TECHNICAL FIELD

The disclosure generally relates to the field of Telecommunication networks and more particularly to Self-Organizing Networks. The disclosure particularly relates to a method of predicting an increase in amount of traffic in a particular cell of a telecommunication network.

BACKGROUND

Mobile communication has become an inseparable part of our day to day life. We find ourselves depending to an increasing extent on mobile phones and its communication networks. As mobile phones and the technology continues to make our lives easier, the complexity of cellular networks is increasing. Accordingly, the cost of operation, administration and management increases.

In this context, Self-Organizing Networks, SON, are gaining importance in that they provide an option whereby networks are able to adapt automatically to changes in requirement. An SON is an automation technology designed to make the planning, configuration, management, optimization and healing of mobile radio networks simpler and faster. Newly added access nodes should be self-configured in line with a plug and play paradigm, while all operational access nodes will regularly self-optimize parameters and algorithmic behaviour in response to observed network performance and radio conditions. Furthermore, self-healing mechanisms can be triggered to temporarily compensate for detected equipment outage, while awaiting a more permanent solution.

Primarily, the functions of an SON can be classified in to three aspects.

A first aspect is related to self-configuration. When a new access node is introduced into the network and powered ON, it gets recognized and registered by the network. This is often an automatic process, hence the self-configuration. The benefit hereof is that any neighbouring access nodes may then automatically adjust their technical parameters, such as emission power, antenna tilt etc., in order to provide the required coverage and capacity and, in the same time, avoid interference.

A second aspect is related to self-optimization. Every access node may comprise hundreds of configuration parameters that control various aspects of their corresponding cells. Each of these can be altered to change network behaviour, based on observations of both the access node itself and measurements at the mobile station or handset. One of the first SON features establishes neighbour relations automatically while other optimize random access parameters or mobility robustness in terms of handover oscillations

A third aspect is related to self-healing. When some nodes in the network become inoperative, self-healing mechanisms aim at reducing the impacts from the failure, for example by adjusting parameters and algorithms in adjacent cells so that other nodes can support the users that were supported by the failing node. In legacy networks, the failing access nodes are at times hard to identify and a significant amount of time and resources is required to fix it. This function of SON permits to spot such a failing access node immediately in order to take further measures, and ensure no or insignificant degradation of service for the users.

For most of the present techniques, inputs for self-organizing come from the network itself. This may be obtained by monitoring the network, counters, alarms or other Key Performance Indicators, KPI. However, in cellular networks, human crowds/events can cause an essential impact in network performance. For example, they amount for a predominant part of network failures and performance degradations.

One of the challenges of present telecommunication networks is to predict an increase in amount of traffic in a cell, or a plurality of cells, which prediction can then be used for optimization of the telecommunication network.

SUMMARY

It is an object to provide for a method of predicting an increase in amount of traffic in a particular cell of a telecommunication network.

It is another object to provide for a node in a telecommunication network arranged for predicting an increase in amount of traffic in a particular cell of a telecommunication network.

In a first aspect of the disclosure, there is provided a method for predicting an increase in amount of traffic in a particular cell of a telecommunication network, wherein said telecommunication network comprises a plurality of access nodes, wherein each of said access nodes is arranged to serve a cell in said telecommunication network, wherein each cell covers a predefined coverage area.

The method comprises the steps of receiving event information from at least one source which is external to said telecommunication network, wherein said event information comprises geographic data and temporal data of events that are to take place, associating said events with at least one particular access node of said plurality of access nodes based on said geographic data of each of said events and based on said predefined coverage areas of said cells, predicting an increase in amount of traffic in a cell of said telecommunication network based on said associated events with at least one particular access node and their corresponding temporal data.

The method is at least based on the insight that a telecommunication network, for example a self-organizing network, SONs, is able to perform more efficient in case an increase in amount of traffic in a cell is predicted.

Such a prediction can, for example, be used for adjusting parameters, such as emission power, antenna tilt, etc., by obtaining information about social events from external sources. Information about events such as popularity and venue of the event is used to predict the number of people attending said event. This information may then be used to alter the parameters of particular cell or cells within a telecommunication network such that the network is able to function effectively while the event occurs.

In a first step, event information is received from external sources. The event information comprises geographical data and temporal data.

The invent information may be requested or acquired from the external sources. That is, the system may be arranged to take the initiative to request the information from the external sources.

The geographical data can be, for example, the name of a venue where the event is to take place. Additionally, the location could be specified by providing an address in string type such as street, city, region, country, postal code etc. Alternatively, geographical data could be in the form of a latitude and longitude by which the location may be identified on a map. Alternatively, the geographical data could be merely a region such as a town or city or a municipality or a state, covering a larger geographical extent as might be in the case of an event being organised in several venues in a city all at once or a parade.

The temporal data implies the time related data regarding the event. Such information often includes, a date and time when said event is to take place. Alternatively, the date could be provided as a range of dates and similarly the time could be provided as a range of times when said event is to take place.

It is noted that the term event may be used to imply any social gathering of human beings. Such an event could be the inauguration of a building, an exhibition, a show in a museum, a concert, a sporting event, a religious gathering, protests or any other possible scenario which is likely to attract people. Such events may be planned well in advance or can happen simultaneously owing to a particular sequence of events.

In a second step, the events are associated with a plurality of access nodes within a telecommunication network. These nodes can be any of a base station, an evolved node B or anything alike. In a telecommunication network, access nodes are assigned to cover or handle the communications originating or ending within a particular geographical area. Thus it is often expressed that a particular node is associated with a particular geographical area, i.e. a coverage area of a cell. Multiple nodes that fall within a certain predefined proximity tolerance of the event venue could be associated with one particular event.

In a third step, an increase in the amount of traffic may be predicted for the associated access nodes during the defined time period of the said social event. This increase could be, for example, used to allocate increased bandwidth to the particular nodes. Alternatively, the access nodes could transmit signals at a higher transmit power. Another option could be to adjust the orientation of a particular cell, or to use beamforming techniques, such that it covers a different, for example smaller, geographical area.

In an example of the disclosure, said method of predicting an increase in amount of network traffic comprises a further step of requesting said event information from said external source. This step usually occurs before the step of receiving event information from external sources. It is based on the insight that it would be advantageous to receive said event information when a node or the telecommunication network itself or a corresponding cloud service is actually receptive for said information.

For example, requesting event information could comprise specifying a particular geographical region and a particular time frame. Only event information falling within such limits are then received. The advantage is that there are only a fewer number of data rows available for consequent steps thereby reducing the amount of processing power required at further stages.

The geographical area could be defined by means of a minimum and maximum longitude and a minimum and maximum latitude. This, in effect, defines a region on a map, for example a rectangular region. Alternatively, the region could be defined by specifying one set of coordinates, for example latitude and longitude, together with a distance defining a circular region on a map. In yet another alternative, the geographical area is indicated with particular cell identification, like cell numbers. As such, the geographical area refers to the actual cells of the telecommunication network.

The time parameters could be defined using any year range, month range, date range, time range. The person skilled in the art realises that a combination of such ranges is possible and is within the scope of this application.

It is noted that the present disclosure may also be directed to identifying the cause of past traffic increases. That is, the social media input may be used for recognizing traffic increase in any of the cells. This information can then be used in the scheduling process.

In an example according to the disclosure, said step of receiving event information comprises receiving said event information from a social networking website or an event database. Often, the events are available online and the data is made available to the users of a social media networking platform. The inventors consider it to be advantageous to gather such information that is available online. Therefore, it is an option to request event information to such social networking platform or a specialized event database. These platforms may mention the characteristics of the event—such as location, time, date etc. in detail. Alternatively, certain venues, such as concert halls or stadiums, maintain their own individual database together with an event calendar on such social media networking platforms. The event information may be requested to, and subsequently received from, such platforms as well.

Another advantage of events hosted on social media networking platforms are that they often indicate the amount of people going to attend said event, or that are considering to attend the event. Although this figure, in most cases, may not be accurate, it gives a good indication regarding the popularity of the event which can be useful for network adaptation.

It is noted that the format in which the event information being the geographic data and temporal data of events that are to take place, are provided may differ from one social networking website to another. The format may also differ from one event database to another. The method may comprise a step in which the provided formats are made uniform such that a computer readable uniform list is obtained.

In an example of the disclosure, the method further comprises a step of formatting said received information into a predefined uniform data structure. The step is based on the insight that it would be advantageous to format all received event information into a consistent format before processing it further. Therefore, once the event information is received from one or more external sources, the data may be extracted and a common formatting may be applied to it. A common example could be in the date of events. Different platforms could host the information in different formats—for example “ddmmyy”, “ddmmyyyy”, “yyyymmdd”, “mmddyy” etc. just to cite a few. In such a scenario, it would be advantageous to extract the event information and to apply a uniform formatting structure. This would be beneficial in the further steps of the method. While searching or requesting information, multiple formats could be utilised such that all the relevant entries are made available, but in interest of further optimisation of software, it would be advantageous to convert all available data to a uniform format.

In an example of the disclosure, said method of predicting an increase in traffic further comprises a step of combining multiple same events into a single aggregated event, wherein same events are defined as events having a substantially same geographic data and a substantially same temporal data. It is possible that while requesting event information to multiple sources, multiple entries of the same event are made. Thus it would be advantageous to eliminate such multiple entries, thereby not over estimating the crowd size. Several parameters could be utilized while determining whether two or more entries concern the same event.

One criteria could be to check the differences in spelling. If there are only minor spelling differences, it could possibly relate to the same event. This is often in the case of a non-native English word, when written using Latin alphabets. Another common field that is prone to such errors would be the location and the time details. For example, one platform may only provide the exact times during which the event occurs. Another platform may additionally provide the time from which the venue is made open to the public and well beyond the closing time of the event. Such differences should be taken into consideration and checks are performed to combine multiple entries of the same event into one single entry.

An example of the disclosure further comprises the step of filtering and prioritizing said event information, wherein filtering of event information is based on availability of data or a type of venue and prioritizing of said event information is based on a number of people expected to attend said event or popularity of said event. This example is based on the insight that it would be advantageous to consider only those events which are documented and well planned in advance and also to give a higher priority to those that are likely to attract larger audiences. It is often the case that in certain databases, certain key elements concerning the data are missing. This may be a time duration of the event, or venue details etc. In such cases, it would be advantageous, from the point of view of reducing the data to be processed, to avoid events which do not have complete information regarding the venue and/or time.

As also discussed, earlier, the term “events” covers a wide range of social gatherings right from religious gatherings in a small church to book readings at a local book club to rock concerts or football matches. From the point of view of load on a telecommunication network, a gathering of about 20-30 people for a book reading is bound to have a lesser impact than a gathering of about 40000-50000 spectators for a football match. Similarly, a low profile football match is likely to attract lesser spectators than the final of a major tournament. Therefore, it makes sense to prioritize the events based on the expected attendance of the event.

Attendance could be estimated by the nature of the event itself, i.e.—book reading vs. football match. Alternately, attendance could be estimated by following the event on a social media networking platform to find out how many people have expressed an interest in viewing or attending this event. Additionally, the expected attendance could be determined by alternate means such as capacity of the venue, or the number of people that the venue can accommodate, the number of tickets sold etc.

Once the expected attendance for the event is established, it would be advantageous to prioritize the events based on the number of the people attending said event for the reasons explained above. Alternately, it is also possible that events occurring with a certain fixed frequency are predicted by the system itself and necessary network adaptations are made automatically without waiting for the information, filtering and prioritizing.

In an example of the disclosure, said association is based on geographical proximity such that at least one cell of said telecommunication network closest to the geographical location of the event is associated to said event. Once the geographical location of the events is identified, certain cells of the communication network have to be associated with the event. The inventors consider that it would be advantageous base such an association on geographical proximity of the cell to the location of the event. For this purpose, a list of cells of the telecommunication network that fall within a relevant geographical area are selected at first.

Here, a selection of one or more cells from the selected ones is to be done. In order to do so, the distance from the cell to the event location is to be calculated. But first, a uniform reference point within each cell may be established. This could be, for example, the location of the node itself or could be any other point within the cell. In order for simplifying the explanation, it is assumed that the reference point within the cell is the location of the node itself. Once the location of the reference point is established, a distance between the reference point and the event location may be calculated. This could be done, for example, using the haversine formula or the Pythagorean theorem approach. Both these techniques are well documented in the state of the art and are commonly used approaches to theoretically calculating the distance between two points on the surface of the earth when the respective latitudes and longitudes are known. For purposes of brevity, the methods and the relevant calculation procedure itself are not further elaborated here.

In an example according to the disclosure, said method further comprises the step of adjusting operations, administration and management, OAM, processes for said at least one particular access node based on said predicted increase in amount of traffic in said corresponding cell.

One of the possible node adaptations to increase of traffic related to the the planning and deployment of new sites, macro or small. Yet a further option is the assigning of additional bandwidth to cells expected to be crowded. Even a further option is the performing of load balancing techniques, e.g. by antenna tilt, mobility parameters or transmitted power, that allow a better share of the expected traffic with close cells, therefore reducing the impact of the expected increase.

In a further example according to the disclosure, said OAM processes comprises at least one of failure management, preventive allocation of resources, re-planning, energy saving, and optimization. These processes are routine processes undertaken to ensure that the network function effectively without any inconvenience to the end users. Once particular cells are associated with one or more events, certain OAM procedures may be performed on the cell. This can be to ensure that cell is capable of handling the additional network traffic without failure. Alternately, the bandwidth and power output of a particular cell could be decreased after the completion of the event so as to conserve energy.

An alternative option could be to provide a list of events and associated network cells and nodes in a printable format such that it may be understood by a user such as a network operator or a maintenance engineer. In the absence of automatic regulatory mechanisms, such a user could make the necessary adjustments in the system.

In accordance with the present disclosure, different aspects applicable to the above mentioned examples of the methods, including the advantages thereof, correspond to the aspects which are applicable to the devices of the communication network.

In a second aspect of the disclosure, there is provided a node for use in a telecommunication network arranged for predicting an increase in the amount of traffic in a particular cell of said telecommunication network, wherein said telecommunication network comprises a plurality of access nodes, wherein each of said access nodes is arranged to serve a cell in said telecommunication network, wherein each cell covers a predefined coverage area.

The node comprises an information acquisition module arranged for receiving event information from at least one external source, wherein said event information comprises geographic data and temporal data of events that are to take place, a cellular network association module arranged for associating said received events with at least one particular access node of said plurality of access nodes based on said geographic data of each of said events and based on said predefined coverage areas of said cells, an output module arranged for predicting an increase in amount of traffic in a cell of said telecommunication network based on said associated events with at least one particular access node and their corresponding temporal data.

The advantages of the first aspect of the disclosure being a method of predicting increase in cellular traffic in a communication network are also inherently a part of the second aspect of the disclosure. Furthermore, it is pointed out that although the claims read as if all the modules according to the present disclosure are incorporated into a single node, a person skilled in the art understands that the same disclosure could be implemented by, for example, distributing each of the modules over several nodes. Alternately, the disclosure could also be purely implemented in the cloud, whereby none of the physical nodes possess any of these modules as such.

The information acquisition module is responsible for receiving information pertaining to events from external sources. The information thus received is subsequently passed on to the other modules within the node.

In an example according to the second aspect of the disclosure, said information acquisition module is further capable of requesting said event information to the plurality of external sources. As was mentioned earlier, it would be advantageous to receive relevant information from external sources. Therefore, the information acquisition module, is further capable of requesting information to external sources such as social media networking platforms and event databases.

In an example according to the second aspect of the disclosure, said information acquisition module is arranged to receive said event information from a social networking site or an event database.

In another example according to the second aspect of the disclosure, said information acquisition module is further arranged to format the received information into a predefined uniform data structure.

In another example according to the second aspect of the disclosure, said information acquisition module is further arranged for combining multiple same events into a single aggregated event, wherein same events are defined as events having a substantially same geographic data and a substantially same temporal data.

In an example according to the second aspect of the disclosure, said node further comprises a social filtering and ranking module arranged for filtering and prioritizing said event information, wherein filtering of event information is based on availability of data or a type of venue and prioritizing of said event information is based on a number of people expected to attend said event or popularity of said event.

In an example according to the second aspect of the disclosure, said association is based on geographical proximity such that at least one access node closest to the geographical location of the event is associated to said event.

In an example according to the second aspect of the disclosure, said output module is further arranged for adjusting operations, administration and management, OAM, processes for said at least one particular access node based on said predicted increase in amount of traffic in said corresponding cell.

In an example according to the second aspect of the disclosure, said OAM processes comprises at least one of failure management, preventive allocation of resources, re-planning, energy saving, and optimization.

In an example according to the second aspect of the disclosure, said node is located within a access node of said telecommunication network or located centrally in a server. It is realised that the node is an access node of the telecommunication network or the node is centrally located server unit that performs all the functions according to the present disclosure.

In accordance with the present disclosure, different aspects applicable to the above mentioned examples of the methods and the nodes, including the advantages thereof, correspond to the aspects which are applicable to the devices of the communication network

According to a third aspect of the disclosure, there is provided a computer readable storage medium comprising instructions which when loaded on to one or more nodes in a telecommunication network are arranged for performing any of the methods as explained above.

In this aspect of the disclosure, a computer readable storage medium is provided with instructions that enable a system on to which said storage media has been loaded to perform the method according to the present disclosure.

The above mentioned and other features and advantages of the disclosure 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.

