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Cost Models for Telecommunication Networks and Their Application to GSM Systems - INTRODUCTION, COST METHODOLOGIES, FL-LRIC COST METHODOLOGY, BSC Projection Model, CONCLUSION

service prices operator services

Klaus D. Hackbarth
University of Cantabria, Spain

J. Antonio Portilla
University of Alcala, Spain

Ing. Carlos Diaz
University of Alcala, Spain


Currently mobile networks are one of the key issues in the information society. The use of cellular phones has been broadly extended since the middle 1990s, in Europe mainly with the GSM (Global System for Mobile Communication) system, and in the United States (U.S.) with the IS-54 system. The technologies on which these systems are based, Time Division Multiple Access (TDMA) and Code Division Multiple Access (CDMA) are completely developed, the networks are completely deployed and the business models are almost exhausted 1 (Garrese, 2003). Therefore, these systems are in the saturation stage if we consider the network life cycle described by Ward, which is shown in Figure 1.

At this stage, it is possible to assume that all work is over in this field. However, in this time stage there are new critical problems, mainly related with network interconnection, regulation pricing and accounting.

These types of questions are quite similar to the regulatory issues in fixed networks in the fields of Public Switched Telephone Network (PSTN), Integrated Service Data Network (ISDN) and Digital Subscriber Line (DSL) access. In the European environment, there is an important tradition in these regulatory issues, mainly produced by the extinction of the old state-dominant network operators and market liberalization. National Regulatory Authorities (NRAs) give priority to guarantee the free competition through different strategic policies that apply mainly to the following topics:

  • Interconnection and call termination prices: The most common situation is a call originated in the network of operator A, and terminates in a customer of another network operator, B. There are other scenarios, like transit interconnection, where a call is originated and terminated in the network of operator A but has to be routed through the network of operator B. In any case, the first operator has to pay some charge to the second one for using its network. The establishment of a fair charge is one of the key points of regulatory policies.
  • Universal service tariffs: In most countries, the state incumbent operator had a monopolistic advantage; hence, the prices were established by a mixture of historical costs and political issues. Currently, with market liberalization and the entry of new operators, these tariffs must be strictly observed to avoid unfair practices.
  • Retail and wholesale services (customer access): This situation deals mainly with the local loop; that is, the final access to the customer. An example is when a network operator offers physical access to the customer—the copper line in DSL access, and an Internet Service Provider (ISP) offers the Internet access.

The establishment of these prices, tariffs and other issues related with the regulatory activities requires defining cost methodologies to provide an objective framework.

The following sections present different cost methodologies applied in telecommunication networks. Furthermore, a specific model named Forward-Looking Long-Run Incremental Cost (FL-LRIC) is deeper studied. Finally, the FL-LRIC model is applied to the specific case of the GSM mobile network.


Cost methodologies must ensure that prices led to profitability, or that they at least cover the proper costs (cost-based prices). A fundamental difficulty in defining cost-based pricing is that different services usually use common network elements. A large part of the total cost is a common cost; hence, it is difficult to divide the different services. The cost-based prices must perform three conditions (Courcoubetis, 2003):

  • Subsidy free prices: each customer has to pay only for its service.
    Sustainable prices: prices should be defensive against competition.
  • Welfare maximization: prices should ensure the social welfare maximization.

Note that the three conditions could be mutually incompatible. The aim of welfare maximization may be in conflict with the others, restricting the feasible set of operating points. Several methods (Mitchell, 1991; Osborne, 1994) have been developed for the cost-based prices calculation, but they have practical restrictions; that is, the ignorance of complete cost functions. This article presents a set of practical methods for the calculation of the cost of services that fulfill the conditions mentioned.

In practice, the main problem is the distribution of common costs between services. Usually only a small part of the total cost is comprised of factors that can be attributed to a single service. The common costs are calculated, subtracting the cost imputable to each service to the total cost. There are two alternatives for the calculation of the common cost: top-down and bottom-up (see Figures 2 and 3, respectively).

In the bottom-up approach, each cost element is computed using a model of the most efficient facility specialized in the production of the single service, considering the most efficient current technology. Thus, we construct the individual cost building models of fictitious facilities that produce just one of these services. The top-down approach starts from the given cost structure of existing facilities and attempts to allocate the cost that has actually incurred to the various services.

Additionally, according to Courcoubetis (2003), a division between direct and indirect costs and fixed and variable costs should be considered. Direct cost is the part solely attributed to a particular service and will cease to exist if the service is no longer produced. Indirect costs are related only to the provision of all services. Fixed costs is the value obtained by the addition of the costs independent of the service quantity. That means these costs remain constant when the quantity of the service changes. Opposite are variable costs, because they depend on the amount of the service produced.

Several methodologies calculate the price under the previous cost definition Most relevant are the two introduced below (Taschdjian, 2001):

  • Fully Distributed Cost (FDC): The idea of FDC is to divide the total cost that the firm incurs amongst the services that it sells. This is a mechanical process; a program takes the values of the actual costs of the operating factors and computes for each service its portion. FDC is a top-down approach.
  • FL-LRIC: This is a bottom-up approach, in which the costs of the services are computed using an optimized model of the network and service production technologies.

Table 1 shows the main advantages and disadvantages of these methods.

Currently, regulation studies are mainly based on the FL-LRIC (see European Commission, 1998).


The objective of the FL-LRIC cost model is to estimate the investment cost incurred by a new hypothetical entrant operator under particular conditions. This new operator has to provide the same service briefcase as the established one. Furthermore, the new operator has to define an optimal network configuration using the most suitable technology (Hackbarth, 2002).

Using the FL-LRIC methodology, market partners can estimate the price p(A) of a corresponding service A . The underlying concepts to perform this estimation are introduced next.

The concept of Forward Looking implies performing the network design. It is considered both present and forecast future of customer demand. Furthermore, the Long Run concept means that we consider large increments of additional output, allowing the capital investment to vary.

The incremental cost of providing a specific service in a shared environment can be defined as the common cost of joint production subtracting the independent cost of the rest of the services. Therefore, if we consider two different services, A and B, the incremental cost of providing A service can be defined as Where C(A,B) is the joint cost of providing services A and B, and C(B) is the cost of providing service B independently. The methodology for implementing LRIC is based on constructing bottom-up models from which to compute C(A,B) and C(B), considering current costs 2 .

Note that the sum of the service prices calculated under the LRIC model do not cover the costs of joint production, because the term [C(A,B)-C(A)-C(B)] is usually negative. Therefore, the price of the service A, p(A) , has to be set between the incremental cost of the service LRIC and the stand-alone cost C(A).
As previously mentioned, the LRIC requires a model and the corresponding procedure to estimate a realistic network design, allowing calculation of the network investment. The next section deals with the particular application of the model to GSM mobile networks, focusing on network design, dimensioning and the corresponding cost calculation.

BSC Projection Model

The objective of this model is to obtain the number of BSCs—that is, the use factor of the BSC—by each specific type of city. Each city considered has a heterogeneous cell deployment. This means that there is not a single type of BTS providing service, but several types distributed over the city. Using the same argument, the BTS assigned to a BSC may be of different types. The optimal case to calculate the use factor of a BSC for each city happens when all BTS of the city belongs to the same type, because it is reduced to a single division. Otherwise, we have to proceed as follows: Initially, the number of BTS is obtained under the condition that the complete city area is covered by the same type of BTS, using the following equation: where the term City_Area is the extension of the city in Km 2 . Obviously, the coverage of the BTS must be expressed in the same units.

The number of BSC to provide service to the BTS previously calculated is obtained considering several restrictions, such as the number of interfaces in the BSC, the number of active connections, the maximum traffic handled by the BSC or the link and path reliability. Afterwards, the BSC use factor for the specific type of BTS in the corresponding city is calculated as follows. The total number of BSC in the city is calculated using the following equation: MSC and NSS Projection Model

The MSC and NSS projection model is based on the same concept as the projection model of the BSC as shown in Figure 5.

The first step calculates the MSC use factor, f_use_MSC BSC, by each BSC. Afterwards, using the parameter f_use_BSC BTS_i ’ the use factor of the MSC for each type of considered BTS is obtained by the multiplication of both factors. Similar procedure is performed for each network element of the NSS 4 .

The BSCs are connected to the MSC using optical rings usually based on STM-1 5 and STM-4 SDH systems. The number of BSCs assigned to each MSC is limited, between other factors, by the traffic capacity of the MSC and the number of interfaces towards the BSC. Therefore, the use factor of the MSC that corresponds to each BSC is calculated as follows: And the MSC use factor for each type of BTS is calculated using the following equation: Using this methodology, an accurate estimation of the total amount of equipment for each network element on a national level can be calculated. Obviously, it is not a real configuration, but it provides a realistic structure to calculate the unit cost under the LRIC perspective.

A real example of this model application is the comparison between the investment of three different GSM operators on a limited scenario of a medium city 6 . The operators work on different bands – the first at 900 MHz, the second at 1800 MHz and the third at a double band (900 and 1800 MHz), with different types of BTSs. Hypothetical costs are assigned to each different network element under a real perspective, which means that the results can be extrapolated to practical cases. Under these premises, the differences between the operators are shown in Figure 6. The complete example is described in Fiñana (2004).

It can be observed that the operator with the double frequency band obtains better results in terms of investment costs. Specifically, the investment cost of this operator is 46% lower than the operator at 1800 MHz and 21% lower than the operator at 900MHz. Therefore, it has a strategic advantage that the corresponding national regulatory authority might consider on the corresponding assessment process, such as the assignment of the provision of the universal service 7 (NetworkNews, 2003).


The article has exposed a relevant problem in the current telecommunication market, which is the establishment of telecommunication services prices under a free competitive market but also under the watchful eye of the national regulatory authorities. The two most relevant cost models have been introduced, with a deeper explanation about the LRIC model, which is currently the most widely accepted. The application of this cost model requires the complete design of the network under some restrictions, forecast of future demand, using the most suitable technology and so on. This article also deals with a possible methodology to apply the LRIC model to the GSM networks, with its particular characteristics. Finally, a short example of the relevance of this type of studies is shown, with the comparison between GSM operators working in different frequency bands.

Last, it is important to mention the relevance of this type of study, on one hand, because an erroneous network costing can establish non-realistic service prices. If they are too low, they will directly affect service profitability. If they are too high, they may reduce the number of customers and hence, affect profitability. On the other hand, under the regulation scope, these studies are required to fix an objective basis for establishing corresponding prices and, hence, to spur free competition, which is evidently the key for the telecommunication market evolution 8 .


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almost 6 years ago

dear sir
could you till me the price of BSC& BTS of GSM Network in the market if we say that i'm looking in the year 2008,2007
many thanks