CN100348071C - Method and system for optimising the performance of a network - Google Patents

Method and system for optimising the performance of a network Download PDF

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Publication number
CN100348071C
CN100348071C CNB028211200A CN02821120A CN100348071C CN 100348071 C CN100348071 C CN 100348071C CN B028211200 A CNB028211200 A CN B028211200A CN 02821120 A CN02821120 A CN 02821120A CN 100348071 C CN100348071 C CN 100348071C
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parameter
value
cost function
network
performance indicators
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CN1575614A (en
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艾伯特·赫格隆德
阿德里安·弗拉纳根
汤玛斯·诺沃萨达
亚纳·莱霍
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Nokia Solutions and Networks Oy
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/50—Network service management, e.g. ensuring proper service fulfilment according to agreements
    • H04L41/5003—Managing SLA; Interaction between SLA and QoS
    • H04L41/5019—Ensuring fulfilment of SLA
    • H04L41/5025—Ensuring fulfilment of SLA by proactively reacting to service quality change, e.g. by reconfiguration after service quality degradation or upgrade
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04Q—SELECTING
    • H04Q3/00—Selecting arrangements
    • H04Q3/0016—Arrangements providing connection between exchanges
    • H04Q3/0062—Provisions for network management

Abstract

When optimising the performance of the network, first of all, the relevant key performance indicators for a specific entity within the network as well as first parameters, which influence the key performance indicators, are determined. A number of entities similar to said specific entity is selected, wherein relevant key performance indicators are associated to every en-tity. The key performance indicators as well as the selected number of en-tities are used as elements in a first cost function, i.e. said first cost func-tion is calculated on the basis of the KPI and the number of entities. Said first cost function is calculated in order to evaluate the network perform-ance. Accordingly, since said first parameters directly relate to the key per-formance indicators, the network performance will depend on the values of said first parameters. Thereafter the values of said first parameters are adjusted, so that a sec-ond set of values of said first parameters are obtained. The key perform-ance indicators are determined again but this time on the basis of the sec-ond values of said first parameters and said first cost function is re-calculated on the basis of these key performance indicators. The result of said first cost function calculated on the basis of said first values of said first parameters is compared to the result of said first cost function re-calculated on the basis of said second values of said first parameters. This comparison is carried out to determine whether the network performance has improved. When the network performance has improved due to the adjusting of said first parameters, said second values of said first parame-ters are adopted as permanent parameters.

Description

Be used to optimize the method and system of network performance
Technical field
The present invention relates to a kind of method and system that is used to optimize network performance.
Background technology
The commercial affairs of managed service provider about how, the telecommunications management network (tmn) model provides a kind of widely accepted method.The TMN model comprises usually 4 layers that manage with triangular pattern or taper mode, and wherein the superiors are that business management, the second layer are that Service Management, the 3rd layer are that network management, bottom are Single Component Managements.Every layer administrative decision is different mutually, but relevant mutually.When work is carried out from top to bottom, all lower floor is released requirement for every layer.In work when carrying out from bottom to top, every layer the significant data resource delivered to the upper strata.Tele Management Forum (TeleManagement Forum ' s (TMF)) TMN has determined the guide of optimizational function and process.The third generation project ((3 of pulling together RdGeneration Partnership Project) 3GPP) adopts same model.The working range of TMF is that searching is used for determining service quality, network requirement is set and makes and can have the standardized way that QoS reports between the system of provider and this service of realization according to service quality (QoS) measured value.
According to the TMN model, the information of upper system flows downward, to guarantee network seamless operation and optimization possibility.Fig. 3 illustrates the TMN model.Information flows to Service Management downwards from the Business Management Layer always, and network management is most important, because in optimization and network development process, must scrutinize commercial aspect.The variation of the level of abstraction in the TMN model demonstration operator routine work.(CAPEX OPEX) and income, can weigh the efficient of commercial affairs planning to utilize capital and operation funds.Then, service, priority of service and the service QoS requirement that provides is provided the commercial situation with hope.At the orlop (network element) of TMN model, will be transformed to the configuration parameter setting with commerce related problem.
For example, the function of TMN business management system support is: set up investment planning; Main QoS criterion is determined in network and service thereof to suggestion; Setting up technological development approach (expansion approach) increases to guarantee the number of users expection.
For example, the function of service management system support is: leading subscriber data, the service that provides and user; Gather and appraise and decide the bill service that provides; Foundation, lifting and Monitoring Service.
For example, the function of network management system (nms) support is: planning network; From lower floor's network Information Monitoring and preliminary treatment/reprocessing initial data; Analyze and distributed intelligence; Optimize network capacity and quality.
The part that entity management system can be regarded as Network Element Function is responsible for: the running of monitoring equipment; Gather initial data (performance indicators), provide this machine graphic user interface (GUI) for the field engineer; And as media to the NMS system.
Except TMN, TMF has also defined telecommunications service chart (Telecom OperationMap (TOM)).Telecommunications and data service provider must be used the customer-oriented service management that adopts commercial process management method to learn, and manage and provide the service and the quality of customer requirement its commercial affairs are carried out cost-effectively.TOM discerns many operational management processes, comprises customer service, Service Management and network management.The telecommunications service chart is used as core commercial affairs process with each layer of TMN, but SML is divided into 2 parts: customer service and service development and operation.Describe separately the client and join management, because can be in each customer service subprocess, the managing customer handing-over be managed, perhaps one or more customer service subprocess of combined access.
Fig. 4 illustrates the network management process and supports the high-level structure of collection of functions group (Function Set Group).According to the framework that TOM provides, can be with each high-rise process image to a series of member functions (component function) (being arranged in the collection of functions group).Suppose:
● network performance management (PM) provide enough measured values;
● network configuration management is supported whole TMF framework;
● network management system (nms) has intelligence, with these two kinds of information combination together.
Then, discern relation and information flowing between them between them.In Fig. 4, TOM and member thereof are shown.For each corresponding management layer is described, each layer functional with shown in Figure 3 functional identical.
On the homepage (please refer to http//www.tmforum.org) of TMF, can find detailed description about TMN model and TOM.
In current cellular formula system, utilize quantity of parameters to handle radio resource, even wherein under the condition that changes, the parameter value setting is still fixing.Operator's task is to reach correct working point according to the setting of service quality manual adjustments parameter.Subject object when usually, being optimized is " beginning to make its work (just to get it working) ".In the simple GSM network of pure voice service, this adjusting is led directly to.For WCDMA, the complexity of these parameter settings is many-sided: many services, service type even multi radio environment.Cellular system based on WCDMA provides variable packet-switched services and circuit switched service, therefore more is difficult to planning and control than current network.Strong connection before each sub-district has increased complexity.For the operator, be actually capacity and the service quality (QoS) of utilizing all possible resource to improve radio net.
Network optimization process is used to improve the overall network quality of mobile subscriber's impression, and is used to guarantee effectively use Internet resources.The optimization process comprises phase-split network, and improves network configuration and performance.The statistics of the key performance indicators (KPI) of operational network are delivered to the instrument that is used for the phase-split network state, in order to have more performance, manual adjustment provided for radio resources management (RPM) parameter.In the starting stage of the process of optimization definition key performance indicators (KPI).For example, they comprise measured value and field measurement data or any other information of the network management system (nms) of the service quality (QoS) that can be used for definite network.For second-generation system, service quality (QoS) for example comprises: the measured value that call drop statistics, the call drop analysis of causes, switching statistics and successful call are attempted, and, must produce the new service quality QoS definition that is used to carry out quality analysis for third generation system with more services.
In order to optimize Virtual network operator or service provider's total income, the operating cost and the maintenance cost that reduce network system just need implementation procedure automations in described network system.
Summary of the invention
Therefore, the objective of the invention is to improve the process of optimizing Internet resources.
Utilization can realize this purpose according to method and the corresponding system that is used to optimize network performance of the present invention.
The present invention is based on and utilize concentrated cost function optimization Internet resources, rather than optimize the idea of Internet resources by optimizing Internet resources respectively.
Current, parametrization radio resource management algorithms respectively: switching control parameter value, access control parameter value, power contorl parameters value etc. independently are set, and can discern wherein for example situation of generation switching problem because wrong power control (CPICH) is provided with.Access control changes and may cause the quality of packet data to change.
Therefore, when optimizing the performance of network, at first determine the relevant key performance indicators of special entity in the network and first parameter that influences key performance indicators.Select and the similarly a large amount of entities of described special entity, wherein relevant with each entity about key performance indicators.The physical quantities of key performance indicators and selection promptly, is calculated described first cost function according to KPI and physical quantities as the element of first cost function.Calculate described first cost function with the assessment network performance.Therefore, because described first parameter is directly relevant with key performance indicators, so network performance depends on first value of described first parameter.After this, adjust the value of described first parameter, so that obtain second class value of described first parameter.Determine key performance indicators again, but be to determine specifically, then, recomputate described first cost function according to these key performance indicators according to second value of described first parameter.The result of described first cost function that will calculate according to described first value of described first parameter and the result of described first cost function that described second value according to described first parameter recomputates compare.Carry out this comparison to determine whether network performance improves.When network performance improves because of described first parameter of adjustment, described second of described first parameter is worth as permanent parameter.
Do not utilize centralized control function optimization parameter group, can make the parameter value swing, may have a negative impact to other KPI because if change a parameter in order to optimize KPI but each parameter is set according to many algorithms.Therefore,, do not utilize independent function, concentrate cost function whole monitoring provided for radio resources management process, have advantage but utilize in order to coordinate to change each parameter.
According to improvement structure of the present invention, in described first cost function, utilize the different weights coefficient that each key performance indicators is weighted.Utilize the different weights coefficient can make one or more key performance indicators that first cost function is had bigger influence.
According to the further improvement of the present invention structure, the fiducial value of key performance indicators is set, and utilize difference between current key performance indicators and the corresponding fiducial value to replace key performance indicators (, please refer to equation (1)) in first cost function to determine " cost ".Therefore, calculate first cost function according to the difference between current key performance indicators and the corresponding fiducial value.Can quality of service goals be set according to the cost of the KPI in the system like this.
According to advantageous embodiment structure of the present invention, described first cost function comprises second cost function and the 3rd cost function, and wherein said second cost function is represented the quality requirement in the network, and the 3rd cost function is represented the capacity requirement in the network.Utilize described second cost function of the second weight coefficient weighting, and utilize described the 3rd cost function of the 3rd weight coefficient weighting.Second cost function and the 3rd cost function and respective weight coefficient thereof are provided, can between the capacity of first cost function and quality, realize balance.
Improve structure according to present invention further optimization, second cost function and the 3rd cost function comprise the entity of selection, and wherein the key performance indicators of Que Dinging is relevant with each entity.Like this can be on network extensive distribution key performance indicators.
Improve structure according to present invention further optimization, utilize sub-district or user in the described network to organize the described entity of expression.Therefore, can be according to for example sub-district or the sub-district cluster function that assesses the cost.
Improve structure according to present invention further optimization, repeat to be used to optimize each step of network performance, so that automatically perform optimizing process.
According to another further advantageous embodiment structure of the present invention,, the value of KPI and the accordingly result of corresponding first parameter and first cost function are stored together in order to set up historical data base.The previous result that the current results of described first cost function is stored in it in historical data base compares, and in determining at the fixed time at interval, whether network performance improves.If in described predetermined time interval, network performance does not improve, then send corresponding notice.Do not give notice when detecting when improving at interval at the fixed time, can avoid deadlock occurring in the processing procedure automatically, and point out possible problem.
Description of drawings
Below with reference to the accompanying drawings, be described in more detail the present invention according to preferred embodiment.Accompanying drawing comprises:
Fig. 1 illustrates the flow chart of the automated procedure that is used to optimize network performance;
Fig. 2 illustrates the example of KPI cost function;
Fig. 3 illustrates the schematic diagram of telecommunications management network (tmn) model;
Fig. 4 illustrates the schematic diagram of telecommunications service chart (TOM); And
Fig. 5 illustrates the schematic diagram of the combination of the monitoring that is used for different management level and majorized function.
Embodiment
In Fig. 1, the flow chart of optimizing the automated procedure of network performance according to first embodiment of the invention is shown.At first, at step S1, select to be used to describe the key performance indicators of performance of the part interested of network.Then, at step S2, determine the configuration parameter of KPI based on it.At step S3, selection will be included in the quantity of the sub-district in the optimizing process,, selects the sub-district cluster that is.At step S4,, determine the currency of KPI according to each configuration parameter.After this, at step S5, determine the currency of KPI according to the quantity of the currency of KPI and sub-district, function assesses the cost.At step S6, the result of cost function, value and the configuration parameter of KPI are stored in the historical data base.
At step S7, at least a value in each configuration parameter is adjusted, obtain one group of new configuration parameter.Organize new configuration parameter according to this, determine new KPI value, then,,, recomputate the cost function according to new KPI value and the number of cells (changing) selected at step S3 at step S5 at step S4.At step S6, also the new result of cost function, new KPI and configuration parameter value are stored in the temporary storage.Subsequently, at step S8, will be based on newly/this new result of the cost function of the configuration parameter group adjusted compares with the previous result who is stored in the cost function in the historical data base, to determine after the adjustment configuration parameter, whether interested network performance improves.
If after adjusting configuration parameter, network performance improves,, the configuration parameter group of adjusting is used as permanent parameter then at step S9.Yet if after step S8 determines to adjust configuration parameter, network performance does not improve, and at step S9, will be used as permanent parameter in first set of configuration parameters that step S6 stores in the historical data base.
At step S10, whether the at interval interior at the fixed time network performance of check improves.When at the fixed time at interval in network performance when not improving, that is, even automatically adjust, KPI history does not improve yet, goes wrong at the automated procedure of optimization network performance step S12 informing network operator.Owing to obviously can not regulate many parameter values automatically, and adjusting can not be optimized network all the time automatically, so whether the operator can check this problem to be because hardware problem, and perhaps under the current network condition, whether cannot the Automatic Optimal network performance.Be in this case at network, network operator must manually be optimized network performance.
On the other hand, when at the fixed time at interval in network performance when improving, flow process jumps to step S7, at step S7, adjusts configuration parameter again, so that further optimize network performance.Then, this flow process will continue flow process described above.
In a second embodiment, not only select relevant KPI, and determine one group of QoS target, utilize one group of benchmark KPI to represent this group QoS at step S1.The automated procedure of optimizing network performance according to second embodiment and optimizing process basically identical according to first embodiment.Unique difference is when when step S5 assesses the cost function, to utilize the difference of KPI and benchmark KPI to replace the KPI value.
Therefore, the operator is provided with capacity requirement to the specified vol KPI that utilizes " ref " in the subindex to be expressed as KPI_C.Correspondingly, the operator is provided with quality requirement to specific KPI_Q.Then, utilize equation (1) calculated mass cost and capacity cost.
Figure C0282112000111
Utilize different weights factor alpha and β, with different cost function combinations or added together.By control or change weight coefficient α and β, can emphasize the cost and the general status of particular type.
Can think that its task is the combination that the mathematical formulae that is used to optimize network performance is used for according to which KPI determining near the zone that requires as far as possible the air interface configuration parameter.
Fig. 2 illustrates the example of KPI cost function f.In this example, be higher than linear the increasing of KPI value at cost of KPI_ref.
Equation (3) illustrates and will optimize, and promptly will be reduced to minimum total cost function.Utilize parameter W, can between capacity and quality requirement, realize balance.By adjusting configuration parameter (2), can be reduced to minimum.The KPI value also depends on service assignment, for example, obtains different cost setting and parameter setting according to service assignment.
KPI_C i=f (configuration parameter, service distribution)
KPI_Q j=f (configuration parameter, service distribution) (2)
The * capacity cost (3) of total cost=W* quality cost+(1-W)
For example, the factor that can influence optimizing process is: the price of service distribution (service mixes), traffic density, every kind of service etc.The final goal that total cost is reduced to hour comprises: Optimizing operation person's income, CAPEX and OPEX be reduced to minimum and attended operation person's favorable image.
According to following equation (4) to (8), the specific examples of the function T that can assess the cost OTAL COST:
(4) total cost=C (queuing ratio)+C (poor quality ratio)+C (call drop ratio)+C (blockage ratio)
Wherein
(5) C (queuing ratio)=0.05*Dev (the queuing ratio that queuing compare-is allowed)
(6) C (poor quality ratio)=0.2*Dev (the poor quality ratio that poor quality compare-is allowed)
(7) C (call drop ratio)=1*Dev (the call drop ratio that call drop compare-is allowed)
(8) C (blockage ratio)=0.10*Dev (blockage ratio-allow blockage ratio)
The optimization task is exactly that the TOM management level that all are different are combined, and should consider that wherein the measured value (quality status stamp and cost mark) of different layers uses this fact of different language.
When carrying out optimizing process in the NMS at network, support the operator to judge customer service and each SML.In order to realize this process, will comprise configuration and the deviation of the cost function measured at (PM) that lower floor carries out is converted to " language " on upper strata.This can realize by carrying out following content:
Execution is converted to (reflection) quality expection/target relevant with service from radio access network parameter (setting).In fact, this means, make configuration management relevant with performance management.That is, utilize one group of particular measurement value, the functional entity that monitoring has customized configuration.Utilize the cost function that adopts the measured value of determining to calculate the performance of this entity.
In fact, mean below and say that to delivering to the measured value (that is, sub-district, class of service etc.) the user class entity, big entity of the quality that can determine each user changes from statistics.Also utilize (respectively) weighted cost function, carry out this step.In addition, these conversions can be combined with cost function, with the end user's quality indication that realizes requiring.
1) the technology conversion (reflection) of end user's flow process rank (experiencing quality) from radio access network measured value (network performance) to service.
2) from assembling the technology conversion (reflection) that level (UMTS class of service) parameter is set to end user's flow process rank (experiencing quality) of service.
3) the technology conversion (reflection) from the measured value of each class of service of being provided with to end user's flow process rank (experiencing quality) of service.
And/or the composite function of class of service and process level information (parameter and setting) and cost function, with support parameterization and monitoring end user's GOS.
Fig. 5 illustrates the schematic diagram of the combination that is used to utilize network monitor function that reflection combines the different management level in the network and majorized function.
By network measure value, performance indicia PI and/or KPI and cost function are combined, can realize reflection from one deck to following one deck.
Can calculate the cost function of the grade of service GOS of user's impression, as equation (9) expression:
(9) GOS=C (service availability)+C (postponing and vibration)+C (quality)+C (call drop)+C (service accessibility)+C (equivalent bit rate or user throughput)
Postpone wherein to comprise that service access postpones and the queuing transmission delay.The non real-time quality is subjected to the influence of packets lost, radio link control RLC, packet data convergence protocol PDCP,, is subjected to the influence of error rate BER and BLER (block error rate) BLER that is.About real-time quality, if up link UL BLER (block error rate) BLER is significantly higher than target BLER, then this quality bad luck.Quality is subjected to down link DL to connect the influence that has a power failure in real time.The income of above-mentioned cost function comprises capacity requirement and service distribution.With kbp/ sub-district/MHz is that total throughout is measured by unit.
When the user 98% was satisfied, it was the throughput of unit that the spectrum efficiency of cost function equals with kbp/ sub-district/MHz.This means that professional accessibility and blocking probability are 2%.The equivalence bit rate is higher than 10% of load service data rate, and 98% user is not by call drop.Adopt the reason of this method to be, on tolerance, help being optimized according to GOS.
Must promptly, utilize the service of different parameters setting or other property control to carry out this reflection to all services that provided.
Although each conversion all makes precision reduce, from statistics, reflection is correct.Because the statistics level can be operated, so the optimum position of reflection function is at NMS.In addition, the NMS implementation procedure can also be handled radio network controller RNC-RNC (or other network element) borderline region.When carrying out this conversion, use the cost function of suggestion at every turn.Therefore in some cases, the service QoS target can cause the parameter setting to clash, and needs the cost function problem that manages conflict.This can realize by in cost function different units being provided with different weight coefficients.When entering network system, this theory is extremely important in different client's classification (silver, copper, gold etc.).
In addition, when being altered to last management level of TOM model, next key step is to calculate to the network optimization, SO service order and with the client area partite transport that Euro, dollar or pound are represented to calculate.In this stage, need interior bill and the pay imformation that inventory/the gathering subsystem provides of customer service layer of TOM.When the knowledge of the characteristic of utilizing client's basic condition/distribution and these distributions, can operator's commercial situation be optimized to the most useful direction according to cost function.It should be noted that to change client's priority and, will cause client's behavior to change, and therefore repeat Business Management Layer's optimization because of the QoS that commercial reason provides.
Have optimum performance in order to ensure cellular network, the operator preferentially makes flexible apparatus according to KPI of system (key performance indicators) and/or thus obtained cost function the QoS target is set.Can perhaps the QoS target be set to the sub-district cluster to each sub-district.Can according to because the blocked call of hardware resource, " soft " blocked call (interference-limited network), call drop are called out, quality is badly called out, for the repeating transmission number of times of packed data and delay, diversity switching probability, direct-cut operation success rate, load condition (up link UL or down link DL), to the packed data of circuit switched service etc., can calculate QoS.
Under the multi radio environment (GSM-WCDMA global system for mobile communications-Wideband Code Division Multiple Access (WCDMA)), importantly, for optimizing capacity, convergence and quality, can be to these two network creation resource pools.This requires that higher (KPI) layer is had all controlled function (quality manager), that is, utilize quality manager can realize according to optimizing process of the present invention.
Quality manager QM, that is, optimizing process provides the center monitors function, and the state of monitoring parameter value, compares the automatic recognition problem situation by the historical information that will be stored in the parameter value in the historical data base.For example, can be as far as possible little, as far as possible independently GERAN and UMTS terrestrial radio Access Network UTRAN are divided into automatic adjusting subsystem.By KPI weight coefficient is set, considers interdepending between the subsystem on the upper strata of quality manager to its each subsystem.
In another embodiment, according to user's group (as business users, free time use etc.), carry out optimizing process.
Can put it briefly the default value of current all parameter values of suggestion.Up to the present the community user network is still operator's task (attempting to consider many cell environments) one by one.Yet, adopt the method and/or the system that optimize network performance according to the present invention, it is inessential to make initial parameter be provided with.For example, when network brings into operation, can under the restriction of very " pine ", carry out access control and switching controls, thereby according to current QoS situation (being positioned at the KPI of the OSS of operate services system) with can regulate QoS target related parameter, that be provided with automatically, make all user access networks.In the parameter change new situation, after the promptly new KPI value, the historical data of it and KPI is compared, and if the change of QoS performance (the perhaps cost function of qos requirement) improve acceptance " test " parameter then.The length of historical data depends on the traffic carrying capacity (the sampling sum should be enough high) on the network.Importantly, the QoS cost function contains the projects in whole RRM and multi radio zone.
Currently at first key parameter (according to optimum capacity and quality) is set to " default " value, in most of the cases, should " default " value guarantees the network operation, but be optimum performance.Optimizing process according to the present invention changes to best operating point according to overall QoS automatically with being provided with of basic parameter.
The regulated quantity of configuration parameter can fixed increment or decrement.As a kind of selection, increment or decrement can be variablees.
A third embodiment in accordance with the invention is utilized cost function to concentrate and is optimized Internet resources, and the service quality (QoS) of calling hierarchy is provided.Cost C is the function of the variant KPI of network, for example:
C = Σ i = 1 n F i ( KPI i ) - - - ( 11 )
KPI wherein iBe i key performance indicators, and Fi is certain positive function that can be used for conversion, weighting and/or i KPI of convergent-divergent.By this cost function C is reduced to minimum, optimize network performance.Be counted as the variant network parameter W=(w of the optimum value of parameter by correct selection 1w 2..., w N), can realize least cost.The cost function method supposes that impliedly the value of KPI is the function of network parameter, that is:
KPI j＝KPI i(w 1；w 2；...，w N)j (12)
Therefore, cost function C still is the function of network parameter, and it can be rewritten as the direct function of parameter:
C = Σ i = 1 N g i ( w i , t ) - - - ( 13 )
G wherein iIt is certain function of t variation in time.
The 3rd embodiment relates in particular to a kind of simple, efficient algorithm that is used for above-mentioned cost function is reduced to minimum.Yet, under actual conditions, optimize this cost function and do not lead directly to.List its subject matter below:
1. in real network, there are many kinds of types of service, user distribution and loads.Network can not be controlled these factors, and these factors can be regarded as external noise source at random.Any optimized Algorithm all should be inresponsive to this random external influence.
2. because the differences such as load of different time are selected (that is function g of equation (13), so can improve the optimal parameter of any given network at any time 1Change in time).Any optimized Algorithm all should adapt to this variation of network best operating point, and can follow the tracks of these variations.
3. may not produce the network model that can under various different situations, be optimized.This means, do not know the function gi of equation (13).The replacement method that the 3rd embodiment adopts and this method be any model of hypothetical network not, but makes optimizing process only according to the network measure value.
The optimized Algorithm of using in cost function being reduced to minimum process is described, and can realizes this optimized Algorithm according to first principle.Study cost function C being reduced to minimum ordinary circumstance according to the parameter that is represented as w.If w 0It is the value that is used for C is reduced to minimum w.Utilization is calculated C (w about the taylor series expansion of any value of w 0) draw,
C ( w 0 ) = C ( w ) + ( w 0 - w ) * C ′ ( w ) + ( w 0 - w ) 2 2 C ′ ′ ( w ) - - - ( 14 )
Wherein C ' is the single order differential of C to W (w), and C " (w) be second-order differential.Because C (w 0) be the smallest point of C, about w 0, ask the differential of equation (14), and establish the result and equal 0, then draw,
w 0 = w - C ′ ( w ) C ′ ′ ( w ) - - - ( 15 )
It is classical Gauss-newton (Gauss-Newton) algorithm optimization algorithm of restraining fast.If C is the quadratic function of w, then a step converges to optimum w 0If C is not a quadratic function, then as long as C " (w) be positive all the time, just can guarantee to restrain.If it is not, then can make it for just, and equation (15) is decomposed into the normal gradients algorithm.Yet owing to the smallest point near C, so second approximation is more accurate, and convergence rate is faster.
Now, according to the WCDMA cost function, study this problem.As mentioned above owing to there is not the model of network, so be difficult to determine C ' (w) and C " (w) value, therefore be difficult to use equation (15).Yet, according to the 3rd embodiment, utilize the network measure value calculate C ' (w) and C " (w) value so that use equation (15).
Minor variations δ w＞0 to the value of parameter w is studied, to draw new parameter value w+ δ w, so the value of cost function can be approximately
C ( w + δw ) = C ( w ) + δw * C ′ ( w ) + δ w 2 2 C ′ ′ ( w ) - - - ( 16 )
Equally, can be in the hope of expression formula C (w-δ w):
C ( w - δw ) = C ( w ) - δw * C ′ ( w ) + δw 2 2 C ′ ′ ( w ) - - - ( 17 )
These two expression formulas are added together, and rearrange everyly, obtain C " (wadd), deduct these two and rearrange this expression formula then, produce C " (wadd) expression formula.
C ′ ( w ) = C ( w + δw ) - C ( w - δw ) 2 * δw - - - ( 18 )
C ′ ′ ( w ) = C ( w + δw ) + C ( w - δw ) - 2 C ( w ) δw 2 - - - ( 19 )
Therefore, by knowing C (w+ δ w) and C (w-δ w), can utilize equation (18) and (19) try to achieve C ' (w) and C " (w) value, perhaps their approximation.Next problem is how to calculate these values at any special time.This is to carry out according to following step:
1. at time t1, parameter value is w, and according to the network measure value of the correct KPI of time t1, utilizes equation (11) function C (w that assesses the cost; T1).
2. at time t1, the w value is changed to w+ δ w.
3. at time t2=t1+ δ t; δ t＞0 according to the network measure value of correct KPI, utilizes the assess the cost value of function of equation (11), to draw C (w+ δ w; T2).
4. at time t2, parameter w is changed to w-δ w.
5. at time t3=t2+ δ t,, utilize equation (11) function that assesses the cost, to draw C (w-δ w according to the network measure value of correct KPI; T3).
6. at time t3, utilize respectively equation (18), (19) draw C ' (w) and C " (w); and utilize measured value C (t1), C (t2), C (t3) to draw under the situation of C (w), C (w+ δ w) and C (w-δ w) respectively, utilize the new value of equation (15) calculating w.
These steps constitute the algorithm of one-period, and can repeat this cycle.To study about the noise fluctuations problem that occurs in the heterogeneous networks measured value discussed above now.Although be not have under the situation of noise item, draw this algorithm of cost function, also can be with this algorithm application in the noise cost function.
The effect that repeats above-mentioned algorithm is to make noise contributions and parameter convergence reach mean value.For example, Kushner, H.J.and Clark, D.S. (1978), Stochastic ApproximationMethods for Constrained and Unconstrained System, volume 26 ofApplied Mathematical Sciences, Springer-Verlag, New York, Heidelberg, the random optimization aspect of Berlin is scrutinized this algorithm.By w being increased at any time and reducing, also help to make noise contributions to reach mean value.In addition, in real network, because usually at δ t time cycle integrates measured value, so reduce noise contributions.For just optimised parameter, can select correct δ t, and in optimizing process, can change the value of δ t.
In addition, this algorithm how the variation of the optimum of tracking network be apparent.Even when parameter reaches optimum, this algorithm still causes this point to fluctuate slightly.As long as this optimum does not change, then near this optimum, the mean value that can make this fluctuation is 0.If this optimum value changes, then this algorithm still can be followed the tracks of this variation.
In first embodiment, adjust the configuration parameter value of KPI, recomputate the cost function, this cost function and cost function based on the preceding value of configuration parameter are compared, the value of newly adjusting is used as new configuration parameter, and, adjusts the value of configuration parameter in two steps according to second embodiment.At first, increase the value of configuration parameter, recomputate the cost function, the previous result of this result and cost function is compared according to new value.Then, reduce the value of configuration parameter, recomputate the cost function, the previous result of result and cost function is compared according to new value.Yet,, still can make the variation of configuration parameter small or be 0 even the result of twice previous cost function that changes does not improve.
As a kind of selection, in the 4th embodiment according to the 3rd embodiment, describe cost function and optimization thereof according to a particular network parameter, that is, the particular problem that obtains and optimize cost function according to key performance indicators (KPI), blocked call than (BKCR) is discussed now.
The WCDMA radio interface of 3g mobile network can carry voice service and the data, services with various data rates, business need and quality of service goals.In addition, to big macrocell, very large variation takes place in operational environment from indoor cell.Under various conditions, effectively use the limited frequency band requirement that various important networks and cell parameter carefully are set.The parameter setting is called radio net planning and optimization.Also established the WCDMA network in case set up, its operation and safeguard and mainly be monitoring performance characteristics and mass property and change parameter value in order to improve performance.The Automatic parameter control device is simple, but the performance indicia that it needs index to determine perhaps in this case, need inform clearly that performance is at improvement or the cost function that is worsening.
The target of optimizing is that the total amount with blocked call on the network is reduced to minimum.The special parameter of optimizing is that the soft-handoff parameters window adds (add) (wadd)." Soft handover gains ina fast power controlled WCDMA uplink " Sipila, K.; Jasberg, M.; Laiho-Steffens, J.; Wacker, A.Vehicular Technology Conference, 1999 IEEE 49 Th, Volume:2,1999 Page (s): 1594-1598, vol.2. discusses improving performance according to soft handover.Have been found that when determining to be reduced to minimum cost function, very careful.May produce the cost function that any parameter of selecting all is maintained fixed so that the wrong way combination is every.
By adjusting network parameter, can directly control some factors that influence network performance.For example, number of users, user distribution and type of service.The variation of these external parameters causes the cost function change.This means, be used for cost function is reduced to that minimum any optimized Algorithm all should robust, even and when having random fluctuation, still can realize convergence.Kushner and Clark, " Stochastic Approximation Methods forConstrained and Unconstrained System ", Springer-Verlag, New York, Heidelberg, 1978 stochastic approximation aspect is scrutinized this algorithm.At this, the relevant result who draws about these researchs of cost function optimization problem is even under noise circumstance, when repeating to make intrasystem noise fluctuations reach mean value, optimization problem can be regarded as noiseless optimization.At this, adopt this method, and obtain optimized Algorithm, to optimize definite cost function, in fact, utilize this optimized Algorithm that the noise cost function is reduced to minimum.
Second consideration of the optimized Algorithm of alternative costs function is to change the best operating point of cost function.Therefore, optimized Algorithm should be able to be followed the tracks of any variation of cost function state.By analyzing as can be seen, to compare with the linear convergence of normal gradients algorithm, the algorithm of suggestion has the quadratic convergence that cost function is reduced to minimum.
Quality manager is the logical block that is used to gather the statistics of various performance indicia in the radio network controller.In specified time interval, quality manager calculates these statistics, and this specified time interval is called qminterval.The more operable statistics of quality manager comprise:
● at each qminterval at interval, all connections of this sector of quality manager scrutiny are also checked call quality.In control cycle, quantity that the accumulative total poor quality is called out in two counters and calling sum.Utilize the ratio of Counter Value to obtain quality.
● the blocked call in during the previous qminterval and total ratio that inserts request.
● in formerly during the qminterval, the calling that call drop finishes and the ratio of terminated call sum.
At this, only use blockage ratio, yet, can expand this method and simulation process other statistics to comprise that quality manager returns.
Add according to handoff parameter, the window that is represented as wadd, research will be reduced to the ordinary circumstance of minimum cost function C (with reference to equation 11).If wadd 0Be that C is reduced to the value that minimum window adds.Utilization is calculated C (wadd about the taylor series expansion of wadd 0), draw:
C ( wadd 0 ) = C ( wadd ) + ( wadd 0 - wadd ) * C ′ ( wadd )
+ ( wadd 0 - wadd ) 2 2 C ′ ′ ( wadd ) - - - ( 20 )
Wherein C ' is the single order differential of C to wadd, and C " be second-order differential.Because C (wadd 0) be minimum, about wadd 0, ask the differential of equation (1), and establish the result and equal 0, then draw,
wadd 0 = wadd - C ′ ( wadd ) C ′ ′ ( wadd ) - - - ( 21 )
It is classical Gauss-newton (Gauss-Newton) algorithm of restraining fast.At wadd, must know C ' and C " value.How explanation is by network-evaluated these values now.Note that equation (20) and (21) corresponding to equation (14) and (15), equation (14) is relevant with the updating currently form of described equation with (15).
The research window adds variation from δ wadd to wadd+ δ wadd and the analog value of cost function C (wadd+ δ wadd).Equally, research window be added to the variation of wadd-δ wadd and the analog value C of cost function (wadd-δ wadd), then, utilize algebraic manipulation can with C ' (wadd) and C " (wadd) be expressed as:
C ′ ( wadd ) = C ( wadd + δwadd ) - C ( wadd - δwadd ) 2 * δwadd
C ′ ′ ( wadd ) = C ( wadd + δwadd ) + C ( wadd - δwadd ) - 2 * C ( wadd ) wadd 2 - - - ( 22 )
If C is a secondary, then therefore there is step convergence.If C is not a secondary, then the expression formula of equation (22) is similar to, but still has the quick convergence faster than normal gradients algorithm.More near wadd 0, just accurate more to being similar to of secondary.Under actual conditions, utilize following process to realize this algorithm:
1) at time t1, the value that window adds is wadd, and according to the network measure value, the value of the function C that assesses the cost (t1).At time t1, the value of wadd is changed to wadd+ δ wadd.
2) time t2 (＞t1), the value that window adds is wadd+ δ wadd, directly according to the network measure value, functional value C (t2) assesses the cost.At time t2, the value that window is added changes to wadd-δ wadd.
3) at time t3, the value that window adds is wadd-δ wadd, and directly according to the network measure value, functional value C (t3) assesses the cost.At time t3, utilize equation (20) and equation (21) and (22) to upgrade the value of wadd, wherein
C(wadd)＝C(t1)
C(wadd+δwadd)＝C(t2)
C(wadd-δwadd)＝C(t3) (23)
Repeat this process, thereby cost function is reduced to minimum.It should be noted that by alternately increasing or reducing the value that window adds, can realize two targets.As mentioned above, first target is to estimate C ' and C ".Second target is more no problem.Algorithmic statement is wherein studied to the situation of the minimum value of cost function.At this moment, the gradient of function is 0, and has finished optimization.Yet the optimum of network changes all the time, so cost function also changes all the time.As mentioned above, by replacing the value of wadd, utilize this algorithm can detect and follow the tracks of any this change.
The next stage of the 4th embodiment is that exploitation can utilize above-mentioned optimized Algorithm that it is reduced to minimum cost function.First kind the most generally speaking, can utilize equation (11) to describe cost function, wherein KPI iBe i KPI of network, and F iIt is certain function that will define.Every of cost function should be positive all the time, so cost function just is all the time.In addition, function F iShould not dominate the mode convergent-divergent KPI of cost function with this item in normal operation iFor example, for the KPI that in claimed range, works, can guarantee correct service quality iValue, F i(KPI i) should be in [0,1] scope.
In the 4th embodiment, only interested in the blocking rate.Purpose is that the blocked call of the function that will add as window is reduced to minimum than (BKCR).In this case, be used to be reduced to minimum explicit costs function be the simple of blockage ratio and.Yet because several reasons, in this case, the better selection of cost function is
C＝ulBKCR 2+dlBKCR 2 (24)
Wherein ulBKCR is a up link blocked call ratio, and dlBKCR is a down link blocked call ratio.Yet in any real network, for the acceptable grade of service, the blocked call ratio must be lower than particular value, for example, and 5%.Can further adjust this cost function, so that plugging value is significantly higher than this value.For example,
C＝f(ulBKCR) 2+f(dlBKCR) 2 (25)
Wherein
f(x)＝exp(x*12)-1 (26)
Select this function to mean, the up link for 5% is blocked, value=1.0 of f (ulBKCR).For the value that is lower than 5%, this function almost is linear.Yet for greater than 5% value, this function increases with index.When having many in cost function, the purposes of function f is more obvious.Another key property of function f is that it is continuously a differentiation function, therefore when asking the derivative of the cost function that is used for optimized Algorithm, does not have problems.
In the 5th embodiment, can expand the algorithm of the 3rd embodiment, in the time that several network parameter will be optimized, cost function is reduced to minimum.By being the problem of the parameter of the 3rd embodiment, realize the situation of a plurality of parameters with a plurality of parameter predigestings.To N the parameter w that will optimize iVector W study,
W＝(w 1；w 2，...；w N) (27)
Initial value to these parameters of beginning to be optimized from it is studied.Can select this initial value at random,
W 0＝(w 0；1；w 0；2；...；w 0；N) (28)
To contain initial value W 0N dimension parameter space in delegation be defined as:
L 0＝W 0+λ n 0 (29)
N n dimensional vector n n 0Be unit vector, this unit vector at first has any direction again, and factor λ is a scalar variable.This theory is to follow L 0Cost function is reduced to minimum.This is equivalent to determine the optimum value of λ, and λ is a scalar value, therefore the algorithm that can adopt previous trifle to describe.Suppose that optimum value is λ 0, the equation below then utilizing obtains the new value of W:
W 1＝W 0+λ 0n 0 (30)
With another row L 1Be defined as:
L 1＝W 1+λ n 1 (31)
N wherein 1Be n 0Conjugate direction.Again, utilize the algorithm of the 3rd embodiment, along the row of redetermination, the repeated optimization cost function.In theory, in noise free system, must be along N conjugate direction (n 0, n 1..., n N-1), repeat the optimization that follows for N time.For noisy cost function,, must repeat more a plurality of cycles in order to remove noise contributions.There are many well-known methods to produce conjugate direction in each step of optimizing process.Compare with independent optimization network parameter, optimize several network parameters simultaneously, can better cost function be reduced to minimum.
Particularly when this algorithm being expanded to more higher-dimension, adopt the further advantage of this algorithm to be, small by the fluctuation that makes each parameter, can break away from the local minimum value of cost function.
According to the optimization method of the first, second, third or the 4th embodiment not only based on latter two result of cost function, and based on the previous history of cost function measured value.Therefore, at time t, the variation that influences parameter can be cost function and different time t, t-1, t-2, t-3 ... the function of each parameter value of t-n.Therefore, can upgrade each parameter, perhaps be the function of previous measured value with each parametric representation.

Claims (14)

1. method that is used to optimize network performance, the method comprising the steps of:
Determine first parameter that relevant key performance indicators and described key performance indicators relied on of entity in the network,
Select the similar solid of certain quantity,
According to the key performance indicators of determining and the entity of selected quantity, calculate first cost function, with the first value assessment network performance according to described first parameter, the currency of described first parameter of the described first value representative of wherein said first parameter,
Adjust the value of described first parameter, thereby produce second value of described first parameter,
Key performance indicators according to determining according to described second value of described first parameter recomputates described first cost function, with the assessment network performance,
To compare according to the result of described first cost function of described first value of described first parameter and result, whether improve with definite network performance according to described first cost function of described second value of described first parameter,
If the network performance according to described second value of described first parameter improves, described second value that then adopts described first parameter is as permanent parameter.
2. method according to claim 1,
Wherein in described first cost function, utilize different weight coefficients that corresponding definite key performance indicators is weighted.
3. method according to claim 1 and 2,
The fiducial value of key performance indicators wherein is set, and determines the difference between the corresponding fiducial value of current key performance indicators, and this difference is used as the interior element of described first cost function with it.
4. method according to claim 1,
Wherein said first cost function comprises second cost function of the quality requirement in the expression network and the 3rd cost function of the capacity requirement in the expression network, wherein utilize described second cost function of the second weight coefficient weighting, and utilize described the 3rd cost function of the 3rd weight coefficient weighting.
5. method according to claim 4,
Wherein said the 3rd weight coefficient equals 1 and subtracts described second weight coefficient.
6. method according to claim 4,
The wherein said second and the 3rd cost function comprises the key performance indicators of determining of the entity of each selection, as element.
7. method according to claim 1,
Wherein utilize sub-district or user in the network to organize the interior described entity of the described network of expression.
8. method according to claim 1,
Wherein repeat to be used to optimize each step of network performance.
9. method according to claim 1, the method comprising the steps of:
In order to set up historical data base, the value of key performance indicators is stored together with the corresponding result of corresponding first parameter and first cost function.
10. method according to claim 9, wherein comparison step comprises step:
The result of described first cost function is compared with the previous result who is stored in first cost function in the described historical data base, and in definite interval at the fixed time, whether network performance improves, and
If in described predetermined time interval, network performance does not improve, then give notice.
11. method according to claim 8,
Wherein, carry out the described step of the value of adjusting described first parameter by alternately increasing and reduce the value of described first parameter.
12. method according to claim 11,
Wherein before carrying out described employing step, carry out the described step that increases and reduce the described value of described first parameter continuously.
13. method according to claim 1,
The wherein measurement of the low management level from network and/or configuration obtains service and/or the indication of each quality of services for users.
14. a system that is used to optimize network performance, this system comprises:
A) be used for determining the device of first parameter that relevant key performance indicators and described key performance indicators relied on of entity in the network,
B) be used to select the device of at least one similar solid,
C) be used for according to described definite key performance indicators and at least one entity of described selection, calculate first cost function, to assess the device of network performance according to first value of described first parameter, the currency of described first parameter of the described first value representative of wherein said first parameter
D) be used to adjust described first value of described first parameter, thereby obtain the device of second value of described first parameter,
E) be used for recomputating described first cost function according to according to the definite described relevant key performance indicators of described second value of described first parameter, with the device of assessment network performance,
F) be used for and will compare according to the result of described first cost function of described first value of described first parameter and result according to described first cost function of described second value of described first parameter, with definite network performance improved device whether,
G) be used for when the network performance according to described second value of described first parameter improves, adopting the device of described second value of described first parameter as permanent parameter.
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Denomination of invention: Method and system for optimising the performance of a network

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