WO2025104373A1

WO2025104373A1 - Contribution-based performance analysis of a communication network

Info

Publication number: WO2025104373A1
Application number: PCT/FI2024/050609
Authority: WO
Inventors: Riku ERTIMO; Eero MÄKI-ESKO; Matti Karjalainen; Mika Ahonen; Juho POUTANEN
Original assignee: Elisa Oyj
Current assignee: Elisa Oyj
Priority date: 2023-11-16
Filing date: 2024-11-13
Publication date: 2025-05-22
Anticipated expiration: 2026-05-16
Also published as: FI20236274A1

Abstract

A computer-implemented method may comprise: Acquiring data associated with a communication network comprising a plurality of cells. Calculating, per subset of cells within the plurality of cells and utilizing the data acquired, a value for a cell-specific key performance indicator. Calculating, utilizing the data acquired, a value for a network key performance indicator, wherein the network key performance indicator is inherently linked to the cell-specific key performance indicator. Calculating, per subset of cells within the plurality of cells and utilizing the data acquired, the network key performance indicator value calculated, and the cell-specific key performance indicator value calculated for said subset of cells, a contribution value associated with said subset of cells. Generating, utilizing the contribution values calculated for the subsets of cells, an output for controlling the communication network, wherein the output indicates a presence of one or more subsets of cells from within the plurality of cells.

Description

Some example embodiments relate to a contribution-based performance analysis of a communication network.

BACKGROUND

A wireless communication network may be analysed and optimized in many different ways, e.g., based on key performance indicators (KPI) of the network. One example of such a KPI is the dropped call rate (DCR). KPI monitoring and analysis can be used for, e.g., identifying problems in the network, finding network elements where optimization activities should be targeted, or monitoring performance after implementing changes in the network.

Identifying network elements that have an impact on the performance of the network may be a non-straightforward and time-consuming task if based on comparing individual KPI values. Therefore, there is a need for enabling an interpretable solution for analysing the performance of the network.

SUMMARY

This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.

Example embodiments of the present disclosure enable a contributionbased analysis of performance of a communication network comprising a plurality of cells. This benefit may be achieved by the features of the independent claims. Further example embodiments are provided in the dependent claims, the detailed description, and the drawings. According to a first aspect, a computer-implemented method is disclosed. The method may comprise: Acquiring data associated with a communication network comprising a plurality of cells. Calculating, per subset of cells within the plurality of cells and utilizing the data acquired, a value for a cell-specific key performance indicator. Calculating, utilizing the data acquired, a value for a network key performance indicator, wherein the network key performance indicator is inherently associated with the cell-specific key performance indicator. Calculating, per subset of cells within the plurality of cells and utilizing the data acquired, the network key performance indicator value calculated, and the cell-specific key performance indicator value calculated for said subset of cells, a contribution value associated with said subset of cells. Generating, utilizing the contribution values calculated for the subsets of cells, an output for controlling the communication network, wherein the output may indicate a presence of one or more subsets of cells from within the plurality of cells. With such a method, the plurality of cells encompassed in the communication network may be analysed based on their contributions on the performance of the communication network.

According to an example embodiment of the first aspect, the one or more subsets of cells may be associated with largest absolute values within the contribution values calculated. With such a method, a list of subsets of cells with highest impact on performance may be made automatically available.

According to an example embodiment of the first aspect, the calculating the cell-specific key performance indicator value for a subset of cells within the plurality of cells may comprise calculating a ratio of a first numerator value and a first denominator value associated with said subset of cells. The calculating the network key performance indicator value may comprise calculating a ratio of a second numerator value and a second denominator value associated with the communication network. The calculating the contribution value for said subset of cells may comprise decreasing the network key performance indicator value from the cell-specific key performance indicator value, multiplying the result with the first denominator value, and dividing the result with the second denominator value. With such a method, contribution-based analysis may be utilized on a key performance indicator that may be defined as a ratio.

According to an example embodiment of the first aspect, the first numerator value may comprise a first value for a first parameter and the first denominator value may comprise a first value for a second parameter. The first value for the first parameter and the first value for the second parameter may be associated with said subset of cells. The second numerator value may comprise a second value for the first parameter and the second denominator value may comprise a second value for the second parameter. The second value for the first parameter and the second value for the second parameter may be associated with the communication network. With such a method, contribution-based analysis may be utilized on a key performance indicator that may be defined as a ratio of the first parameter and the second parameter.

According to an example embodiment of the first aspect, the calculating the network key performance indicator value may comprise adding together the cell-specific key performance indicator values calculated for the subsets of cells and dividing the result by a number of the subsets of cells within the plurality of cells. The calculating the contribution value for a subset of cells within the plurality of cells may comprise decreasing the network key performance indicator value from the cell-specific key performance indicator value and dividing the result by the number of the subsets of cells within the plurality of cells. With such a method, calculation of contribution values may be based on the impact of an individual key performance indicator value on the average of the key performance indicator values.

According to an example embodiment of the first aspect, the calculating the network key performance indicator value may comprise adding together the cell-specific key performance indicator values calculated for the subsets of cells. The calculating the contribution value for a subset of cells within the plurality of cells may comprise dividing the network key performance indicator value by a number of the subsets of cells within the plurality of cells and decreasing the result from the cell-specific key performance indicator value. With such a method, calculation of contribution values may be based on the impact of an individual key performance indicator value on the total sum of the key performance indicator values.

According to an example embodiment of the first aspect, the controlling the communication network may comprise targeting optimization activities on the one or more subsets of cells. With such a method, optimization activities may be targeted efficiently based on the contribution of the subsets of cells on the performance of the communication network.

According to an example embodiment of the first aspect, the method may further comprise: Acquiring further data associated with the communication network, wherein the further data may comprise first data associated with a first time period and second data associated with a second time period. Calculating, per subset of cells within the plurality of cells and utilizing the first data, a first contribution value associated with said subset of cells. Calculating, per subset of cells within the plurality of cells and utilizing the second data, a second contribution value associated with said subset of cells. Calculating, per subset of cells within the plurality of cells and utilizing the first contribution value and the second contribution value associated with said subset of cells, a contribution change value. Generating, utilizing the contribution change values calculated for the subsets of cells, a further output for controlling the communication network, wherein the further output may indicate a presence of other one or more subsets of cells from within the plurality of cells. With such a method, the performance of the plurality of cells encompassed in the communication network may be analysed based on change of their contributions over time.

According to an example embodiment of the first aspect, the controlling the communication network may comprise targeting further optimization activities on the other one or more cells. With such a method, optimization activities may be targeted efficiently based on the contribution on performance of the communication network and its change over time.

According to a second aspect, an apparatus may comprise at least one processor and at least one memory including computer program code. The at least one memory and the computer code may be configured to, with the at least one processor, cause the apparatus at least to perform: Acquiring data associated with a communication network comprising a plurality of cells. Calculating, per subset of cells within the plurality of cells and utilizing the data acquired, a value for a cell-specific key performance indicator. Calculating, utilizing the data acquired, a value for a network key performance indicator, wherein the network key performance indicator is inherently linked to the cell-specific key performance indicator. Calculating, per subset of cells within the plurality of cells and utilizing the data acquired, the network key performance indicator value calculated, and the cell-specific key performance indicator value calculated for said subset of cells, a contribution value associated with said subset of cells. Generating, utilizing the contribution values calculated for the subsets of cells, an output for controlling the communication network, wherein the output may indicate a presence of one or more subsets of cells from within the plurality of cells.

According to an example embodiment of the second aspect, the at least one memory and the computer program code may be configured to, with the at least one processor, cause the apparatus further to perform: Calculating the cellspecific key performance indicator value for one subset of cells within the plurality of cells by calculating a ratio of a first numerator value and a first denominator value associated with said one subset of cells. Calculating the network key performance indicator value by calculating a ratio of a second numerator value and a second denominator value associated with the communication network. Calculating the contribution value for said one subset of cells by decreasing the network key performance indicator value from the cell-specific key performance indicator value, multiplying the result with the first denominator value, and dividing the result with the second denominator value.

According to an example embodiment of the second aspect, the at least one memory and the computer program code may be configured to, with the at least one processor, cause the apparatus to further perform: Acquiring further data associated with the communication network, wherein the data may comprise first data associated with a first time period and second data associated with a second time period. Calculating, per subset of cells within the plurality of cells and utilizing the first data, a first contribution value associated with said subset of cells. Calculating, per subset of cells within the plurality of cells and utilizing the second data, a second contribution value associated with said subset of cells. Calculating, per subset of cells within the plurality of cells and utilizing the first contribution value and the second contribution value, a contribution change value. Generating, utilizing the contribution change values calculated for the subsets of cells, a further output for controlling the communication network, wherein the further output may indicate a presence of other one or more subsets of cells from within the plurality of cells.

According to a third aspect, a computer program product may comprise computer-readable program code configured to, when read and executed by a computer system, cause the computer system at least to perform: Acquiring data associated with a communication network comprising a plurality of cells. Calculating, per subset of cells within the plurality of cells and utilizing the data acquired, a value for a cell-specific key performance indicator. Calculating, utilizing the data acquired, a value for a network key performance indicator, wherein the network key performance indicator is inherently linked to the cellspecific key performance indicator. Calculating, per subset of cells within the plurality of cells and utilizing the data acquired, the network key performance indicator value calculated, and the cell-specific key performance indicator value calculated for said subset of cells, a contribution value associated with said subset of cells. Generating, utilizing the contribution values calculated for the subsets of cells, an output for controlling the communication network, wherein the output may indicate a presence of one or more subsets of cells from within the plurality of cells.

According to an example embodiment of the third aspect, the computer- readable program code may be configured to, when read and executed by the computer system, cause the computer system to further perform: Acquiring further data associated with the communication network, wherein the further data may comprise first data associated with a first time period and second data associated with a second time period. Calculating, per subset of cells within the plurality of cells and utilizing the first data, a first contribution value associated with said subset of cells. Calculating, per subset of cells within the plurality of cells and utilizing the second data, a second contribution value associated with said subset of cells. Calculating, per subset of cells within the plurality of cells and utilizing the first contribution value and the second contribution value, a contribution change value. Generating, utilizing the contribution change values calculated for the subsets of cells, a further output for controlling the communication network, wherein the further output may indicate a presence of other one or more subsets of cells from within the plurality of cells.

According to an example embodiment of the third aspect, the computer program product may be embodied on a computer-readable medium readable by the computer system.

Any example embodiment may be combined with one or more other example embodiments. Many of the attendant features will be more readily appreciated as they become better understood by reference to the following detailed description considered in connection with the accompanying drawings.

DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are included to provide a further understanding of the example embodiments and constitute a part of this specification, illustrate example embodiments and together with the description help to understand the example embodiments. In the drawings:

FIG. 1(a) and FIG. 1(b) illustrate a schematic block diagram of an example communication network;

FIG. 2 illustrates a schematic block diagram of an apparatus configured to practise one or more example embodiments;

FIG. 3 illustrates a schematic flow chart of contribution-based analysis according to an example embodiment; and

FIG. 4 illustrates a schematic flow chart of contribution-based analysis according to another example embodiment. DETAILED DESCRIPTION

Reference will now be made in detail to example embodiments, examples of which are illustrated in the accompanying drawings. The detailed description provided below in connection with the appended drawings is intended as a description of the present examples and is not intended to represent the only forms in which the present example may be constructed or utilized. The description sets forth the functions of the example and the sequence of steps for constructing and operating the example. However, the same or equivalent functions and sequences may be accomplished by different examples.

Although the specification may refer to “an”, “one”, or “some” embodiment(s) in several locations, this does not necessarily mean that each such reference is to the same embodiment(s), or that the feature may not apply to other embodiments. Single features of different embodiments may also be combined to provide other embodiments. Furthermore, words “comprising” and “including” should be understood as not limiting the described embodiments/example, and the embodiments/examples may contain also features/structures that have not been specifically mentioned.

Furthermore, although the numerative terminology, such as “first”, “second”, etc., may be used herein to describe various embodiments, elements, or features, it should be understood that these embodiments, elements, or features should not be limited by this numerative terminology. This numerative terminology is used herein only to distinguish one embodiment, element, or feature from another embodiment, element, or feature. For example, a first cell discussed below could be called a second cell, and vice versa, without departing from the teachings of the present disclosure.

According to an example embodiment, performance analysis of a communication network is based on how individual network objects, such as subsets of cells within a plurality of cells comprised in the communication network, contribute on the performance of the communication network. Key performance indicator values are utilized to calculate contribution values. Values for a cell-specific key performance indicator are calculated for the subsets of cells and a value for a network key performance indicator is calculated for the communication network. The network key performance indicator is inherently linked to the cell-specific key performance indicator, which may be understood such that the network key performance indicator measures or indicates a similar aspect of performance on a network level as the cell-specific key performance indicator measures or indicates on a cell level or a subset of cells level, e.g., the network KPI may indicate a dropped call rate for the communication network and the cell-specific KPI may indicate a dropped call rate for a single cell. The contribution values calculated may be utilized to identify subsets of cells that present worse performance than other subsets of cells within the communication network.

According to the example embodiment, it is possible to identify subsets of cells that have a significant impact on the performance of the communication network. The contribution values may enable interpretation of the impact of an individual subset of cells whereas the key performance indicator values as such may not be easily interpretable. A list of the worst performing subsets of cells may be obtained automatically by utilizing contribution value calculation. With such a list available, it may be possible to automatically perform necessary corrective actions in order to optimize the performance of the identified subsets of cells. Depending on the situation, the actions may be different. Utilizing contribution value calculation may increase the speed and effectiveness of controlling the communication network.

FIG. 1(a) illustrates an example embodiment of a communication network, for which the contribution-based analysis may be utilized. The communication network 100 may comprise one or more devices 110, which may be also referred to as client nodes, user nodes, or user equipment (UE). An example of a device is a UE 110, which may communicate with one or more access nodes of a radio access network (RAN) 120. The communication network 100 may therefore comprise a radio network. The RAN 120 may comprise one or more transmission sites, also simply referred to as sites (e.g., Sites 1 to 3). A site may comprise one or more access nodes. A transmission site may be further configured to provide communication services in one or more sectors, as will be further described with reference to FIG. 1(b). One access node may be configured to serve one or more sectors and/or one or more cells, illustrated in FIG. 1(a) with dotted circles, which may correspond to geographical area(s) covered by signals transmitted by the access node for a corresponding cell. Signals transmitted by an access node to the UE 110 may be referred to as downlink signals. Signals transmitted by the UE 110 to an access node may be referred to as uplink signals. An access node may be also referred to as an access point or a base station.

The communication network 100 may be configured for example in accordance with the 4^th or 5^th generation (4G, 5G) digital cellular communication networks, as defined by the 3^rd Generation Partnership Project (3GPP). For example, the communication network 100 may be configured to operate according to 3GPP (4G) LTE (Long-Term Evolution) and/or 3GPP 5G NR (New Radio) specifications. It is however appreciated that example embodiments presented herein are not limited to these example networks and may be applied in any present or future wireless communication networks, or combinations thereof, for example other type of cellular networks such as Global System for Mobile communication (GSM) or universal mobile telecommunication system (UMTS), short-range wireless networks, multicast networks, broadcast networks, or the like. Access nodes 122, 124, 126 of the RAN 120 may for example comprise 5^th generation access nodes (gNB) or 4^th generation access nodes (eNodeB).

FIG. 1(b) illustrates an example of cells of a sector of a transmission site, where Site 1 of FIG. 1(a) is used as an example. The access node 122 may be configured to serve three sectors (A to C). In this example, two cells 132-1 and 132-2 may be configured at Sector B, but in general a sector may comprise one or more cells. The cells may be identified with different cell identifiers (e.g., physical cell ID). Cells associated with the same sector may be configured to operate at different frequencies or with different code bases in case of a code division multiple access (CDMA) system. As illustrated in FIG. 1(b), coverage areas of the cells of the same sector may overlap. A contribution value according to an example embodiment may be calculated, e.g., for a subset of cells comprising a plurality of cells associated with the same sector or for a subset of cells configured to operate at a frequency or with a code basis.

Referring to FIG. 1(a), the communication network 100 may further comprise a core network 130, which may comprise various network functions (NF) for establishing, configuring, and controlling data communication sessions of users, for example the UE 110. The data communication sessions may carry data traffic, for example application data associated with one or more applications running on the UE 110. The communication network 100 may further comprise a network controller 140, for example a centralized selforganized network (C-SON) controller, which may be responsible of configuring various operations of the RAN 120. The network controller 140 may be also referred to as a centralized network controller. The network controller 140 may interface an operations support system (OSS) 150, which may be configured to deliver various information, such as for example inventory management (IM) data, configuration management (CM) data, or performance management (PM) data between the RAN 120 and the network controller 140. Even though illustrated as a separate entity, network controller 140 may be also embodied as part of any suitable network device of function, for example as part of the OSS 150. Even though some operations have been described as being performed by the network controller 140, it is understood that similar functions may be performed alternatively by other network device(s) or network function(s) of the communication network 100, which may be in general referred to as network objects. The operations may be performed by an automated network monitoring and controlling system or an automated network operation center (NOC) such as, e.g., a virtual NOC. The automated NOC may be understood as a network object responsible for monitoring power failures, communication line alarms, and other performance issues that may affect the network. In telecommunication environments the automated NOC may track details of call flows. One task of the network controller 140 may be to analyse performance of the communication network 100, or network object(s) thereof, e.g., in order to determine how to target optimization activities. Operational characteristics of the communication network 100 may be analysed and optimized with many different methods and based on various key performance indicators (KPI), including, but not limited to, the following: traffic channel (TCH) setup success rate, standalone dedicated control channel (SDCCH) setup success rate, cell availability, TCH drop rate, SDCCH drop rate, SDCCH traffic, TCH traffic, SDCCH congestion time, downlink EDGE (Enhanced Data rates for GSM Evolution) traffic, circuit-switched (CS) success rate, packet-switched (PS) success rate, radio resource control (RRC) mobile- oriented success rate, RRC mobile-terminated (MT) success rate, PS call drop rate, CS call drop rate, high-speed uplink packet access (HSUPA) traffic, CS traffic, high-speed downlink packet access (HSDPA) traffic, RRC setup success rate, evolved-UMTS terrestrial radio access network (E-UTRAN) radio access bearer (E-RAB) setup success rate, RRC abnormal release rate, E-RAB drop rate , downlink data volume, uplink data volume, average reported channel quality indicator (CQI), and multiple input multiple output (MIMO) rank indicator. Analysing individual KPI values manually may comprise timeconsuming tasks. Example embodiments of the present disclosure provide methods that may overcome such challenges. Contribution-based analysis may be utilized with any key performance indicator available.

FIG. 2 illustrates an example embodiment of an apparatus 200 configured to perform operations of one or more example embodiments, e.g., functionalities described below with reference to FIG. 3 and FIG. 4. The apparatus 200 may be for example used to implement the network controller 140. The apparatus 200 may comprise at least one processor 202. The at least one processor 202 may comprise, for example, one or more of various processing devices or processor circuitry, such as for example a co-processor, a microprocessor, a controller, a digital signal processor (DSP), a processing circuitry with or without an accompanying DSP, or various other processing devices including integrated circuits such as, for example, an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a microcontroller unit (MCU), a hardware accelerator, a special-purpose computer chip, or the like. The apparatus 200 may further comprise at least one memory 204. The at least one memory 204 may be configured to store, for example, computer program code or the like, for example operating system software and application software. The at least one memory 204 may comprise one or more volatile memory devices, one or more non-volatile memory devices, and/or a combination thereof. For example, the at least one memory 204 may be embodied as magnetic storage devices (such as hard disk drives, floppy disks, magnetic tapes, etc.), optical magnetic storage devices, or semiconductor memories (such as mask ROM, PROM (programmable ROM), EPROM (erasable PROM), flash ROM, RAM (random access memory), etc.).

The apparatus 200 may further comprise a communication interface 208 configured to enable apparatus 200 to transmit and/or receive information to/from other devices, functions, or entities. In one example, the apparatus 200 may use communication interface 208 to transmit or receive information over a service based interface (SBI) message bus of the core network 130, for example to the core network 130 and/or the RAN 120. The communication interface 208 may therefore comprise a data communication interface and be configured for communication between devices, for example according to one or more data communication protocols. The apparatus 200 maybe for example configured to transmit indication(s) of verified or non-verified performance, for example to an automated service ticket system, or to provide network configuration instructions to the RAN 120 to cause reconfiguration of network object(s). The apparatus 200 may further comprise a user interface 210, for example for providing user output by the apparatus, such as for example visual and/or audible signal(s), for example by speaker(s), display(s), light(s), or the like. The user interface 210 may be used for example for outputting indication(s) of verified or non-verified performance to a human user.

When the apparatus 200 is configured to implement some functionality, some component and/or components of the apparatus 200, such as for example the at least one processor 202 and/or the at least one memory 204, may be configured to implement this functionality. Furthermore, when the at least one processor 202 is configured to implement some functionality, this functionality may be implemented using program code 206 comprised, for example, in the at least one memory 204.

The functionality described herein may be performed, at least in part, by one or more computer program product components such as for example software components. According to an example embodiment, the apparatus 200 comprises a processor or processor circuitry, such as for example a microcontroller, configured by the program code when executed to execute the embodiments of the operations and functionality described. A computer program or a computer program product may therefore comprise instructions for causing, when executed, the apparatus 200 to perform the method(s) described herein. Alternatively, or in addition, the functionality described herein may be performed, at least in part, by one or more hardware logic components. For example, and without limitation, illustrative types of hardware logic components that may be used include Field-programmable Gate Arrays (FPGAs), application-specific Integrated Circuits (ASICs), application-specific Standard Products (ASSPs), System-on-a-chip systems (SOCs), Complex Programmable Logic Devices (CPLDs), Graphics Processing Units (GPUs).

The apparatus 200 comprises means for performing at least one method described herein. In one example, the means comprises the at least one processor 202, the at least one memory 204 including the program code 206 configured to, when executed by the at least one processor, cause the apparatus 200 to perform the method.

The apparatus 200 may comprise a computing device such as for example an access point, an access node, a base station, a server, a network device, a network function device, or the like. Although the apparatus 200 is illustrated as a single device it is appreciated that, wherever applicable, functions of the apparatus 200 may be distributed to a plurality of devices, for example to implement example embodiments as a cloud computing service.

FIG. 3 illustrates a flowchart according to an example embodiment of a computer-implemented method for identifying cells based on contribution on the performance of a communication network. The apparatus 200 illustrated with FIG. 2 is configured to perform the operation of the method in the communication network 100 illustrated with FIG. 1(a) and 1(b).

Referring to FIG. 3, data associated with the communication network comprising a plurality of cells is acquired in operation 301. The data may be acquired from one or more data sources, such as communication databases and/or external databases. An external database may be, e.g., a data source providing weather information. The data may be associated with a time period. A value for a cell-specific key performance indicator (KPI) is calculated in operation 302 per a subset of cells within the plurality of cells, utilizing the data acquired. The subset of cells may comprise one or more cells. The subset of cells may be an aggregation of cells from within the plurality of cells. The aggregation may be associated with, e.g., a geographical area, such as a municipality, a province, or a zip code area. Additionally, or alternatively, the aggregation may be associated with, e.g., a configuration or a parameter, such as a network, a base station vendor, a frequency, hardware, or a beam set. Additionally, or alternatively, the aggregation may be associated with, e.g., user level, such as a terminal type, a subscription type, or a user category such as, e.g., age. Additionally, or alternatively, the aggregation may be associated with a combination of a geographical area and a parameter, such as a vendor border, a frequency border, or a network border. Additionally, or alternatively, the aggregation may comprise a sub-period from within the time period the data is associated with, such as a solar day, an hour, a busy hour, or a week. A value for a network key performance indicator is calculated in operation 303 utilizing the data acquired. The network KPI is inherently linked to the cell-specific KPI, which may be understood such that the network KPI measures or indicates a similar aspect of the performance on a network level as the cell-specific KPI measures or indicates on a cell level or a subset of cells level. In an example, the cell-specific key performance values calculated and the network key performance value calculated may be stored associated with a time stamp indicating the time period the acquired data is associated with. Per subset of cells within the plurality of cells, a contribution value associated with said subset of cells is calculated in operation 304 utilizing the data acquired, the network KPI value calculated, and the cell-specific KPI value calculated for said subset of cells. An output for controlling the communication network is generated in block 305 utilizing the contribution values calculated for the plurality of cells. The output may indicate a presence of one or more subsets of cells from within the plurality of cells. In an example embodiment, the one or more subsets of cells may be associated with largest absolute values from within the contribution values calculated.

In an example embodiment, the calculating the cell-specific KPI value for one subset of cells within the plurality of cells may comprise calculating a ratio of a first numerator value and a first denominator value. The calculating the network KPI value may comprise calculating a ratio of a second numerator value and a second denominator value. The calculating the contribution value for said one subset of cells may comprise decreasing the network key performance indicator value from the cell-specific key performance indicator value, multiplying the result with the first denominator value, and dividing the result with the second denominator value. The calculations explained above may be expressed by the following equations:

where k_t may be understood as the cell-specific key performance indicator value calculated for a subset of cells i , n_t may be understood as the first numerator value, d_t may be understood as the first denominator value, K may be understood as the network key performance indicator value, N may be understood as the second numerator value, D may be understood as the second denominator value, M may be understood as a number of the subsets of cells, and c_t may be understood as the contribution value calculated for the subset of cells i. In an example embodiment, the first numerator value may comprise a first value for a first parameter and the first denominator value may comprise a first value for a second parameter, wherein the first value for the first parameter and the first value for the second parameter are associated with said one subset of cells. The second numerator value may comprise a second value for the first parameter and the second denominator value may comprise a second value for the second parameter, wherein the second value for the first parameter and the second value for the second parameter are associated with the communication network. In an example embodiment, the first parameter may be, e.g., a number of successes and the second parameter may be a number of attempts. In another example embodiment, the first parameter may be a number of dropped calls and the second parameter may be a total number of calls.

In an example embodiment, the calculating the network key performance indicator value may comprise adding together the cell-specific key performance indicator values calculated for the subsets of cells and dividing the result by a number of the subsets of cells. The calculating the contribution value for one subset of cells within the plurality of cells may comprise decreasing the network key performance indicator value from the cell-specific key performance indicator value and dividing the result by the number of the subsets of cells. The calculation explained above may be expressed by the following equations:

where K may be understood as the network key performance indicator value, k_t may be understood as the cell-specific key performance indicator value calculated for a subset of cells i, and M may be understood as the number of the subsets of cells.

In an example embodiment, the calculating the network key performance indicator value may comprise adding together the cell-specific key performance indicator values calculated for the subsets of cells. The calculating the contribution value for one subset of cells within the plurality of cells may comprise dividing the network key performance indicator value by a number of the subsets of cells and decreasing the result from the cell-specific key performance indicator value. The calculation explained above may be expressed by the following equations:

1 ci L = kt L ~ —K, M where K may be understood as the network key performance indicator value, k_t may be understood as the cell-specific key performance indicator value calculated for a subset of cells i, and M may be understood as the number of the subsets of cells.

In an example embodiment, the controlling the communication network may comprise targeting optimization activities on the one or more subsets of cells.

FIG. 4 illustrates a flowchart according to an example embodiment of a computer-implemented method for identifying cells based on contribution change. The apparatus 200 illustrated with FIG. 2 is configured to perform the operation of the method within the communication network 100 illustrated with FIG. 1(a) and 1(b).

Referring to FIG. 4, further data associated with the communication network is acquired in operation 401. The further data may comprise first data associated with a first time period and second data associated with a second time period. For example, the first time period may be a solar day and the second time period may be a subsequent solar day, or the first time period may be an hour and the second time period may be a subsequent hour. Per subset of cells within the plurality of cells, a first contribution value associated with said subset of cells is calculated in operation 402 utilizing the first data, and a second contribution value associated with said subset of cells is calculated in block 403 utilizing the second data. Per subset of cells within the plurality of cells, a contribution change value is calculated in operation 404 utilizing the first contribution value and the second contribution value associated with said subset of cells. In an example embodiment, the contribution change value may be calculated by decreasing the first contribution value from the second contribution value.

A further output for controlling the communication network is generated in operation 405 utilizing the contribution change values calculated for the plurality of cells. The further output may indicate a presence of other one or more subsets of cells from within the plurality of cells. In an example embodiment, the other one or more subsets of cells may be associated with largest absolute values from within the contribution change values calculated. In an example embodiment, the controlling the communication network may comprise targeting further optimization activities on the another one or more subsets of cells.

Although the subject matter has been described in language specific to structural features and/or acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example embodiments of implementing the claims and other equivalent features and acts are intended to be within the scope of the claims.

It will be understood that the benefits and advantages described above may relate to one example embodiment or may relate to several example embodiments. The example embodiments are not limited to those that solve any or all of the stated problems or those that have any or all of the stated benefits and advantages. It will further be understood that reference to 'an' item may refer to one or more of those items.

The steps or operations of the methods described herein may be carried out in any suitable order, or simultaneously where appropriate. Additionally, individual blocks may be deleted from any of the methods without departing from the scope of the subject matter described herein. Aspects of any of the example embodiments described above may be combined with aspects of any of the other example embodiments described to form further example embodiments without losing the effect sought.

It will be understood that the above description is given by way of example embodiments only and that various modifications may be made by those skilled in the art. The above specification, example embodiments and data provide a complete description of the structure and use of exemplary embodiments. Although various example embodiments have been described above with a certain degree of particularity, or with reference to one or more individual embodiments, those skilled in the art could make numerous alterations to the disclosed example embodiments without departing from scope of this specification.

Claims

1. A computer-implemented method, comprising: acquiring data associated with a communication network comprising a plurality of cells; calculating, per subset of cells within the plurality of cells, utilizing the data acquired, a value for a cell-specific key performance indicator; calculating, utilizing the data acquired, a value for a network key performance indicator, wherein the network key performance indicator is inherently linked to the cell-specific key performance indicator; calculating, per subset of cells within the plurality of cells, utilizing the data acquired, the network key performance indicator value calculated, and the cellspecific key performance indicator value calculated for said subset of cells, a contribution value associated with said subset of cells; and generating, utilizing the contribution values calculated for the subsets of cells, an output for controlling the communication network, wherein the output indicates a presence of one or more subsets of cells from within the plurality of cells.

2. A computer-implemented method according to claim 1, wherein the one or more subsets of cells are associated with largest absolute values within the contribution values calculated.

3. A computer-implemented method according to claim 1 or 2, wherein the calculating the cell-specific key performance indicator value for a subset of cells within the plurality of cells comprises calculating a ratio of a first numerator value and a first denominator value associated with said subset of cells, wherein the calculating the network key performance indicator value comprises calculating a ratio of a second numerator value and a second denominator value associated with the communication network, and wherein the calculating the contribution value for said subset of cells comprises subtracting the network key performance indicator value from the cell-specific key performance indicator value, multiplying the result with the first denominator value, and dividing the result with the second denominator value.

4. A computer-implemented method according to claim 3, wherein the first numerator value comprises a first value for a first parameter and the first denominator value comprises a first value for a second parameter, the first value for the first parameter and the first value for the second parameter being associated with said subset of cells, and wherein the second numerator value comprises a second value for the first parameter and the second denominator value comprises a second value for the second parameter, the second value for the first parameter and the second value for the second parameter being associated with the communication network.

5. A computer-implemented method according to claim 1 or 2, wherein the calculating the network key performance indicator value comprises adding together the cell-specific key performance indicator values calculated for the subsets of cells within the plurality of cells and dividing the result by a number of the subsets of cells within the plurality of cells, and wherein the calculating the contribution value for a subset of cells within the plurality of cells comprises subtracting the network key performance indicator value from the cell-specific key performance indicator value and dividing the result by the number of the subsets of cells within the plurality of cells.

6. A computer-implemented method according to claim 1 or 2, wherein the calculating the network key performance indicator value comprises adding together the cell-specific key performance indicator values calculated for the subsets of cells within the plurality of cells, and wherein the calculating the contribution value for a subset of cells within the plurality of cells comprises dividing the network key performance indicator value by a number of the subsets of cells within the plurality of cells and subtracting the result from the cell-specific key performance indicator value.

7. A computer-implemented method according to any of the preceding claims, wherein the controlling the communication network comprises targeting optimization activities on the one or more subsets of cells.

8. A computer-implemented method according to any of the preceding claims, further comprising: acquiring further data associated with the communication network, wherein the further data comprises first data associated with a first time period and second data associated with a second time period; calculating, per subset of cells within the plurality of cells, utilizing the first data, a first contribution value associated with said subset of cells; calculating, per subset of cells within the plurality of cells, utilizing the second data, a second contribution value associated with said subset of cells; calculating, per subset of cells within the plurality of cells, utilizing the first contribution value and the second contribution value associated with said subset of cells, a contribution change value; and generating, utilizing the contribution change values calculated for the subsets of cells, a further output for controlling the communication network, wherein the further output indicates a presence of other one or more subsets of cells from within the plurality of cells.

9. A computer-implemented method according to claim 8, wherein the controlling the communication network comprises targeting further optimization activities on the other one or more subsets of cells.

10. An apparatus comprising: at least one processor; and at least one memory including computer program code, the at least one memory and computer program code being configured to, with the at least one processor, cause the apparatus at least to perform: acquiring data associated with a communication network comprising a plurality of cells; calculating, per subset of cells within the plurality of cells, utilizing the data acquired, a value for a cell-specific key performance indicator; calculating, utilizing the data acquired, a value for a network key performance indicator, wherein the network key performance indicator is inherently linked to the cell-specific key performance indicator; calculating, per subset of cells within the plurality of cells, utilizing the data acquired, the network key performance indicator value calculated, and the cellspecific key performance indicator value calculated for said subset of cells, a contribution value associated with said subset of cells; and generating, utilizing the contribution values calculated for the subsets of cells, an output for controlling the communication network, wherein the output indicates a presence of one or more subsets of cells from within the plurality of cells.

11. An apparatus according to claim 10, wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus to further perform: calculating the cell-specific key performance indicator value for one subset of cells within the plurality of cells by calculating a ratio of a first numerator value and a first denominator value associated with said one subset of cells; calculating the network key performance indicator value by calculating a ratio of a second numerator value and a second denominator value associated with the communication network; and calculating the contribution value for said one subset of cells by subtracting the network key performance indicator value from the cell-specific key performance indicator value, multiplying the result with the first denominator value, and dividing the result with the second denominator value.

12. An apparatus according to claim 10 or 11, wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus to further perform: acquiring further data associated with the communication network, wherein the data comprises first data associated with a first time period and second data associated with a second time period; calculating, per subset of cells within the plurality of cells, utilizing the first data, a first contribution value associated with said subset of cells; calculating, per subset of cells within the plurality of cells, utilizing the second data, a second contribution value associated with said subset of cells; calculating, per subset of cells within the plurality of cells, utilizing the first contribution value and the second contribution value, a contribution change value; and generating, utilizing the contribution change values calculated for the subsets of cells, a further output for controlling the communication network, wherein the further output indicates a presence of other one or more subsets of cells from within the plurality of cells.

13. A computer program product comprising a computer-readable program code configured to, when read and executed by a computer system, cause the computer system at least to perform: acquiring data associated with a communication network comprising a plurality of cells; calculating, per subset of cells within the plurality of cells, utilizing the data acquired, a value for a cell-specific key performance indicator; calculating, utilizing the data acquired, a value for a network key performance indicator, wherein the network key performance indicator is inherently linked to the cell-specific key performance indicator; calculating, per subset of cells within the plurality of cells, utilizing the data acquired, the network key performance indicator value calculated, and the cellspecific key performance indicator value calculated for said subset of cells, a contribution value associated with said subset of cells; and generating, utilizing the contribution values calculated for the subsets of cells, an output for controlling the communication network, wherein the output indicates a presence of one or more subsets of cells from within the plurality of cells.

14. A computer program product according to claim 13, wherein the computer-readable program code is configured to, when read and executed by the computer system, cause the computer system to further perform: acquiring further data associated with the communication network, wherein the further data comprises first data associated with a first time period and second data associated with a second time period; calculating, per subset of cells within the plurality of cells, utilizing the first data, a first contribution value associated with said subset of cells; calculating, per subset of cells within the plurality of cells, utilizing the second data, a second contribution value associated with said subset of cells; calculating, per subset of cells within the plurality of cells, utilizing the first contribution value and the second contribution value, a contribution change value; and generating, utilizing the contribution change values calculated for the subsets of cells, a further output for controlling the communication network, wherein the further output indicates a presence of other one or more subsets of cells from within the plurality of cells.

15. A computer program product according to claim 13 or 14 embodied on a computer-readable medium readable by the computer system.