Abstract:
In LTE, there is no control node that collects Performance Management (PM) data from base stations, like a Base Station Controller (BSC) or Radio Network Controller (RNC) does for 2G/3G systems. Instead, an Operating Support System (OSS) has to collect PM data directly from eNodeBs, thereby causing scalability issues. A method of improved PM for LTE networks uses the statistical counters defined in the eNodeB and counters created from elementary events and parameters of events. Specific counters or user-defined counters can be defined that are, for example, not traditionally implemented in the nodes, or that use events from additional Network Elements (NEs). The counter files and events are collected by an observation gateway or directly by the PM application, and are monitored in different time scales. The counters are also aggregated for different time periods, thereby providing scalability and time-based statistics for the counter values.

Description:
RELATED APPLICATIONS 
       [0001]    This application is a continuation of U.S. application Ser. No. 13/509,077, filed 4 Sep. 2012, which was the National Stage of International Application No. PCT/EP2009/066806, filed 10 Dec. 2009, the disclosures of each of which are incorporated herein by reference in their entirety. 
     
    
     TECHNICAL FIELD 
       [0002]    The present invention relates to telecommunications and, in particular, to performance management in mobile telecommunications systems for monitoring and optimizing system operation. 
       BACKGROUND 
       [0003]    Performance Management (PM) functions, in a mobile telecommunications system, are used for monitoring, troubleshooting and optimization of the mobile telecommunications system. The PM functions are based on events and counters generated by the several system elements of the mobile telecommunications system, among which are radio access units, Base Stations (BS), radio network controllers, and other system nodes and servers. 
         [0004]    Events are used to monitor and investigate elementary system operation. Relevant information of the operation of the system can be obtained from a long time observation of the events data. 
         [0005]    Counters are used to obtain aggregate or statistical information of the system. Counters are implemented in the various system elements but can also be created from events and event parameters. There is a continuously increasing number of predefined counters that are recorded in the system elements. 
         [0006]    Examples of recording events can be found in the General Performance Event Handler (GPEH) and User Equipment Traffic Recording (UETR) functions of system elements. An example for collecting statistical counters is the STATS function of system elements in, for example, third generation (3G) and Long Term Evolution (LTE) mobile telecommunications systems. Note that events data and counter values generated by a plurality of system elements may be collected by a common server or gateway instead of by the system elements themselves. 
         [0007]    The events data and counter values may be forwarded directly, in real-time, to a management server or gateway that is part of an Operating Support System (OSS) by using a streaming application, for example. However, the events and counters may also be collected in files for a set period of time called the Result Output Period (ROP) before forwarding thereof to the OSS. ROP files are retrieved periodically from the system elements and processed in the OSS. Both real-time events data and counter values, as well as ROP files, may be available for processing by the OSS. 
         [0008]    An OSS implements several types of PM functions such as traffic monitoring, troubleshooting, radio and transport network optimization. From the processed events and counters Key Performance Indicators (KPIs) can be driven that are used for monitoring, troubleshooting and planning purposes. KPIs are used for high level monitoring and business planning functions. These functions are not necessarily part of the OSS. 
         [0009]    An OSS may also include applications for user defined counters to be created from events or event combinations, which provides an extended observation possibility for telecommunications systems. Besides the above, the events data and counter values may be used by other applications as well. 
         [0010]    LTE networks, for example, implement a lot of auto-configuration functions and use default configurations which provide fast installation and stable operation in the initial phase of a systems setup. However, monitoring of the overall operation of the large number of system elements requires a centralized management system. Exceptional conditions and operations should be observed by a performance monitoring OSS. Performance monitoring tools and functions are also needed in order to optimize the operation of LTE. 
         [0011]    A problem of LTE performance monitoring is the plural numbers of nodes and cells, e.g., femtocells that have to be monitored. These nodes, also called LTE eNodeB, generate larger numbers of events and counters that have to be processed compared to previous mobile Radio Access Network (RAN) systems, such as GSM RAN, for example. 
         [0012]    Scalability issues occur if the OSS has to communicate and collect events data and counter values directly for large numbers of system elements, such as the LTE eNodeBs. This is particularly true in the absence of (intermediate) control nodes, which are also used for collecting and pre-processing PM data from the system elements in GSM and WCDMA RAN systems. 
         [0013]    Another problem with newly-deployed systems and system technology is the lack of reference data for the different parameters to derive KPIs, for example. Current PM monitoring functions need a lot of prior knowledge of the system, or decent operational experience, which means more expensive implementations and increased operating expenses. This is in particular a problem for small system operators which are not able to invest in the implementation of such tools and do not have large experienced staff for evaluation and system operation. 
       SUMMARY 
       [0014]    It is an object of the present invention to provide performance management functions for a mobile telecommunications system that can be implemented in a central operating support system or as a separate performance management tool, and adapted to collect and process plural events data and counter values generated by plural system elements. 
         [0015]    It is another object of the present invention to provide an expert tool for automatically extracting monitoring, troubleshooting and optimization information from the performance management functions of the mobile telecommunications system, for use by a systems operator. 
         [0016]    A first aspect comprises a method of system Performance Management (PM) by an Operating Support System (OSS) of a mobile telecommunications system. The mobile telecommunications system comprising a plurality of nodes and radio access units servicing a plurality of cells generating a plurality of operational events data and counter values measured periodically for a first Result Output Period (ROP). The method comprising the steps of: collecting events data and counter values originating from the nodes and radio access units; aggregating the collected counter values periodically for a second and further ROPs having a duration longer than the first ROP, wherein the first and second and further ROPs are set corresponding to a specific operational event and counter; creating further counter values from the collected events data periodically for the second and further ROPs; processing the aggregated and further counter values corresponding to the originating nodes, radio access units and ROP; and analyzing the processed counter values for providing system operational performance indicia in different time scales. 
         [0017]    The aggregation of counter values for a second and further result output periods, i.e., for a second, third, fourth, etc. result output period, provides scalability and adequate time-based statistics for the counters. For adequately identifying problems that occur on different time scales, the aggregation periods are set corresponding to specific events and counters. That is, events and counters that relate to short term problems are aggregated for a correspondingly short result output period and events and counters that relate to long term problems are aggregated for a correspondingly long result output period, for example. Note that some events and counters should be observed and aggregated both in short and long time periods. 
         [0018]    Events data, which may include different parameters, are turned into further counter values that are not provided for by the counter values that are directly collected from the system elements, i.e., the nodes and radio access units of the mobile communications system. By creating such further counters for specific events periodically, corresponding to a respective set aggregation period or time scale for the specific events, self-consistency of the performance data available as events and counters in the system is maintained such that the aggregated and further counter values may be commonly processed in relation to the different system elements for providing performance management information in accordance with the time scale relevant for the specific information. 
         [0019]    In this manner, larger numbers of events data and counter values compared to present performance management can be adequately handled and analyzed, such as the large number of performance management data generated in LTE, for example. 
         [0020]    The events and counters are monitored and aggregated for different time periods. In a further example, for specific operational events and counters, different second and further ROPs are set corresponding to time periods related to usage of the mobile telecommunications system. The different second and further ROPs correspond to natural time periods of human life and behavior in relation to periods of communication traffic change and traffic load of the telecommunications system, such as five minutes, fifteen minutes, an hour, a day, a week, a month or a year. 
         [0021]    The size of the collected events data and counter values may be as large as a few MBytes, which does not allow storing them for a long time. The aggregation method makes it possible to store the information in an aggregated way for a longer time. Accordingly, in a further example, the collected events data and counter values are stored for a period of time being a multiple of the respective second and further ROPs. For example, data aggregated for a period of 5 or 15 minutes need only to be stored for a few hours. Data aggregated for 1 hour can be dropped after a few days, etc. It will be appreciated that this is a significant advantage in the efficient use of and the provision of storage capacity. 
         [0022]    Processing of the aggregated and further counter values corresponding to the originating nodes, radio access units and ROP comprises, among other things, parsing of the aggregated and further counter values and extracting counter values for each counter per cell and node and storing them. 
         [0023]    By creating counter value distributions for the extracted counter values, an adequate spatial statistics base is provided, serving as reference data for future analysis of the events and counters. The spatial statistics may be created for extracted counter values after filtering thereof with respect to set filter criteria relating to the cells and nodes of the telecommunications system. The filter criteria in fact specify the scope of monitoring and are also used to decrease the amount of data to be processed. Input filtering for (a group of) cells, for example, enables different analysis for rural and urban areas, for example. Counters that are not of interest can be excluded from the analysis using the input filters as well. Filters can be added based on prior knowledge of the system or based on operational experience. 
         [0024]    In an example, at least an average value and a standard deviation value of the counter value distributions of the thus created spatial statistics are calculated, among other things, to identify exceptional counter values. Outlier cells and nodes are identified, for example, by sorting counter values for different cells and nodes. By mapping cause patterns with the identified outlier cells and nodes, system operational performance indicia for the first and second and further ROPs are provided. By correlating the spatial statistics with time-based statistics, more detailed results are derived. 
         [0025]    The sensitivity of the OSS is tuned by settable factors f and g, such that outlier cells and nodes are automatically identified if a deviation from the average is larger than f times the standard deviation value and if a number of outlier counters for a same cell is larger than g. 
         [0026]    That is, typical error cases can be identified, for monitoring, troubleshooting and optimization of the mobile telecommunications system. The analysis is performed for different time scales, which allows for identifying problems that may be visible in a short or in a long time scale, for example. 
         [0027]    Another aspect comprises an Operating Support System (OSS) for providing Performance Management (PM) of a mobile telecommunications system comprising a plurality of nodes and radio access units for servicing a plurality of cells. The nodes and radio access units are arranged for generating a plurality of operational events data and counter values measured periodically for a first Result Output Period (ROP). The OSS comprising: a collecting unit, arranged for collecting events data and counter values originating from the nodes and radio access units; an aggregating unit, arranged for aggregating the collected counter values periodically for a second and further ROPs having a duration longer than the first ROP, wherein the first and second and further ROPs are set in relation to a specific operational event and counter; a counter creating unit, arranged for creating counter values from the collected events data periodically for the second and further ROPs; and a processing and analyzing unit, for processing the aggregated and further counter values in relation to the originating nodes, radio access units and ROP, and for analyzing the processed counter values for providing system operational performance indicia in different time scales, including the first and second and further ROPs. 
         [0028]    The OSS may be comprised by software, hardware or a combination of software and hardware in a single node of a telecommunications system, by a plurality of collaborating nodes and even by a server, gateway or computer processing unit external to the telecommunications system. 
         [0029]    In an embodiment, the OSS comprises a unit for setting different second and further ROPs, wherein the aggregating unit and counter creating unit are arranged for operating with set different second and further ROPs. 
         [0030]    In a further embodiment, the processing and analyzing unit comprises a parser arranged for parsing the aggregated and further counter values for extracting counter values for each counter per cell and node, a storage unit arranged for storing the extracted counter values, a filter unit arranged for filtering extracted counter values with respect to set filter criteria relating to the cells and nodes, and a spatial statistics unit arranged for calculating spatial statistics comprising counter value distributions including an average value and a standard deviation value of the counter value distributions. 
         [0031]    For analyzing spatial statistics for performance management purposes, in another embodiment the processing and analyzing unit further comprises a sorter unit, arranged for sorting counter values for different cells and nodes and for identifying outlier cells and nodes based on the calculated average value and standard deviation value of the sorted counter values. 
         [0032]    The processing and analyzing unit may further comprises a mapping unit, arranged for mapping cause patterns with the identified outlier cells and nodes, and a presentation unit for presenting system operational performance indicia based on this mapping. 
         [0033]    The above-mentioned and other features and advantages of the invention will be best understood from the following description referring to the attached drawings. In the drawings, like reference numerals denote identical parts or parts performing an identical or comparable function or operation. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0034]      FIG. 1  shows, in a very schematic and illustrative manner, a basic architecture of a mobile telecommunications system comprising an Operating Support System (OSS). 
           [0035]      FIG. 2  shows, in a schematic and illustrative manner, an example of an OSS in accordance with the present invention. 
           [0036]      FIG. 3  shows, in a schematic and illustrative manner, an example of the BSO of  FIG. 2 , in accordance with the present invention. 
           [0037]      FIG. 4  illustrates an example of the method according to the invention. 
       
    
    
     DETAILED DESCRIPTION 
       [0038]    The present invention will now be illustrated by way of example and not by way of limitation in a Radio Access Network (RAN)  2  of a mobile communications system  1 , such as a Global System for Mobile communications (GSM), a General Packet Radio Service (GPRS), Wideband Code Division Multiple Access (WCDMA), Time Division-Synchronous Code Division Multiple Access (TD-SCDMA) RAN, or a Long Term Evolution (LTE) mobile telecommunications system supporting communication with mobile User Equipment (UE)  3  connecting via a wireless radio link  4  and radio access units  5  to the RAN  2 . The RAN  2  comprises several node and servers arranged as Radio Network Controller (RNC)  6  for supporting the communication with switching nodes, such as a Mobile Switching Center (MSC)  8  and/or servers of an Internet Protocol (IP) Multimedia Subsystem (IMS)  9  which operatively connect  10  to the RAN  2 . 
         [0039]    The radio access units  5 , called Radio Base Stations (RBSs) in a GSM system, for example, and eNodeBs in an LTE communications system, for example, provide service to UEs  3  in a restricted geographical area, called a cell  15 , and connect operatively  7  to the RAN  2  for exchanging calls and data between the different UE  3  and other subscribers and users of the telecommunications system  1 . 
         [0040]    For the purpose of the present invention, the manner of call handling and data exchange between the several subscribers and users of the telecommunications system is not of importance, such that this will not be further detailed herein. Further, this is knowledge which is fully within the reach of the person skilled in the art. 
         [0041]    For the present invention it is important that several radio access units  5  and RNCs  6  of the telecommunications system  1 , and in particular the RAN  2 , are communicatively connected to a central management or Operating Support System (OSS)  11  of the telecommunications system  1 , illustratively indicated by dashed lines  12 . The connections  12  may, for example, be streaming connections, for the real-time streaming of events data and counter values to the OSS  11 . 
         [0042]    In the present description and claims, the radio access units  5  and RNCs  6  are also termed system elements (SEs). The SEs  5 ,  6  generate internal and external events about their operation. Each event may include one or more parameters that are linked to the event. In the SEs  5 ,  6  several counters are implemented to obtain aggregate or statistical information of the system. In  FIG. 1 , these events and counters are schematically indicated by reference numerals  13  and  14 , respectively. The counter values are measured by the SEs  5 ,  6  periodically for a time period, the first Result Output Period (ROP), and the result is stored in ROP files. A basic first ROP is typically 5-15 minutes and is set corresponding to a specific counter. Note that the RNC nodes  6  may collect and store the events and most of the counters related to the controlled radio access units  5 . The ROP files and/or the events from the SEs  5 ,  6  are forwarded to the OSS  11 . 
         [0043]      FIG. 2  shows schematically an example of an OSS  20  in accordance with the present invention. The OSS  20  includes several Performance Management (PM) functions performed by a data collecting unit, called a Performance Management Gateway (PMG)  21 , a counter creating unit, called Event Based Applications (EBA)  22 , an aggregating unit, called Counter Aggregation (CA)  23 , and a processing and analyzing unit, called Bulk Statistical Observation (BSO)  24 . The OSS  20  further comprises a unit  25  for setting different second and further ROPs, i.e. third, fourth, fifth, etc. ROPs, for use by the EBA  22  and the CA  23 . 
         [0044]    The events  13  generated by the several radio access units  5  and RNC  6  as shown in  FIG. 1  are either forwarded to the PMG  21  or to the other PM functions  22 ,  23 ,  24  of the OSS  20 . 
         [0045]    The counter values  14  and basic first ROP are collected by the PMG  21  and are a primary input of the CA  23 . Here the input counter values and ROP files are stored for a time period and periodically aggregated for a second and further ROPs having a duration longer than the first ROP. In the unit  25 , the ROP are set in relation to specific operational events and counters. The second and further ROPs are created for natural time periods, which correspond to the periods of human life and behavior in relation to the use of the telecommunications system  1 , for example ROPs of 1 hour, 1 day, 1 week, 1 month, 1 year. Basic ROPs of 5 or 15 minutes are, for example, aggregated for 1 hour. The 1 hour ROPs are aggregated for 1 day periods. The 1 day ROPs are aggregated for 1 week periods, etc. It is assumed that these periods correspond to the periodic change of the traffic volume and composition, i.e., speech, multimedia data, internet related data, metering data, etc. The CA  23  provides several ROP files as input to the BSO  24 . 
         [0046]    The EBA function  22  of the OSS  20  creates counters from the events and parameters included in the events collected by the PMG  21 , for the same time periods, i.e., the second and further ROPs as in the CA  23 . In the EBA function  22  user defined counters can be specified, that are not implemented in the SEs  6 ,  7 , for example. The EBA function  22  can also be used to define counters or multiple events from different SEs  6 ,  7 . The thus created counter values are input to the BSO  24 . 
         [0047]    The BSO operational units and functions are displayed in  FIG. 3 . BSO  24  receives the first or basic ROP files  29  and the aggregated or second and further ROPs files  26 ,  27 ,  28 , as input. A parser unit  30  parses the counter files  26 ,  27 ,  28 ,  29  and extracts the counter values for each activated counter per cell  15 . The data are stored in a storage unit  31 , such as a RAM or a database. The data are stored in the storage unit  31  in order make the data available for historical analysis. This makes it possible, for example, to compare actual collected and processed events and counter data with similar data of previous time periods. Depending on the size of the data and available DB capacity 10-100 ROP files are stored per accumulation periods ROP. 
         [0048]    The data are further applied to a filter unit  32 , thereby specifying the scope of monitoring and for decreasing the amount of data to be processed. The filtering can be performed for a group or groups of cells  15 , to prepare different analysis for rural and urban areas, for example. Counters that are not of interested for a particular analysis should be excluded from such analysis for which the filter unit  32  can be applied as well. By default all cells and parameters are included. Filters can be added based on prior knowledge of the system or based on operation experience, for example. 
         [0049]    For each counter that passes the filter unit  32 , spatial statistics are created by a spatial statistics unit  33 , which means that a statistical distribution of the counter values is created for the cells  15 , or SEs  5 ,  6 . From these statistics, the average and standard deviation are calculated for the different time scales, i.e., the first and second and further ROPs. Other quantities that characterize the distribution may also be obtained. 
         [0050]    The counter values for the different cells are sorted per counter and outlier cells are identified by a sorter unit  34 . The counter value is an outlier, for example, if the deviation from the average is larger than a factor f times the standard deviation value, where f=3 or another value to be set. Accordingly the value of f is used to control the number of outliers. 
         [0051]    Another factor g to be set is the number of outlier counters for the same cell. For example, if the value of g&gt;5 there are more than 5 parameters that have an extraordinary value and they should belong to the same root cause or root causes. 
         [0052]    The parameters f and g are used to tune the sensitivity of the OSS system  20 . The actual values of the factors f and g may depend from the type and size of the mobile telecommunications system and/or the operator, for example. 
         [0053]    Next, cause patterns are fitted to the outlying counters by a mapping unit  35 , which helps the operator to identify the problem and the root cause of the problem. If, for example, call drop or data packet loss for a certain service is high in a particular cell  15  and at the same time the signal strength level is relatively low, it can be concluded that the drop or loss is due to the weak signal. Predefined cause patterns can be provided with the mapping function, however the mapping function and unit  35  provide the possibility to add new patterns by the operator based on operation experience. 
         [0054]    The analysis is done for different time scales, i.e., different ROP, as illustrated by the several rows of arrows corresponding to a particular ROP file  26 ,  27 ,  28 ,  29 . This makes it possible to observe different types of problems. A problem may be identified only at smaller time scale. On the other hand in short time scale there can be many outliers that make it difficult to identify the problem. Long scale observation may identify problems that are due to long time traffic increase, aging of connectors, devices, etc., that are not visible in short time scale. This makes it possible to investigate the history of the values of different parameters. 
         [0055]    This analysis assumes that the majority of the cells and SEs operate well. This is also a necessary criterion for a self-configuration system like LTE, where automating functions ensure the proper settings and operation. The results may be presented in different ways. For each time scale the cells that have outlying counters are presented and listed. In another view the relevant counters can be selected, or they are selected automatically as the counters having outlying values and the corresponding cells are indicated. These performance indicia are presented by the presentation unit  36  of the processing and analyzing unit  24 . 
         [0056]      FIG. 4  illustrates in a flow chart type diagram the steps of an example of performing the method of the invention, with reference to the a telecommunications system as outlined by  FIG. 1  and measured periodically for a first Result Output Period (ROP). 
         [0057]    In a first step  40 , collecting events data and counter values originating from said nodes  6  and radio access units  5  are collected. In a second step  41 , the collected counter values are periodically aggregated for a second and further ROPs having a duration longer than the first ROP, wherein the first and second and further ROPs are set corresponding to a specific operational event and counter. In a further step  42  counter values are created periodically for the second and further ROPs from the collected  40  events data. By processing the aggregated and further counter values in step  43  corresponding to the originating nodes  6 , radio access units  5  and ROP, and analyzing  44  the processed counter values, system operational performance indicia in different time scales are provided  44 . 
         [0058]    Further examples of the method are elucidated above with reference to the  FIGS. 2 and 3 . 
         [0059]    With the present invention, an operator becomes a good overview of the system and network operation, which includes all available counters. It can be used for automatic monitoring and trouble-shooting as well. It provides a centralized performance monitoring method, i.e., operators can avoid complex drive tests, etc., in order to obtain a full picture of the system operation. The method and OSS system provided are able to monitor all available counters in a mobile communications system, as well as user-defined counters. 
         [0060]    The invention makes use of the self-consistency of data instead of predefined thresholds and is self-adapting to different system deployment scenarios, traffic conditions, etc. There is no need for specific system or network knowledge to use the present performance management tool. On the other hand it has the flexibility to add such knowledge to processing and analyzing unit BSO  24 , for example, if required. 
         [0061]    The result is analyzed in different time scales, therefore it is possible to notice errors that occur slowly, e.g., due to oxidation of connectors, as well as short temporary problems like large traffic bursts, packet delays, variations in packet delays, etc. 
         [0062]    The present invention is not limited to the embodiments as disclosed above, and can be modified and enhanced by those skilled in the art beyond the scope of the present invention as disclosed in the appended claims without having to apply inventive skills.