental information of historical information storehouse and current network; Obtain resource management decision, and decision information is passed to understructure; Described understructure through with the resource management decision information of obtaining alternately of superstructure, and the management of resource in carry out this wireless network according to the decision information that obtains constitutes the cognitive ring of net intercaste.

Three. the heterogeneous network resource management method based on cognition of the present invention comprises the steps:

(1) resource distribution module obtains the network environment information that the historical information library module provides; According to these information that obtain; Resource distribution module utilizes Forecasting Methodology, and according to the non-cooperative game opinion each network is carried out the management of resource in each overlay area, makes the benefit of each network reach maximum;

(2) according to connecting the information that level resource information measurement collection device module provides; The resource requirement predicting unit is utilized the Forecasting Methodology based on Wiener-Hopf equation; Through processing to the conditions of demand of past switch call resource; Under given performance index, obtain the possible resource requirement situation of a period of time intra calling in the future;

(3) predicted value that provides according to the resource requirement predicting unit carries out the resource reservation unit and carry out the reservation of switch call resource, thereby the cutting off rate that guarantees switch call satisfies index request;

(4) when the user arrives,, admit control according to the implementation status of traffic assignments administrative unit and resource reservation module;

(5) user resources information is offered a connection level resource information measurement collection device module;

(6) resource information measurement collection device module is compiled the information that connects level resource information measurement collection device unit, and the information that obtains is offered the historical information storehouse, is carried out the renewal in information processing and historical information storehouse by the historical information storehouse.

The present invention has following advantage:

1. the present invention is based on cognitive heterogeneous network resource management system,, make network constantly adjust network parameter, to adapt to the variation of network environment according to the dynamic change of environment owing to introduce cognitive ring of net intercaste and the cognitive ring of network level.

2. the present invention is because the cognitive ring of its net intercaste utilizes Forecasting Methodology and non-cooperative game opinion, makes between net resource management dynamically adjust policy in resource management according to the current state of historical information storehouse and network, thereby makes each operator's maximizing the benefits.

3. network level resource management module of the present invention is introduced the cognitive ring of network level; Make the network can be according to the historical professional conditions of demand of user; To future customer service predict; And, Internet resources are fully utilized, and guarantee that switch call satisfies given qos requirement according to the dynamic adjustment reserved resource that predicts the outcome.

Description of drawings

Fig. 1 the present invention is based on cognitive heterogeneous network resource management system structured flowchart;

Fig. 2 the present invention is based on cognitive heterogeneous network resource management management method block diagram;

Fig. 3 is a simulating scenes of the present invention;

Fig. 4 adds the cognitive ring of network level and does not add the new call blocking rate comparison diagram of network level cognitive ring emulation for the present invention;

Fig. 5 adds the cognitive ring of network level and does not add the cognitive ring of network level emulation switch call blocking rate comparison diagram for the present invention;

Fig. 6 adds the cognitive ring of networking intercaste and does not add the cognitive ring of networking intercaste simulating area three new call blocking rate comparison diagrams for the present invention;

Fig. 7 adds the cognitive ring of networking intercaste and does not add each regional call blocking rate mean value comparison diagram of the cognitive ring of networking intercaste emulation for the present invention;

Fig. 8 adds the cognitive ring of networking intercaste and does not add each regional call blocking rate standard deviation comparison diagram of the cognitive ring of networking intercaste emulation for the present invention.

Embodiment

With reference to Fig. 1; The present invention is based on cognitive heterogeneous network resource management system comprises; RRM module and RRM module between net, the RRM module is accomplished the management of resource between heterogeneous network and the maintenance in historical information storehouse between this net, and resource management decision information is provided for the RRM module; And the RRM module is accomplished the resource management of each wireless access network internal, and for RRM module between netting the environmental information of each wireless network is provided.

Resource management module between described net; Comprise HIB submodule and RA submodule; This HIB submodule is collected, is stored and handles the environmental information from each different radio Access Network, periodically upgrades the historical information storehouse, for the RA submodule provides required network environment information; This RA submodule is predicted the business of network through the network environment information that the HIB submodule provides; And utilize the non-cooperative game opinion to set up equation; Separate and obtain policy in resource management through finding the solution Nash Equilibrium, and the policy information that is generated is passed to the RRM module.

Described RRM module; Comprise N-RRM submodule, L-RRM submodule and RMC submodule; This N-RRM submodule is used to accomplish the resource management of the network level of wireless access network internal, and the user service information that resource management decision information that provides according to the resource allocation submodule and link level RRM submodule provide carries out the prediction of Network; And carry out the reservation of switch call resource according to predicting the outcome, and execution result is passed to the L-RRM submodule; The L-RRM submodule is accomplished the resource management of wireless access network internal link level; The switch call resource obligate information that provides according to RRM submodule in the net carries out user's admittance control; For RRM submodule in netting provides necessary user service information, simultaneously these information are passed to the RMC submodule; The network environment information of wireless access network is collected, stores, handled to the RMC submodule with the information of L-RRM submodule transmission, and these network environment informations are passed to the historical information storehouse;

Described N-RRM submodule comprises RRP unit and RR unit, and user service information that this RRP unit provides according to the L-RRM submodule and given index are accomplished the prediction to customer service, and prediction result information is passed to the RR unit; The RR unit carries out the reservation of resource according to the information of transmitting of predicting the outcome, and resource obligate information is passed to the L-RRM submodule;

Described L-RRM submodule comprises TAM unit, AC unit and L-RMC unit, and control is admitted according to the resource obligate information of N-RRM submodule transmission and the output of TAM unit in this AC unit; Collection, storage and the processing of link level network service information accomplished in the L-RMC unit, and these information are passed to the RMC submodule.

Described TAM is responsible for the unit professional allocation manager, and this unit outgoing traffic shunting and business are not shunted two kinds of strategies, and the policy information of being exported is passed to the AC unit, admit control by the AC unit according to the gained strategy.

Described business is distributing strategy not, when the user arrives, judges whether current overlay area has network can independently provide the user required resource, admit if condition is set up, otherwise the user is not admitted.

Described service distributing strategy; When the user arrives, judge at first whether current overlay area has network can independently provide the user required resource, if setting up, condition admits; Otherwise; Judge that whether resource that all available networks of region provide jointly satisfies user's resource requirement, admit if condition is set up, otherwise the user is not admitted.

With reference to Fig. 2, the present invention is based on cognitive heterogeneous network resource management management method, comprise that step is following:

Step 1: obtain network environment information, each network is carried out resource management in each overlay area.

1a) history information that provides of the Internet resources operating position that provides through the RMC submodule of RA submodule and HID through prediction algorithm, dopes each regional number of users N in a period of time in the future ₁, N ₂, N ₃, N ₄, N ₅

1b) each regional user's number of obtaining according to prediction of RA submodule utilizes the effect function to obtain the benefit function U of WMAN Network respectively according to the non-cooperative game opinion _Wman(m _i, c _j) and the benefit function U of Cellular Network _Cell(m _i, c _j), promptly

$U_{\mathrm{wman}}(m_i,c_j)=w[({\mathrm{<figure-callout\; id="1"\; label="N"\; filenames="HSA00000036532900022.png"\; state="\{\{state\}\}">N</figure-callout>}}_1\log \left(\mathrm{\&alpha;}\frac{B_m-{\mathrm{\&Sigma;}}_{i=2}^5{m}_i}{N_1}\right)+({\mathrm{<figure-callout\; id="2"\; label="N"\; filenames="HSA00000036532900022.png,HSA00000036532900051.png"\; state="\{\{state\}\}">N</figure-callout>}}_2\log (\mathrm{\&alpha;}+\frac{{\mathrm{<figure-callout\; id="2"\; label="c"\; filenames="HSA00000036532900022.png,HSA00000036532900051.png"\; state="\{\{state\}\}">c</figure-callout>}}_2+m_2}{N_2})-{\mathrm{<figure-callout\; id="2"\; label="N"\; filenames="HSA00000036532900022.png,HSA00000036532900051.png"\; state="\{\{state\}\}">N</figure-callout>}}_2\log \left(\mathrm{\&alpha;}\frac{c_2}{N_2}\right))$

$+({\mathrm{<figure-callout\; id="3"\; label="N"\; filenames="HSA00000036532900051.png,HSA00000036532900052.png"\; state="\{\{state\}\}">N</figure-callout>}}_3\log \left(\mathrm{\&alpha;}\frac{{\mathrm{<figure-callout\; id="1"\; label="B\; l"\; filenames="HSA00000036532900022.png"\; state="\{\{state\}\}">B</figure-callout>}}_l+B_{c1}-{\mathrm{<figure-callout\; id="2"\; label="c"\; filenames="HSA00000036532900022.png,HSA00000036532900051.png"\; state="\{\{state\}\}">c</figure-callout>}}_2+m_3}{N_3}\right)-{\mathrm{<figure-callout\; id="3"\; label="N"\; filenames="HSA00000036532900051.png,HSA00000036532900052.png"\; state="\{\{state\}\}">N</figure-callout>}}_3\log \left(\mathrm{\&alpha;}\frac{{\mathrm{<figure-callout\; id="1"\; label="B\; l"\; filenames="HSA00000036532900022.png"\; state="\{\{state\}\}">B</figure-callout>}}_l+B_{c1}-c_2}{N_3}\right))$

$+({\mathrm{<figure-callout\; id="4"\; label="N"\; filenames="HSA00000036532900022.png,HSA00000036532900051.png"\; state="\{\{state\}\}">N</figure-callout>}}_4\log \left(\mathrm{\&alpha;}\frac{{\mathrm{<figure-callout\; id="4"\; label="c"\; filenames="HSA00000036532900022.png,HSA00000036532900051.png"\; state="\{\{state\}\}">c</figure-callout>}}_4+m_4}{N_4}\right)-{\mathrm{<figure-callout\; id="4"\; label="N"\; filenames="HSA00000036532900022.png,HSA00000036532900051.png"\; state="\{\{state\}\}">N</figure-callout>}}_4\log \left(\mathrm{\&alpha;}\frac{c_4}{N_4}\right))$

$+({\mathrm{<figure-callout\; id="5"\; label="N"\; filenames="HSA00000036532900022.png,HSA00000036532900041.png"\; state="\{\{state\}\}">N</figure-callout>}}_5\log \left(\mathrm{\&alpha;}\frac{{\mathrm{<figure-callout\; id="2"\; label="B\; l"\; filenames="HSA00000036532900022.png,HSA00000036532900051.png"\; state="\{\{state\}\}">B</figure-callout>}}_l+B_{c2}-{\mathrm{<figure-callout\; id="4"\; label="c"\; filenames="HSA00000036532900022.png,HSA00000036532900051.png"\; state="\{\{state\}\}">c</figure-callout>}}_4+m_5}{N_5}\right)-{\mathrm{<figure-callout\; id="5"\; label="N"\; filenames="HSA00000036532900022.png,HSA00000036532900041.png"\; state="\{\{state\}\}">N</figure-callout>}}_5\log \left(\mathrm{\&alpha;}\frac{{\mathrm{<figure-callout\; id="2"\; label="B\; L"\; filenames="HSA00000036532900022.png,HSA00000036532900051.png"\; state="\{\{state\}\}">B</figure-callout>}}_L+B_{c2}-c_4}{N_5}\right))]$

$U_{\mathrm{cell}}(m_i,c_j)=w[({\mathrm{<figure-callout\; id="2"\; label="N"\; filenames="HSA00000036532900022.png,HSA00000036532900051.png"\; state="\{\{state\}\}">N</figure-callout>}}_2\log \left(\mathrm{\&alpha;}\frac{{\mathrm{<figure-callout\; id="2"\; label="c"\; filenames="HSA00000036532900022.png,HSA00000036532900051.png"\; state="\{\{state\}\}">c</figure-callout>}}_2+m_2}{N_2}\right)-{\mathrm{<figure-callout\; id="2"\; label="N"\; filenames="HSA00000036532900022.png,HSA00000036532900051.png"\; state="\{\{state\}\}">N</figure-callout>}}_2\log \left(\mathrm{\&alpha;}\frac{m_2}{N_2}\right))$

$+({\mathrm{<figure-callout\; id="3"\; label="N"\; filenames="HSA00000036532900051.png,HSA00000036532900052.png"\; state="\{\{state\}\}">N</figure-callout>}}_3\log \left(\mathrm{\&alpha;}\frac{{\mathrm{<figure-callout\; id="1"\; label="B\; l"\; filenames="HSA00000036532900022.png"\; state="\{\{state\}\}">B</figure-callout>}}_l+B_{c1}-{\mathrm{<figure-callout\; id="2"\; label="c"\; filenames="HSA00000036532900022.png,HSA00000036532900051.png"\; state="\{\{state\}\}">c</figure-callout>}}_2+m_3}{N_3}\right)-{\mathrm{<figure-callout\; id="3"\; label="N"\; filenames="HSA00000036532900051.png,HSA00000036532900052.png"\; state="\{\{state\}\}">N</figure-callout>}}_3\log \left(\mathrm{\&alpha;}\frac{{\mathrm{<figure-callout\; id="1"\; label="B\; l"\; filenames="HSA00000036532900022.png"\; state="\{\{state\}\}">B</figure-callout>}}_l+{\mathrm{<figure-callout\; id="1"\; label="B\; c"\; filenames="HSA00000036532900022.png"\; state="\{\{state\}\}">B</figure-callout>}}_c+m_3}{N_3}\right))$

$+({\mathrm{<figure-callout\; id="4"\; label="N"\; filenames="HSA00000036532900022.png,HSA00000036532900051.png"\; state="\{\{state\}\}">N</figure-callout>}}_4\log \left(\mathrm{\&alpha;}\frac{{\mathrm{<figure-callout\; id="4"\; label="c"\; filenames="HSA00000036532900022.png,HSA00000036532900051.png"\; state="\{\{state\}\}">c</figure-callout>}}_4+m_4}{N_4}\right)-{\mathrm{<figure-callout\; id="4"\; label="N"\; filenames="HSA00000036532900022.png,HSA00000036532900051.png"\; state="\{\{state\}\}">N</figure-callout>}}_4\log \left(\mathrm{\&alpha;}\frac{m_4}{N_4}\right))$

$+({\mathrm{<figure-callout\; id="5"\; label="N"\; filenames="HSA00000036532900022.png,HSA00000036532900041.png"\; state="\{\{state\}\}">N</figure-callout>}}_5\log \left(\mathrm{\&alpha;}\frac{{\mathrm{<figure-callout\; id="2"\; label="B\; l"\; filenames="HSA00000036532900022.png,HSA00000036532900051.png"\; state="\{\{state\}\}">B</figure-callout>}}_l+B_{c2}-{\mathrm{<figure-callout\; id="4"\; label="c"\; filenames="HSA00000036532900022.png,HSA00000036532900051.png"\; state="\{\{state\}\}">c</figure-callout>}}_4+m_5}{N_5}\right)-{\mathrm{<figure-callout\; id="5"\; label="N"\; filenames="HSA00000036532900022.png,HSA00000036532900041.png"\; state="\{\{state\}\}">N</figure-callout>}}_5\log \left(\mathrm{\&alpha;}\frac{{\mathrm{<figure-callout\; id="1"\; label="B\; l"\; filenames="HSA00000036532900022.png"\; state="\{\{state\}\}">B</figure-callout>}}_l+{\mathrm{<figure-callout\; id="2"\; label="B\; c"\; filenames="HSA00000036532900022.png,HSA00000036532900051.png"\; state="\{\{state\}\}">B</figure-callout>}}_c+m_5}{N_5}\right))$

Wherein: U _{I, x} ^(con)Expression network i provides the bandwidth benefit that b is obtained for connecting x, and w, α are that a constant is used for the control effect function; B _mThe total resource of expression WMAN, B _C1And B _C2Represent the resource that Cell1 and Cell2 are total respectively, m _iExpression WMAN is the resource that cell i is distributed, and c _iExpression cellular is the resource that cell i is distributed, and c ₂+ c ₃=B _C1, c ₄+ c ₅=B _C2

For the benefit that makes network reaches maximum, with benefit function U _Wman(m _i, c _j) respectively to independent variable m ₂, m ₃, m ₄And m ₅Ask local derviation, with benefit function U _Cell(m _i, c _j) respectively to independent variable c ₂And c ₄Ask local derviation, make the gained partial derivative equal zero, can get six partial differential equation as follows:

$\frac{\&PartialD;U_{\mathrm{wman}}(m_i,c_j)}{\&PartialD;{\mathrm{<figure-callout\; id="2"\; label="m"\; filenames="HSA00000036532900022.png,HSA00000036532900051.png"\; state="\{\{state\}\}">m</figure-callout>}}_2}=0,$

$\frac{{\&PartialD;U}_{\mathrm{wman}}(m_i,c_j)}{{\&PartialD;\mathrm{<figure-callout\; id="3"\; label="m"\; filenames="HSA00000036532900051.png,HSA00000036532900052.png"\; state="\{\{state\}\}">m</figure-callout>}}_3}=0,$

$\frac{{\&PartialD;U}_{\mathrm{wman}}(m_i,c_j)}{{\&PartialD;\mathrm{<figure-callout\; id="4"\; label="m"\; filenames="HSA00000036532900022.png,HSA00000036532900051.png"\; state="\{\{state\}\}">m</figure-callout>}}_4}=0,$

$\frac{{\&PartialD;U}_{\mathrm{wman}}(m_i,c_j)}{{\&PartialD;\mathrm{<figure-callout\; id="5"\; label="m"\; filenames="HSA00000036532900022.png,HSA00000036532900041.png"\; state="\{\{state\}\}">m</figure-callout>}}_5}=0$

$\frac{{\&PartialD;U}_{\mathrm{cell}}(m_i,c_j)}{{\&PartialD;\mathrm{<figure-callout\; id="2"\; label="c"\; filenames="HSA00000036532900022.png,HSA00000036532900051.png"\; state="\{\{state\}\}">c</figure-callout>}}_2}=0,$

$\frac{{\&PartialD;U}_{\mathrm{cell}}(m_i,c_j)}{{\&PartialD;\mathrm{<figure-callout\; id="4"\; label="c"\; filenames="HSA00000036532900022.png,HSA00000036532900051.png"\; state="\{\{state\}\}">c</figure-callout>}}_4}=0;$

With the above equation abbreviation, can get the equation behind corresponding following six abbreviations:

N ₁(m ₂+c ₂)＝N ₂(B _m-m ₂-m ₃-m ₄-m ₅)，

N ₁(m ₃+B _c1-c ₂+B _l1)＝N ₃(B _m-m ₂-m ₃-m ₄-m ₅)，

N ₁(m ₄+c ₄)＝N ₄(B _m-m ₂-m ₃-m ₄-m ₅)，

N ₁(m ₅+B _c2-c ₄+B _l2)＝N ₅(B _m-m ₂-m ₃-m ₄-m ₅)，

N ₂(B _l1+B _c1-c ₂+m ₃)＝N ₃(c ₂+m ₂)，

N ₄(B _l2+B _c2-c ₄+m ₅)＝N ₅(c ₄+m ₄)；

1c) the equation behind above-mentioned six abbreviations of simultaneous can obtain Nash Equilibrium and separates through finding the solution this Simultaneous Equations, obtains making the benefit of each network to reach maximum policy in resource management.

Step 2: carry out the cognitive ring of network level, according to the information that the L-RMC module provides, the RRP module is utilized the Forecasting Methodology based on Wiener-Hopf equation, through the resource requirement situation of the conditions of demand of past switch call resource being predicted future, a period of time intra was called out.

1a) utilize Wiener-Hopf equation that the required resource increment of switch call is carried out modeling; Suppose that R (t) is the required number of resources of t switch call constantly; This method is every at a distance from Δ t time prediction once to the required number of resources of switch call; Utilize basic dimension to receive the variation model of model; Switching required resource increment is modeled as: here μ for control average constant factor; δ is the constant factor of control criterion difference; α is that average is that 0 variance is 1 standardized normal distribution; Therefore Δ R is that average is μ Δ t; Standard deviation is the normal distribution of

; Learn that by

for arbitrary time span Δ t, Δ R can utilize μ and δ directly to calculate;

1b) find the solution the estimated value of above-mentioned μ and δ, suppose that μ and δ can utilize the average and the standard deviation of Δ R sampled value to estimate for given time interval τ arbitrarily.If t is a current time; μ τ and are respectively the average and the standard deviation of sample value; Sampling time interval is [t, t-τ], [t-τ; T-2 τ]; ... [t-(k-1) τ, t-k τ], wherein k represents sampling number; Make r (t) represent R (t) in t sampled value constantly; Then the sample value of Δ R is r (t-i τ)-r (t-i τ-τ), i=0 in the time interval [t-i τ, t-i τ-t]; ... k-1, thus the estimated value that draws μ and δ is respectively

and

$\widehat{\mathrm{\&mu;}}=\frac{\underset{i=0}{\overset{k-1}{\mathrm{\&Sigma;}}}(r(t-\mathrm{i\&tau;})-r(t-\mathrm{i\&tau;}-\mathrm{\&tau;}))}{\mathrm{k\&tau;}}=\frac{r\left(t\right)-r(t-\mathrm{k\&tau;})}{\mathrm{k\&tau;}},$

$\widehat{\mathrm{\&delta;}}=\frac{1}{\sqrt{\mathrm{\&tau;}}}\sqrt{\frac{\underset{i=0}{\overset{k-1}{\mathrm{\&Sigma;}}}{(r(t-\mathrm{i\&tau;})-r(t-\mathrm{i\&tau;}-\mathrm{\&tau;})-\widehat{\mathrm{\&mu;}}\mathrm{\&tau;})}^2}{k}}$

1c) confirm the resource reservation value; From the above mentioned; Because

can know

utilizes μ and the δ in above-mentioned estimated value

and

replacement formula

; Then according to the notion of standardized normal distribution α quantile, draw and satisfy given finger target resource reservation value through looking into the standardized normal distribution table.

Step 3: the information of forecasting according to RRP provides, carry out the reservation of switch call resource by the RR module, and the obligate information of resource passed to the L-RRM module.

Step 4: when the user arrives, do not shunt with two kinds of strategies of service distributing and RR submodule output information situation according to the outgoing traffic of TAM unit and to admit control, this admittance control is divided into two kinds of different performances:

The one, situation about not shunting for business: when the user arrives, judge whether current overlay area has the network can

So that the user independently to be provided required resource, admit if condition is set up, otherwise the user is not admitted.

The 2nd, for the situation of service distributing: when the user arrives; Judge at first whether current overlay area has network can independently provide the user required resource; If setting up, condition admits, otherwise, judge whether resource that all available networks of region provide jointly satisfies user's resource requirement; Admit if condition is set up, otherwise the user is not admitted.

Step 5:L-RMC module is collected user's resource requirement information, and these information are passed to RRP module and RMC module, carries out the prediction of network resource requirement by the RRP unit, and the RMC submodule carries out compiling, store and handling of network environment information.

The information of L-RMC module transmission is compiled, stores and handled to step 6:RMC module; And the information that obtains passed to historical information storehouse HID; Carry out information processing and renewal by the historical information storehouse, after the renewal information is passed to the RA submodule, repeating step 1 is to step 6.

Effect of the present invention can further specify with following simulation result:

1. simulating scenes

Simulating scenes of the present invention is as shown in Figure 3, and it comprises three kinds of network coverages, and wherein WMAN Network covers All Ranges, and WLAN Network covers 3 and 5 zones, and Cellular Network covers 2 and 4 zones.

2. emulation content and result

2a) the cognitive ring of artificial network level is chosen 3 zones and is discussed the influence of network performance in the emulation;

The arrival rate of new calling and switch call all is to change to 13/minute from 5/minute in the emulation; The duration of calling out all is 5 minutes; Be that 80% system resource, simulation result such as Fig. 4 and shown in Figure 5 are reserved in switch call when not adding the cognitive ring of network level.Fixed resource 80% curve correspondence among this Fig. 4 and Fig. 5 does not add the cognitive ring of network level, the shunting among Fig. 4 and Fig. 5 and do not divide that flow curve is corresponding to add that the networking level is cognitive to be encircled.

2b) the cognitive ring of emulation net intercaste is to the influence of network performance, and emulation is chosen All Ranges and discussed;

Choosing five periods of one day in the emulation analyzes; Each period, total traffic carrying capacity was identical; Total user's arrival rate all is 28/minute; But the professional proportion in each sub-district of different time is dynamic change, will introduce the cognitive ring of net intercaste in the emulation network can be compared according to the dynamic change adjustment this situation of network parameter of professional proportion with in the situation of not netting the cognitive ring of intercaste.Simulation result such as Fig. 6, Fig. 7 and shown in Figure 8.This Fig. 6 is a zone new call blocking rate of 2 each periods, and Fig. 7 is the mean value of each new call blocking rate in zone, and Fig. 8 is the standard deviation of each new call blocking rate in zone.

3. analysis of simulation result

4a) the cognitive influence that encircles network performance of artificial network level: from the simulation result of Fig. 4 and Fig. 5, can find out; The improvement situation that adds the cognitive ring of network level back network performance is embodied in; Satisfy under the given finger target prerequisite at the switch call blocking rate, the blocking rate of the adding network level new calling in cognitive ring back is obviously lower.

4b) the cognitive influence that encircles network performance of emulation net intercaste: from Fig. 6 simulation result, can find out; The 2 new call blocking rates variations of the cognitive postcricoid area of net intercaste territory are more steady introducing; From Fig. 7 simulation result, can find out; The new average blocking rate of calling out in each zone, the cognitive ring of net intercaste back is lower introducing, and from Fig. 8 simulation result, can find out, and is less in the variance of introducing each new call blocking rate in zone of the cognitive ring of net intercaste back.

Claims (7)

1. the heterogeneous network resource management system based on cognition comprises

RRM module between net constitutes the superstructure of network resource management system, is used to accomplish the management of resource between heterogeneous network and the maintenance in historical information storehouse, and resource management decision information is provided for the RRM module;

The RRM module, the understructure of formation network resource management system is used to accomplish the resource management of each wireless access network internal, and for RRM module between netting the environmental information of each wireless network is provided;

Described superstructure, the environmental information of each wireless network that provides through understructure is set up and is upgraded the historical information storehouse, and according to the historical information storehouse business is predicted, obtains resource management decision, and decision information is passed to understructure; Described understructure through with the resource management decision information of obtaining alternately of superstructure, and the management of resource in carry out this wireless network according to the decision information that obtains constitutes the cognitive ring of net intercaste.

2. heterogeneous network resource management system according to claim 1; RRM module between wherein netting; Comprise historical information storehouse submodule and resource allocation submodule; This historical information storehouse submodule is according to collecting periodically to upgrade the historical information storehouse from the environmental information of each different radio Access Network, for the resource allocation submodule provides required information; This resource allocation submodule periodically carries out the reasonable resources management according to the environmental information of the wireless network that historical information storehouse submodule provides, with each wireless access network of the decision notification of being done.

3. heterogeneous network resource management system according to claim 1, RRM module wherein comprises:

RRM submodule in the net; Be used to accomplish the resource management of the network level of wireless access network internal; The user service information that resource management decision information that provides according to the resource allocation submodule and link level RRM submodule provide; Carry out the prediction of Network, and carry out the reservation of switch call resource, and execution result is passed to link level RRM submodule according to predicting the outcome;

Link level RRM submodule; Be used to accomplish the resource management of wireless access network internal link level; The switch call resource obligate information that provides according to RRM submodule in the net carries out user's admittance control; And for RRM submodule in the net provides necessary user service information, and these information are passed to resource information measurement collection device submodule;

Resource information measurement collection device submodule is used to collect, store, handle the environmental information of the wireless network of wireless access network, and the environmental information of these wireless networks is passed to the historical information storehouse.

The RRM submodule is that link level RRM submodule provides the switching arranged resources value in the described net; Described link level RRM submodule is admitted control according to the switching arranged resources value that provides; And collection switch call business information; And collected relevant switch call business information passed to RRM submodule in the net, constitute the cognitive ring of network level.

4. according to claims 3 described heterogeneous network resource management systems; RRM submodule in wherein netting; Comprise resource requirement predicting unit and resource reservation unit; This resource requirement predicting unit generates the reservation policy of resource according to connecting the customer service demand environment information that level resource information measurement collection device provides, and the reservation policy information of carrying out is passed to the resource reservation unit; This resource reservation unit carries out the reservation of resource according to the reservation policy information that the resource requirement predicting unit provides, and execution result information is passed to link level RRM submodule;

5. according to claims 3 described heterogeneous network resource management systems; Link level RRM submodule wherein; Comprise traffic assignments administrative unit, admission control cell and be connected level resource information measurement collection device unit; How distributing of this traffic assignments administrative unit management service, and the management strategy that generates passed to admission control cell; This admission control cell is controlled according to the admittance that traffic assignments information that obtains and resource obligate information carry out the user; This connection level resource information measurement collection device unit is responsible for collecting, the environmental information of storage, process user, and the information of collecting is passed to resource information measurement collection device submodule.

6. the heterogeneous network resource management method based on cognition comprises the steps:

(1) resource distribution module obtains the network environment information that the historical information library module provides; According to these information that obtain, resource distribution module utilizes Forecasting Methodology, and according to the non-cooperative game opinion each network is carried out the management of resource in each overlay area; Promptly through study to network state historical information storehouse and network current state; Acquisition is to the predicted value of network number of users in a period of time in future, and the number of users according to each network's coverage area of gained utilizes non-cooperative game opinion method that the resource of each network institute overlay area is carried out distribution again; Internet resources are fully utilized, realize the maximizing the benefits of operator;

(2) according to connecting the information that level resource information measurement collection device unit provides; The resource requirement predicting unit is utilized the Forecasting Methodology based on Wiener-Hopf equation; Through processing to the conditions of demand of switch call resource; Under given performance index, obtain the possible resource requirement situation of a period of time intra calling in the future;

(3) predicted value that provides according to the resource requirement predicting unit is carried out the resource reservation unit and is carried out the reservation of switch call resource, satisfies index request with the cutting off rate that guarantees switch call;

(4) when the user arrives,, admit control according to the implementation status of traffic assignments administrative unit and resource reservation unit;

(5) user resources information is offered a connection level resource information measurement collection device unit;

(6) resource information measurement collection device submodule compiles the information that connects level resource information measurement collection device unit, and the information that obtains is offered the historical information storehouse, is carried out the renewal in information processing and historical information storehouse by the historical information storehouse.

7. according to claims 6 described heterogeneous network resource management methods based on cognition, wherein the described implementation status according to traffic assignments administrative unit and resource reservation module of step (4) is admitted control, is divided into two kinds of situation:

The one, professional situation about not shunting: when the user arrives, judge whether current overlay area has network can independently provide the user required resource, admit if condition is set up, otherwise the user is not admitted.

The 2nd, for the situation of service distributing: when the user arrives; Judge at first whether current overlay area has network can independently provide the user required resource; If setting up, condition admits, otherwise, judge whether resource that all available networks of region provide jointly satisfies user's resource requirement; Admit if condition is set up, otherwise the user is not admitted.

Images