Billing process and system in a telecommunication network

The present invention relates to a billing system and a Accounting procedures to establish connections in a telecommunications network To be charged.

In the telecommunication sector, a distinction is made between the The service provider and the user. Of the Traffic provider, generally a network operator, creates with the infrastructure (Fixed and / or mobile) is the prerequisite for traffic generation. Of the Service provider can be the network operator himself or a customer of this Network operator, for example a service provider, for example a bank, the Airtime by an operator and as a Value Added Service at the Users sold. The user is a customer of a service provider. He Uses a telecommunication system and pays for the service provider Fees or a service (Value Added Service) at one Service providers.

The telecommunication process can basically be divided into two Divide segments: signaling and traffic. The present invention Refers to the classification of both segments. But since the Signaling is now hardly offset, the following is only the case Classification of the traffic segment. The traffic segment can Be divided into the following parts:

The carrier channels the traffic between the networks.

The operator operates the communications network, for example, one GSM, UMTS or IN network. He is a customer of the carrier.

The service provider is a customer of the operator and refers to the operator Communication power from him.

The user is the end user and is a customer Service provider.

The classification of transport objects, for example connections Between the carrier and the operator, is carried out with the term " Interconnection known procedures. Between operator and service provider The same process can be applied or a Known variant via a classic billingsystem. Between the Service provider and the user is traditionally a classic For example, a so-called CDR (call detail Records) based system. Each link is billed in detail.

These conventional billing systems are very dependent on the Infrastructure systems. This results in complex system interconnections. The majority of the invoices are now available on paper, via Mail Since, on the other hand, transport tariffs tend to decline massively The cost ratio yield to billing expenditure worse. Such Conventional billing systems generally do not permit any Use-related cost reductions. In addition, the Systems are only badly combined with the more important prepaid services become.

A charge and debiting of connections during or At the latest immediately after the connection is increasingly demanded, for example In Prepaid Systems. These needs, however, demand that Billing system all the details that determine the price of a connection, In real-time processing. For example, the billing system must be the same According to the connection all temporal and geographical indications about the For example the duration of the connection, the Day, the location of the caller and the called party, possible discounts Etc. during or shortly after the connection. As a result, the billing system is heavily loaded during peak periods And must be oversized. Depending on where the offsetting For example, in an operation center or a SIM card in Terminal, it is sometimes difficult to impossible at the end of the Connection to all the required data. In mobile phones For example, the CDRs required for charging a call Only 15 minutes after the end of the call.

The object of the invention is therefore to provide the technical prerequisite for A new clearing system and a new clearing system To avoid these disadvantages.

This goal is achieved with a billing system and procedure For the use of a digital Telecommunication network by a customer (operator, service provider Or users) to determine the characteristics of the independent Claims.

In particular, this objective is achieved by a clearing procedure , In which the amounts of use are calculated from a value determined in a first step Memory area. The customer profile is made up of one or more random variables from previous Connections of the customer. After new customer connections The stored customer profile is derived dynamically.

This can cause a delay during or even before the connection Forecast about the connection costs. These Settlement costs can be calculated and debited directly become.

In a simple embodiment of the invention, Customer profile simply one from the previous connections of the customer Average price per call. Preferably, however, Customer profile more statistical information about the behavior of the customer, For example information about the duration of the customer's connections. The Customer profile can include, for example, the number of connections in Predefined continuous classes, and / or the mean value and the Spread of the customer's connection time. Thus, for example, the Amount for the next connection can also be determined from trends.

The customer profile can also include multidimensional functions of Random variables from previous connections of the customer of the digital Telecommunication network. For example, the customer profile Information on the average duration of a customer 's call Function of the daytime. If the billing system then notes, That a certain customer often longer in the evening than in the morning or longer On Sunday as during the working week, the next Connections then as a function of the time of day and / or of the Weekdays.

The usage amounts are also derived from one in a second Memory area. The Total customer profile is made up of one or more random variables of Earlier connections from at least one group of users of the Digital telecommunication network and is dynamically adapted. The statistical system load can be obtained from the total customer profile From which the usage amounts depend. The random variables, the To derive the total customer profile Preferably the connection time, the day time, the weekday, and / or Geographical characteristics of previous connections.

In this way, the usage amounts that can be used for new Connections arise when creating the connection from the Dynamic customer profile To be debited. Preferably, however, these amounts are previously recorded at the User, whereby the user has the possibility to make the If the price is too high.

The usage amounts can be used in this way Telecommunication terminal, for example, in a fixed or mobile Telephone. The terminal in this case contains a third Storage area which stores a prepaid money amount, as well as means To debit or recharge the money. This possibility is already in the GSM mobile device under the term advice-of-charge (AOC). The According to the invention, also includes a processor for switching off One or more random variables from previous customer connections A dynamic customer profile and in a first memory area And to retrieve from the stored dynamic customer profile the Amount for new connections and to increase this amount at the Create a connection directly from the third storage area To charge The amounts determined for new connections Can be displayed on the display of the device. The Use amounts are also preferably derived from a second one Memory area , Wherein the total customer profile consists of one or more Random variables of previous connections of at least one group of Users of the digital telecommunication network.

The terminal may, for example, contain a chip card, e.g. For example, a SIM card containing storage means and processing means To implement the accounting method according to the invention. The However, according to the invention, the process according to the invention can be carried out in a similar manner Billing system used to determine telecommunications network usage amounts Is intended to be realized, or in any Programmable device. The programmable device Preferably with one stored on a data carrier Computer program controlled.

According to the invention, the utilization amount for a connection Or signaling not by the random variables of this connection, such as Duration, time or distance, but by a customer profile, Based on random variables (all) of previous customer connections Has been determined. For example, the cost of the next connection Based on the average value of the duration of all previous customer connections be determined. The cost of the connection can already be done in this way During a connection or even before the connection is made Without waiting for the end of the connection. The cost can For example a prepaid card or a bank account. Of the Signaling traffic can thus be simplified since the Signaling information need not be transmitted in the real-time, But can be communicated later, after which the changes in the Customer profile of the user.

The usage amount also preferably depends on one With the help of random variables of all (all) previous connections of all users Determined dynamic total customer profile, or at least one Group of users. The rating can also be dynamic to the load Of the system.

This process can not be just between a service provider And the user, but also between one Service provider and a user, or between a carrier and a Operator, or between an operator and a service provider. In this In the latter case, the service provider is regarded as the customer of the operator, and The customer profile is made up of one or more random variables from previous Connections of the service provider. The amounts of use which the Service providers are billed periodically in this case This customer profile.

Although only one embodiment is described in the following description In the special case of classification in a GSM network The method according to the invention also for a different mobile radio network, Example of a UMTS or IN network or for a fixed network, inter-, intranet, extranet Or for other telecommunications systems.

The invention will be described by way of example as follows Better understood, and by the accompanying figures, Which show:<ul><li>FIG. 1 is a perspective view of a terminal device, FIG The method according to the invention can be used,</li><li>FIG. 2 shows the statistical total customer traffic distribution, FIG Can be stored in a second memory area, </li><li>FIG. 3 shows the statistical customer traffic distribution shown in FIG First memory area can be stored,</li><li>FIG. 4 shows the overall system load and the load The customer, both as a function of the time of day</li><li>FIG. 5 is a flow diagram of the clearing method.</li></ul>

FIG. 2 shows the statistical total customer traffic distribution, Which is derived from all connections of all customers. The curve shows the Number of connections as a function of the duration of the connections. From this Curve, the mean value t_Gkp And the scattering S_Gkp To determine; Example is an average value t_Gkp Of 80 sec and a scatter S_Gkp From 35 sec. Within t_Gkp + 2S_Gkp Are 95% of all compounds in the temporal behavior detected.

Other random variables of customers' According to application, individually or jointly used, for example the Connection times, the times, the weekday, the holidays, the Distances (national / national, national / international, international / international) And / or the location (from the A-subscriber and / or the B-subscriber). The For example, stored in a memory area Can preferably include one or more statistical variables Such as mean, spread, class, moving average, distribution in Predefined classes, etc. of the total customer traffic distribution. The The overall customer profile is preferably dynamic after each connection or connection Regularly, for example daily or weekly.

From this total customer profile, the earnings figures (mean Time per link and average yield per link). These Revenue figures are decisive for the individual service user.

Every customer has their own customer profile. The customer profile of a New customer is based on the overall customer profile. The amount to be charged Amount for a new connection will be during or even before this Connection from the customer profile is prognosticated and possibly the same Off After each connection, the customer profile is displayed according to a Suitable algorithm, according to FIG. 5 Terminated connection longer or shorter than the mean value t_Kp, That will be Statistical customer profile. Thus the amounts for the Next customer connections.

The amounts billed to the customer are determined by the According to the invention Sufficient number of connections and if the interest is not considered become. Therefore, the method and system of the present invention is independent From the pricing policy of the carrier, network operator or service provider.

FIG. 3 shows the customer traffic distribution for a Certain customers who are made from all connections between a Service provider and specific users (or between an operator And a service provider as a customer). In this case, the Curve the number of connections of the customer as a function of the duration of the Links. The customer profile can be derived from this curve with the mean value T_Kp And the scattering S_Kp determine. The customer profile, which is also in one Storage area can be stored, preferably includes one or more Several statistical variables, such as mean value, spread, class, sliding Average, distribution to predefined classes, etc Customer traffic distribution. In the simplest embodiment, the Customer profile only the average price per connection for this Clients. In a preferred embodiment, the customer profile includes As well as the duration of the customer 's connections, Example the mean value and the spread of this duration. Preferably But the customer profile more information about this duration, for example, too The distribution into predefined classes, and other random variables of Connections, making the cost of the next connections reliable Can be prognosticated. Preferably, these specifications Multi-dimensional registered, so that, for example, the customer profile data About the usual behavior of the customer as a function of the time of the day And / or of the weekday, for example, the dynamic Pricing in the morning other than in the afternoon, According to the habits of the customer.

If the clearing process is carried out directly in a terminal, Example in a mobile phone 1, performed, the dynamic Customer profile in a first memory area 101, preferably on the SIM chip card 10, are stored. For example, the customer profile can be In a second storage area 102. Of the Chip card processor 100 determines the following after each new connection Dynamic customer profile as a function of one or more Random variables, and determines from the stored dynamic Customer profile and possibly the total customer profile the usage amount For new connections.

If the card contains a third memory area that contains a Prepaid money amount, this amount can be used before or During the connection directly from this storage area. In a variant, the usage amount is debited to a bank account, or, If the card has Trusted Third Party features on the card Electronically signed and encrypted and on a corresponding account To be debited. This is, for example, possible when the card is a GSM SIM card , Which has the functions of the GSM 11.14 and the patent document EP689368. With these functions it is Possible to read time elements from the map, as a basis for the calculation Of the customer profile.

The customer profile is preferably dynamic after each Connection or regularly corrected or adjusted. It is not necessary, however, That this customer profile is adapted in real time. This allows the The statistical customer profile If it is less stressed, for example outside the Peaks, and does not need to process connection details In real-time. This adjustment can be for example On the basis of GSM-area under the term CDR (Call Detail Records) Known connection details, which are also used today for the settlement in the Different levels are used; the Connection details do not need to be connected to the device during the connection Billing system.

The invoicing can be carried out in a billing system that: For example in a company center, in the terminal or in a SIM card in the Telecommunications network.

Statistically can also be used in a system which runs over the day Average system load B_Gkp determine. FIG. 4 shows The number of connections from all service users as a function of time (Daytime load of the system). For example, a daily discount can be This system load is derived and via the customer 's website System usage. For example, the amount of transport to be paid After system utilization. For example, from the Customer profile, the customer is averaged by time x_KpTelephoned, with a small spread S, he can get from a daily discount Benefit when x_Kp A time with a small system load.

Analogous to this process can be the amount of traffic to be paid Can also be determined for all other random variables mentioned above. Customer profiles of individual customers can lead to group profiles of friends and family Families, companies, and so on.

Statistical discounts (moving the statistical elements to Of the time axis) can also be applied.

The invention may, for example, be provided by a service provider Which sells services outside the telecommunications sector (Eg a financial services provider), and connections as a value-added service sold. With the present invention the calculation of Subscriptions and transport costs to service users much easier.

The present invention therefore allows compounds to be prepared in advance (Debits instead of ordinary credit clearing systems). In order to The fraud can be massively reduced.

Text of the flow chart on FIG<dl tsize="2"><dt>20</dt><dd>Save the customer profile as a customer profile T_Kp : = T_Gkp S_Kp . = S_Gkp</dd><dt>21</dt><dd>Create a connection</dd><dt>22</dt><dd>Allocation of the usage amount from the customer profile</dd><dt>23</dt><dd>Amount of use&gt; available money amount?</dd><dt>24</dt><dd>Connection not established</dd><dt>25</dt><dd>Connected; End of the connection</dd><dt>26</dt><dd>Determination of random variables of the connection: duration t, etc.</dd><dt>27</dt><dd>Derivation of a new customer profile, with random variables The last connection T_Kp : = F (t_Kp, T), ..</dd></dl>