CN1678120A - Resource reservation intelligent call admission control method and apparatus - Google Patents

Resource reservation intelligent call admission control method and apparatus Download PDF

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CN1678120A
CN1678120A CN 200510011698 CN200510011698A CN1678120A CN 1678120 A CN1678120 A CN 1678120A CN 200510011698 CN200510011698 CN 200510011698 CN 200510011698 A CN200510011698 A CN 200510011698A CN 1678120 A CN1678120 A CN 1678120A
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user
interference
fuzzy
resource reservation
admission control
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CN100384299C (en
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朱刚
牛桂新
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Beijing Jiaotong University
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Beijing Jiaotong University
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Abstract

In the invention, admitting decision is implemented by using current number of system users to replace measurement outage probability in ICAC scheme. The method includes three modules: fuzzy equivalent interference estimator, neural network interference predictor, and fuzzy call admission processor. The estimator is in use for estimating interference generated by new call request users. The predictor is in use for one step predicting interference from users connected to current system already. The fuzzy call admission processor is in use for admitting decision for new call request users. Strategy of obligated resources is adopted in the invention to lower outage probability of each class of service. Comparing number of current user with difference between system admissible maximum number of user and obligated number of user is one of reference for admitting decision. Features are: simple, small amount of calculation, and low blocking probability of new call request users under heavy load.

Description

A kind of resource reservation intelligent call admission control method and device
Affiliated technical field
The present invention relates to call connection control method, particularly a kind of intelligence call acceptance control (RRICAC:Resource Reserved Intelligent Call Admission Control) method and device based on resource reservation belongs to the telecommunication system resources management domain.
Background technology
Call connection control method is just in developing stage.Current, cry in the cdma cellular communication system and admit the research of controlling schemes to mainly contain three major types: a class is based on the CAC algorithm of SIR or total interfering signal power; The another kind of CAC algorithm that is based on the power system capacity analytical model; A class is based on the CAC algorithm of power controlling models again.But these algorithm researches or be confined to single operation system, or can not satisfy a plurality of qos requirements of system simultaneously.
Chang Chung-Ju has proposed to control (ICAC) scheme based on the intelligence call acceptance of neural network identification and fuzzy decision technology at above problem in its article " the intelligence call acceptance control under different Q os requires in the Wideband CDMA Systems " (Intelligent Call Admission Control for Differentiated QoSProvisioning in Wideband CDMA Cellular Systems) literary composition, utilize fuzzy decision and neural network identification ability respectively, estimate that new user asks to have connected in the equivalence interference that produces and the system user's average interference, according to the measurement outage probability of the current all kinds of business of two interference estimating and system feedback, whether the admittance of decision call request then.This ICAC algorithm can be applicable to the multi-service cdma system, can guarantee all the time that all kinds of service disconnection probability meet the demands.But there are following two shortcomings in this algorithm: 1) implement complexity, the algorithm implementation will constantly be measured and the current outage probability of computing system, and the correlation computations amount is big; 2) strict guarantee of system break probability makes that new call request user's blocking probability is too high under the heavy duty situation.
Summary of the invention:
At the shortcoming that exists in the above-mentioned existing method, problem to be solved by this invention provides a kind of intelligence call acceptance control method and device based on resource reservation, shortcut calculation is implemented complexity, reduces new call request user's blocking probability in system break probability tolerable scope.
The technical solution adopted for the present invention to solve the technical problems is:
A kind of intelligence call acceptance control device based on resource reservation with the measurement outage probability in the current system user number replacement ICAC scheme, is implemented acceptance judging.Comprise three modules: fuzzy equivalent interference estimator, neural net interference prediction device and fuzzy call acceptance processor.Fuzzy equivalent interference estimator module is used to estimate that new call request user produces interference; Neural net interference prediction device is used for having connected in the current system one-step prediction that the user disturbs; Fuzzy call acceptance processor is used for new call request user's acceptance judging.
A kind of resource reservation intelligent call admission control method adopts fuzzy decision and nerve network recognition technique to implement the Call Admission Control algorithm, and the uncertainty and the expert info of utilization fuzzy logic carry out interference and the acceptance judging that new call request user produces; Non-linear and the prediction characteristic of utilization nerve network recognition technique carries out being connected in the system one-step prediction that the user produces interference.
Fuzzy equivalent interference estimator adopts the fuzzy decision technology, according to service parameter (the peak rate R of new call request p, average speed R m, the peak rate duration T pAnd outage probability requires P Otg), estimate the interference I of its generation New
Neural net interference prediction device designs a serial feedback neural net according to System Discrimination and neural networks principles, and Installed System Memory is at user's average interference I during current time n k' (n) as the input variable of serial feedback neural net, come accurately predicting to connect user's interference I during next moment (n+1) in the system k^ (n+1).
Fuzzy call acceptance processor utilizes the fuzzy decision technology, the one-step prediction interference and the current system that have connected the user in the system of the equivalence interference that the new call request of exporting according to fuzzy equivalent interference estimator produces, the output of neural net interference prediction device hold number of users Num, carry out the acceptance judging of new call request.Reserve a part of number of users for reducing outage probability, have only when system's active user's number is not more than the open ended maximum number of user of system and reserves the difference of number of users, new call request user just might be admitted.The value of reserving number of users is set according to test method: under a certain arrival rate of user, be recorded in the different systematic functions of reserving under the number of users situation, the reserved value under the selection performance best-case is as its final value.
The present invention has following advantage:
1, the present invention adopts resource reservation policy to reduce the outage probability of all kinds of business, as one of foundation of acceptance judging, implements the comparison of the open ended maximum number of user of the active user of system number and system and the difference of reserving number of users simple.In the algorithm implementation process, system active user's number need are converted to corresponding linguistic variable according to its member function, and then are input to indistinct logic computer with other parameter language variable and get final product, and simple, amount of calculation is little.
2, the present invention has reduced new call request user blocking probability under the heavy duty situation.Since the ICAC algorithm current system break probability as one of main foundation of acceptance judging, according to fuzzy admission processing device decision rule, as long as outage probability is near requiring thresholding, new call request will get clogged, and the present invention reduces outage probability by reserved resource rather than acceptance judging, therefore, and after the value of given reserved resource, along with the increase of load, the blocking probability of this invention must be lower than ICAC.
3, the present invention has adopted reservation policy, makes that the system break probability is still in the tolerable scope under the heavy duty situation.Integrated system outage probability and new the two factor of call request user blocking probability consider that the grade of service of the present invention is better than the ICAC algorithm.
Description of drawings
Below in conjunction with accompanying drawing the present invention is described in further detail,
Fig. 1 is a resource reservation intelligent call admission controlling schemes frame diagram of the present invention.
Fig. 2 is the fuzzy equivalent interference estimator schematic diagram of resource reservation intelligent call admission controlling schemes of the present invention.
Fig. 3 is the neural net interference prediction device structure chart of resource reservation intelligent call admission controlling schemes of the present invention.
Fig. 4 is the flowchart of resource reservation intelligent call admission controlling schemes of the present invention.
Fig. 5 is a simulation result.
Embodiment 1: a kind of intelligence call acceptance control device based on resource reservation comprises:
Fuzzy equivalent interference estimator: estimate the interference of its generation according to the service parameter of new call request.
Neural net interference prediction device:, connect user's interference when predicting next in the etching system according to the average interference of current time Installed System Memory the user.
Blur the call acceptance processor: the one-step prediction interference and the current system that have connected the user in the system of the equivalence interference that the new call request of exporting according to fuzzy equivalent interference estimator produces, the output of neural net interference prediction device hold number of users, carry out the acceptance judging of new call request.
As shown in Figure 1, the service parameter of new call request (is peak rate R p, average speed R m, the peak rate duration T pAnd outage probability requires P Otg) be input to fuzzy equivalent interference estimator, estimate the interference I of its generation NewCurrent time (n constantly) Installed System Memory is at user's average interference I k' (n) be input to neural net interference prediction device, predict next interference I of connection user in (n+1 is constantly) system constantly k^ (n+1); Fuzzy call acceptance processor is according to I New, I k^ (n+1) and current system hold number of users Num and carry out acceptance judging.
A kind of resource reservation intelligent call admission control method, described fuzzy equivalent interference estimator is a fuzzy implementation, as shown in Figure 2, estimator is converted to the corresponding language variable to the service parameter of new call request according to the member function in the fuzzy logic, input as fuzzy inference system, then according to corresponding fuzzy rule, try to achieve the fuzzy set of the interference that the new call request of estimation produces, utilize the defuzzification method to calculate its numerical value.
Described neural net interference prediction device is according to the System Discrimination principle, is the interference modeling that has connected the user in the system non-linear ARMA model (NARMA), utilize the NARMA model that the one-step prediction of average interference is described as p the function of measuring interference and q the interference of having predicted, promptly
I k ^ ( n + 1 ) = H ( I k ′ ( n ) , . . . , I k ′ ( n - p + 1 ) ; I k ^ ( n ) , . . . , I k ^ ( n - q + 1 ) ) - - - ( 1 )
Wherein, I kI in ^ (i) the expression k sub-district (moment average interference predicted value of n-q+1≤i≤n), I k' (i) expression i (n-p+1≤i≤n) is the average interference measured value constantly, and H () is a nonlinear function undetermined.Be similar to H () function by designing a serial feedback neural net, to reach higher forecasting precision, very fast rate of convergence and low computation complexity.Installed System Memory is at user's average interference I during current time n k' (n) as the input variable of serial feedback neural net, come accurately predicting to connect user's interference I during next moment (n+1) in the system k^ (n+1) is for the accuracy of strengthening predicting, I k' (n) get the average of system interference in N T time period, promptly
I k ′ ( n ) = Σ i = 0 N - 1 I k ( n - iT ) N - - - ( 2 )
Wherein, the length of N express time window.Feedback Neural Network interference prediction device structure comprises the q layer network as shown in Figure 3, and every layer all has a similar neural network model and a subtracter.The i layer network has two outside inputs: measure interference sample value I k' time-delay (n-i+2) and first output neuron Y of preceding one deck I+1,1(n), I k' (n-i+2) difference with this model output constitutes error signal e i(n), be used for dynamically adjusting the weights of i neural network model.The output Y of first model 1,1(n) be exactly next the predicted interference I constantly that requires k^ (n+1).
Described fuzzy call acceptance processor is a fuzzy judgment process, acceptance judging value Z that obtains after the processor defuzzification and admittance thresholding Z THMake comparisons, if Z>Z TH, just admit new call request, otherwise refusal.
Wherein resource reservation is embodied in current selection and the parameter of holding the number of users member function of system and is provided with, reserve a part of number of users for reducing outage probability, have only when system's active user's number is not more than the open ended maximum number of user of system and reserves the difference of number of users, new call request user just might be admitted.System can hold maximum number of user and be required to determine by the outage probability of speech and data service:
P otg 1 = Pr { Z k < SIR 1 * } &le; P otg 1 * - - - ( 3 )
P otg 2 = Pr { Z k < SIR 2 * } &le; P otg 2 * - - - ( 4 )
Z k = &Sigma; i = 1 N v , k v i , k + &Sigma; j = 1 N d , k &delta; j , k &CenterDot; R G &CenterDot; M j , k - - - ( 5 )
V in the formula (5) I, kAnd δ J, kThe activation probability of representing interior voice user i of sub-district k and data user j respectively.Try to achieve N by formula (3) to (5) V, kAnd N D, kMaximum, system holds maximum number of user and gets the maximum in two maximums.The value of reserving number of users is set: under a certain arrival rate of user according to test method, be recorded in the different systematic functions of reserving under the number of users situation, reserved value under the selection performance best-case is as its final value, then according to this value simulating, verifying resource reservation intelligent call admission control method.
Mamdani pattern fuzzy logic system is all adopted in fuzzy equivalent interference estimator and the design of fuzzy call acceptance processor, and ambiguity solution all adopts centre of area method, and computing formula is:
X = &Sigma; i = 1 K &omega; i &times; X i &Sigma; i = 1 K &omega; i
Wherein, ω iThe expression weight, X iThe fuzzy set of expression input.
The said method flow process as shown in Figure 4.Process step is as follows:
Step 1: the arrival of Waiting for Call request,
Step 2: estimate the interference that call request produces,
Or step 3: predict that the user disturbs in the current system,
Or step 4: measure number of users in the current system,
Step 5: ask acceptance judging value Z,
Step 6: judge that whether decision value Z is greater than a definite value Z THIf,, step 7 below carrying out, if not, refusal is got back to step 1,
Step 7: admittance also distributes respective channel from available channel, number of users adds one in the system, returns step 1.
Based on the performance evaluation index of the intelligence call acceptance control method of resource reservation and device with new call request arrival rate change curve referring to Fig. 5.
Embodiment 2:
In radio transmission, mainly there are path and shadow loss, the user is evenly distributed in the sub-district, and all users have the control of perfect power in its home cell, and promptly the power of each primary channel of the speech that receives of base station or data service all equals normal value.
The business that user terminal produces is divided into two kinds of real-time voice service and non real-time data services, Poisson distribution is all obeyed in speech and data user's arrival, voice sources is modeled as two condition discrete time Markov Chain, during ON state (conversation phase), produce an air interface packet in every frame length T time, during OFF state (quiet period), do not produce air interface packet, conversation and quiet period average duration are obeyed the exponential distribution that parameter is 1/ α and 1/ β respectively, data source is characterized by group's Poisson process, and the average information arrival rate is A d, data message length for obey geometric distributions on the occasion of stochastic variable, according to the processing gain of data service, higher layer protocol data units is further divided into one group of air interface packet.
The method of customization is adopted in the design of serial feedback neural net interference prediction device, utilizes Levenberg-Marquardt rule neural network training.
Adopt the strategy of resource reservation to reduce the system break probability, the comparison of the open ended maximum number of user of system active user's number and system and the difference of reserving number of users is as one of foundation of acceptance judging, under a certain arrival rate of user, be recorded in the different systematic functions of reserving under the number of users situation, reserved value under the selection performance best-case is as its final value, then according to this value simulating, verifying resource reservation intelligent call admission control method.

Claims (7)

1, a kind of resource reservation intelligent call admission control device, it is characterized in that: comprising: fuzzy equivalent interference estimator, neural net interference prediction device and fuzzy call acceptance processor, fuzzy equivalent interference estimator module is used to estimate that new call request user produces interference; Neural net interference prediction device is used for having connected in the current system one-step prediction that the user disturbs; Fuzzy call acceptance processor is used for new call request user's acceptance judging.
2, a kind of resource reservation intelligent call admission control method, it is characterized in that: adopt fuzzy decision and nerve network recognition technique to implement the Call Admission Control algorithm, the uncertainty and the expert info of utilization fuzzy logic carry out interference and the acceptance judging that new call request user produces; Non-linear and the prediction characteristic of utilization nerve network recognition technique carries out being connected in the system one-step prediction that the user produces interference.
3, a kind of resource reservation intelligent call admission control method according to claim 2, it is characterized in that: adopt the strategy of resource reservation to reduce the system break probability, the comparison of the open ended maximum number of user of system active user's number and system and the difference of reserving number of users is as one of foundation of acceptance judging, under a certain arrival rate of user, be recorded in the different systematic functions of reserving under the number of users situation, reserved value under the selection performance best-case is as its final value, then according to this value simulating, verifying resource reservation intelligent call admission control method.
4, a kind of resource reservation intelligent call admission control method according to claim 2, it is characterized in that: the business that user terminal produces is divided into two kinds of real-time voice service and non real-time data services, Poisson distribution is all obeyed in speech and data user's arrival, voice sources is modeled as two condition discrete time Markov Chain, during ON state (conversation phase), produce an air interface packet in every frame length T time, during OFF state (quiet period), do not produce air interface packet, conversation and quiet period average duration are obeyed the exponential distribution that parameter is 1/ α and 1/ β respectively, data source is characterized by group's Poisson process, and the average information arrival rate is A d, data message length for obey geometric distributions on the occasion of stochastic variable, according to the processing gain of data service, higher layer protocol data units is further divided into one group of air interface packet.
5, a kind of resource reservation intelligent call admission control method according to claim 2, it is characterized in that: in radio transmission, mainly there are path and shadow loss, the user is evenly distributed in the sub-district, all users have the control of perfect power in its home cell, promptly the power of each primary channel of the speech that receives of base station or data service all equals normal value.
6, a kind of resource reservation intelligent call admission control method according to claim 2, it is characterized in that: Mamdani pattern fuzzy logic system is all adopted in fuzzy equivalent interference estimator and the design of fuzzy call acceptance processor, ambiguity solution all adopts centre of area method, and computing formula is:
X = &Sigma; i = 1 K &omega; i &times; X i &Sigma; i = 1 K &omega; i
7, a kind of resource reservation intelligent call admission control method according to claim 2 is characterized in that: the method for customization is adopted in the design of serial feedback neural net interference prediction device, utilizes Levenberg-Marquardt rule neural network training.
CNB2005100116988A 2005-05-10 2005-05-10 Resource reservation intelligent call admission control method and apparatus Expired - Fee Related CN100384299C (en)

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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2007098684A1 (en) * 2006-03-01 2007-09-07 Huawei Technologies Co., Ltd. A processing method of resource amendment failure and device thereof
CN101163255B (en) * 2006-10-12 2010-04-21 中兴通讯股份有限公司 Local strategy control method for resource preservation using fuzzy theory
CN1980480B (en) * 2005-12-08 2010-12-22 株式会社Ntt都科摩 Apparatus and method for call admission control
CN101360319B (en) * 2007-07-30 2011-07-20 鼎桥通信技术有限公司 Resource reservation method and apparatus based on traffic
WO2021036414A1 (en) * 2019-08-29 2021-03-04 浙江大学 Co-channel interference prediction method for satellite-to-ground downlink under low earth orbit satellite constellation

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1373572A (en) * 2001-03-01 2002-10-09 深圳市中兴通讯股份有限公司 Recepting control method for mixed services of broad-band CDMA system
CN1146174C (en) * 2001-06-27 2004-04-14 华为技术有限公司 Call permission control method for multi-speed CDMA mobile communication system

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1980480B (en) * 2005-12-08 2010-12-22 株式会社Ntt都科摩 Apparatus and method for call admission control
WO2007098684A1 (en) * 2006-03-01 2007-09-07 Huawei Technologies Co., Ltd. A processing method of resource amendment failure and device thereof
CN101163255B (en) * 2006-10-12 2010-04-21 中兴通讯股份有限公司 Local strategy control method for resource preservation using fuzzy theory
CN101360319B (en) * 2007-07-30 2011-07-20 鼎桥通信技术有限公司 Resource reservation method and apparatus based on traffic
WO2021036414A1 (en) * 2019-08-29 2021-03-04 浙江大学 Co-channel interference prediction method for satellite-to-ground downlink under low earth orbit satellite constellation

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