Refarming GSM Spectrum.indd

INTERCONNECT COMMUNICATIONSA Telcordia Technologies Company

John BerryInterConnect Communications

Refarming GSM Spectrum Achieving Equity and Objectivity when Assessing Mobile Operator Allotments

EBITDA

CostSites

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Refarming GSM Spectrum - Achieving Equity and Objectivity when Assessing Mobile Operator Allotments ii

© InterConnect Communications 2009

Written and published by: InterConnect Communications Ltd Merlin House Station Road Chepstow Monmouthshire NP16 5PB United Kingdom

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Copyright ©: InterConnect Communications Ltd 2009

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Note: This document is intended only as a discussion of selected issues relating to the subject matter. It is neither a definitive statement nor a legal document, nor does it purport to suggest any detailed commercial strategy. For this reason, readers are advised to liaise with the appropriate authorities and, if necessary, seek suitable legal and/or technical advice prior to making business decisions. Whilst InterConnect Communications Ltd has exercised every care in the preparation of this document, no responsibility can be accepted for any omissions or errors contained herein.

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Synopsis

The present paper addresses the problem faced by many National Regulatory Authorities as they seek to re-farm the spectrum in the 900MHz and 1800MHz bands currently in use by mobile networks using the GSM standard in order that it may be usable for services using the IMT family of standards. Within this standards transition there are many complexities, both economic and legal. Spectrum access rights were granted as long ago as 1980 to some existing mobile network operators. They may be reluctant to lose these rights without some compensatory allocation and they certainly would want to know that they were being treated equitably. After all, they have been operating networks for many years and would not want to lose competitive advantage over a new operator just entering the market.

On the positive side the problem can be modelled. This paper discusses a model that makes use of subscriber and service data to generate traffic. It considers propagation and computes cell sizes. It then brings the traffic and the propagation together to compute the number of sites needed considering various amounts of spectrum used. Ultimately it allows the NRA spectrum manager to evaluate an almost limitless set of scenarios such that his decision making might be suitably informed and objectively made. All IMT bands are considered though the focus is on 900MHz, 1800MHz and 2100MHz. The model is set up to work using the specifics of a single country, its landmass, population and demography.

The model has as its basis Recommendation ITU-R SM.1390 and Report ITU-R SM.2023. It uses these to uniquely address the spectrum manager’s dilemma: how much do I take from X to give to Y, what will both parties’ network costs be in the event of the change and how much should I give X as compensation. As such it is different from other models produced from larger studies such as WINNER and SPECULATOR.

Refarming GSM Spectrum - Achieving Equity and Objectivity when Assessing Mobile Operator Allotments 1


Introduction

At the time of writing, mobile operators and spectrum managers are addressing the prospect of migrating spectrum allocated in the 1980s for second generation mobile services using, amongst others, the GSM standard. World Radio Conferences have designated the 900MHz and 1800MHz bands used for GSM as ‘IMT’, for use by the evolving family of new standards of IMT-2000 and IMT-Advanced. Incumbent mobile network operators (MNOs) have been using the GSM spectrum for many years. They have extensive infrastructure in place and have been evolving their services from voice through to circuit switched data. Meanwhile, they have also been participating in auctions and other spectrum acquisition to obtain allocations in the 3G 2100MHz band to permit enhanced services leading to high speed packet access, allowing data throughputs of up to 14.4Mb/s and beyond.

This state of affairs shows that the industry is driving forward in 3G, but there is nevertheless a history that regulators need to manage carefully. Recent efforts on the part of some spectrum regulators to claw back GSM spectrum and re-farm it have been met with legal challenge by MNOs as they fight to retain rights granted when the current mobile market explosion was in its infancy. Arguments can be made for re-farming: GSM operators have allocations that are sub-multiples of 5MHz, making use by 3G services using W-CDMA difficult and also propagation properties of the GSM bands help reduce costs by allowing long distances between base stations and subscribers when serving rural communities. In search of equality therefore, regulators might seek to re-balance allocations. If they do, objectivity is needed in order to navigate this complex legal and regulatory minefield.

This paper takes the view that a spectrum regulator would want to know their options in re-farming. Whether - ultimately - they are motivated to actually take action is a separate issue. Having options means knowing the result of any re-balancing of allocations across the bands from 900MHz through to 2100MHz before discussions begin. This paper discusses how this objectivity might be achieved and suggests use of a tool to model outcomes, thereby allowing many ‘what-if’ questions to be asked.



Background

There are three spectrum allocations that are of specific interest: 900MHz, 1800MHz and 2100MHz. The situation varies country-by-country but, for most, there is a pair of spectrum blocks 35MHz-wide at 900MHz, a pair of 75MHz-wide blocks at 1800MHz and a pair of 70MHz-wide blocks at 2100MHz. In all, there is about 180MHz of spectrum available as paired spectrum (termed 2 x 180MHz), capable of supporting mobile networks using frequency division duplex operation. There are other bands but, whilst the principles discussed in this tool can be applied to these too, the situation is simplified here to discuss the re-farming of GSM as the primary regulatory question.

Most countries have between two and four MNOs. Most countries have allocated all spectrum resource in the 900MHz band. Some have allocated 1800MHz, though large parts of this band remain fallow. And many countries are just beginning the process of releasing the 2100MHz band. The 900MHz band has some attractive properties; when an MNO seeks to meet coverage targets (when not traffic limited), fewer base station sites are needed. In a mixed urban-rural country, therefore, every MNO would ideally like some 900MHz spectrum. This advantage diminishes when operating in urban areas and here sheer volume of spectrum will be needed in the future, making 1800MHz and 2100MHz attractive. Any method of re-farming, therefore, needs to be able to model network deployment, postulate various mixes of block size and band, and to calculate operator return on investment in each case as fixed and variable costs change in line with site count.

If regulatory action were to be considered, most spectrum regulators would want to have objective evidence on hand to support decisions and most would want to behave equitably to both existing and new MNOs. It is with this background that InterConnect Communications has worked to aid the regulatory task.

Link Between Spectrum and Site Count

This concept is easily explained using the physical channels of GSM, each supporting one Erlang of traffic. It is well established that, for a given network deployment comprising radio sites, and where for example these sites have an omni-directional coverage to subscribers moving around the site, the coverage footprint and the traffic served can be calculated for a given number of channels deployed at the site. If more traffic is to be served, this needs either more channels at the single site or the re-use of the channels at other new sites, in which case the site count grows. If we fix the traffic then there is an inverse relationship between the number of channels and the number of sites; if we have very few channels, we need a lot of sites and if we want few sites, we have to allocate many channels.



It is true that one cannot just increase the number of sites at which channels are re-used because interference would become rife. When re-using spectrum, the cell radius must be reduced to maintain the required signal-to-noise ratio. This further plays on the number of sites needed.

This shows that there is a negative relationship between site count and spectrum allocated for a given traffic.

Defining the Task

MNOs are in business to make profit. Their shareholders make capital available and expect a return. What that return is depends on many things. Traditionally in the early 2000s in Europe, MNOs made up to 55% EBITDA. More recently as average revenue per user fell, this has reduced to between 20% and 40%. The weighted average cost of capital, a measure of the minimum return expected given the risk and opportunity cost return, is typically somewhere between 12% and 20% and so supernormal profits are being made. It is possible to model multiple MNO business cases to determine the EBITDA returned year by year (and indeed InterConnect has models set up for just that). Spectrum regulators could elect that any re-farming should permit at least normal profits to be made and could set a benchmark EBITDA to use in modelling. This would require the regulator to make a value judgement on what a reasonable return was to be. It would also require the regulator to set the services to be offered and tariffs to be charged. The task is achievable but is fraught with controversy.

Within the Eurpoean Union, the concept of the ‘efficient operator’ is well established. Effectively, this is the cost side of the EBITDA argument. The concept here is that the cost per subscriber falls as the efficiency rises. This would mean that an efficient operator would deploy only those base stations essential to meet his business needs, yielding a downward sloping cost curve. If the cost of spectrum were to be added to this cost curve, a point of inflection would be realised where the cost of base stations balanced the cost of spectrum. The point of inflection would show the optimum site count for spectrum block size for a given market share in each band. Superficially, this appears an attractive solution until one considers the various arguments that could be put to reduce the accuracy of the cost calculations. The graphical concept behind this model is shown in Figure 1 overleaf.



To calculate EBITDA needs revenue and costs. To calculate the cost point of inflection needs accurate costs. Both have attraction but both also have problems. What is common, however, is the dependent variable of site count. Both models make use of the relationship between site count and quantity of spectrum needed to serve a given market share. This shows a way of removing the argument about revenue and cost and centring on a new currency that is commonly understood: the number of sites and at these sites, the number of sectors used to serve a given subscriber base drawing a given traffic.

The model needs to take in real subscriber data for the country concerned. It needs to consider the services that an MNO might offer and from that derive the traffic likely to be generated. The model needs to dimension the cell size considering the varying urbanisation across the nation-state. From these parameters a graph is needed that relates site count versus spectrum allocated for a given subscriber base.



Defining the Task

MNOs are in business to make profit. Their shareholders make capital available and expect a return. What that return is depends on many things. Traditionally in the early 2000s in Europe MNOs made up to 55% EBITDA. More recently as average revenue per unit fell, this has reduced to between 20% and 40%. The weighted average cost of capital, a measure of the minimum return expected given the risk and opportunity cost return, is typically somewhere between 12% and 20% and so supernormal profits are being made. It is possible to model multiple MNO business cases to determine the EBITDA returned year by year (and indeed InterConnect has models set up for just that). Spectrum regulators could elect that any re-farming should permit at least normal profits to be made and could set a benchmark EBITDA to use in modelling. This would require the regulator to make a value judgement on what a reasonable return was to be. It would also require the regulator to set the services to be offered and tariffs to be charged. The task is achievable but is fraught with controversy.

Within the EU the concept of the ‘efficient operator’ is well established. Effectively this is the cost side of the EBITDA argument. The concept here is that the cost per subscriber falls as the efficiency rises. This would mean that an efficient operator would deploy only those base stations essential to meet his business needs yielding a downward sloping cost curve. If the cost of spectrum were to be added to this cost curve, a point of inflection would be realised where the cost of base stations balanced cost of spectrum. The point of inflection would show the optimum site count for spectrum block size for a given market share in each band. On the face of it this appears an attractive solution until one considers the various arguments that could be put to reduce the accuracy of the cost calculations. The graphical concept behind this model is shown in Figure 1 below.

Figure 1: Cost Model and Point of Inflection in Total Cost Suggesting Optimal Spectrum Quantity

To calculate EBITDA needs revenue and costs. To calculate the cost point of inflection needs accurate costs. Both have attraction but both have problems. What is however common is the dependent variable of site count. Both models make use of the relationship between site count and quantity of spectrum needed to serve a given market share. This shows a way of removing the

Figure 1 - Cost Model and Point of Inflection in Total Cost Suggesting Optimal Spectrum Quantity

argument about revenue and cost and centring on a new currency that is commonly understood: the number of sites and at these sites, the number of sectors used to serve a given subscriber base drawing a given traffic.

The model needs to take in real subscriber data for the country concerned. It needs to consider the services that an MNO might offer and from that derive the traffic likely to be generated. The model needs to dimension the cell size considering the varying urbanisation across the nation-state. From these parameters a graph is needed that relates site count versus spectrum allocated for a given subscriber base.

Figure 2: Site Count Versus Spectrum Quantity

This last point of subscriber base or market share needs some explanation. We have three spectrum bands: 900MHz, 1800MHz and 2100MHz. Each has specific attributes and probably each operator would want some of each band. If this is the case, we need to be able to determine the volume of subscribers that might be serviced and with what on each band. Without this no calculation of sites can be made for that MNO and band. The idea of market share therefore describes the likely share of the services that might make use of a given band. The model makes use of market share but makes no attempt to discuss how the market share is derived. It is simply a way of acting on the subscriber base to set the traffic for the site calculation in hand.

In search of objectivity and equity in evaluating MNO allocations, InterConnect rejected both EBITDA and cost modelling to settle on a new currency; sites. Once sites are known, costs can be apportioned and revenues set to return to the more controversial measures. This paper goes on to discuss how site count, spectrum and market share play together in an MNO’s business.

So How Does the Model Work?

The above introduction illustrated that the first thing needed is the population and the traffic that this population generates. Most countries do have reasonably accurate population statistics available though these need to be modified both for the market penetration of mobile phones and for the transitory flow of population across the business day and geographically. A useful starting point on the traffic is to determine the current services demanded on GSM and its evolutions such as EDGE. For the present description, the model considered the services set out in ITU-R

Figure 2 - Site Count versus Spectrum Quantity

This last point of subscriber base or market share needs some explanation. We have three spectrum bands: 900MHz, 1800MHz and 2100MHz. Each has specific attributes and probably each operator would want some of each band. If this is the case, we need to be able to determine the volume of subscribers that might be serviced and with what on each band. Without this, no calculation of sites can be made for that MNO and band. The idea of market share, therefore, describes the likely share of the services that might make use of a given band. The model makes use of market share but makes no attempt to discuss how the market share is derived. It is simply a way of acting on the subscriber base to set the traffic for the site calculation in hand.

In search of objectivity and equity in evaluating MNO allocations, InterConnect rejected both EBITDA and cost modelling to settle on a new currency; sites. Once sites are known, costs can be apportioned and revenues set to return to the more controversial measures. This paper goes on to discuss how site count, spectrum and market share play together in an MNO’s business.

So How Does the Model Work?

The above introduction illustrates that the first items of data needed are the population and the traffic that this population generates. Most countries do have reasonably accurate population statistics available, though these need to be modified both for the market penetration of mobile phones and for the transitory flow of population across the business day and geographically. A useful starting point on the traffic is to determine the current services demanded on GSM and its evolutions such as EDGE. For the present description, the model considered the services set out in ITU-R Recommendation SM.1390: speech, simple messaging and circuit switched data. For 3G services, medium multimedia, high multimedia and interactive multimedia are added.

There are two conditions in cell planning: coverage limited and traffic limited. Coverage limited is where the traffic within the coverage footprint of a single site is easily served and the grade of service met. Cells are concatenated to provide landmass coverage. Generally this is the case only in rural areas of the country. Traffic limited is where more than one base station site is needed within the normal cell coverage footprint in order to service the traffic. In this case the cell size depends not on propagation but on the traffic density. There are five useful parameters needed in traffic specification: penetration rate for the service in question, busy hour call attempts, call durations, net user data rates in kb/s and activity factors. Each needs to be specified in both rural and urban areas.



The limiting range for the different services is still set by propagation and it is essential that a correct path budget is prepared and used in the model for GSM and 3G services as well as for the services offered. This means also that the signal received in both downlink and uplink is calculated. The COST 231 Hata model is the most useful in this case since it can be coded and used in MS Excel. The cell radius can be calculated for differing urbanisation by simply designating a cell ‘urban’ or ‘rural’ and switches set in the propagation model to suit. Similarly, load balancing equations are used to determine the ability of a site to actually handle the data required, considering the limiting Eb/N0 for the service concerned.

Using W-CDMA technology, 3G mobiles all occupy the same spectrum, separated by codes assigned to transmission. This means that each mobile generates an interfering signal to all others and this is accounted for in the path budget using an interference margin, itself a function of the traffic level. Similarly, gains from soft and softer handover need to be accounted for. These parameters complete the set and the tool is nearly ready to be used to dimension a cellular network.

One thing remains: net system capability. The various parameters above allow the required bit rate per cell (in b/s/cell) to be calculated. If we know from the vendor technology the net system capability in b/s/Hz/cell, then dividing one by the other



Figure 3 - The Various Parameters of the Model

user data rates in kb/s and activity factors. Each needs to be specified in both rural and urban areas.

• Services

• Path Budget

• Traffic

• Cell Dimensioning

• Population

So how might this analysis work...

yields the Hz or spectrum needed. One could imagine that this factor might available. Sadly this is not the case. It does depend on many factors. Report ITU-R SM.2023 recommends that this factor is determined empirically though perhaps this requires the ‘chicken to come before the egg’. Report SM.2023 does, however, give some seed values which are useful.

At the heart of the model, therefore, is a family of curves that relate site count to quantity of spectrum allocated for a given traffic or market share and design rules (such as the technology). Once computed the scene is set for modelling.

User Interface and the Inputs and Outputs

There are three levels of data used in this model. The first is the hard coded stuff such as the propagation model and the interference margin. This can be modified but it is unlikely to be changed unless the technology changes. The second is the ‘firmware’: data that is set for the nation-state in question and for the services offered. This can be changed readily but is unlikely to be changed by the regulatory authority user. The third is the input data to ask ‘what if?’. This will be changed continuously in search of objective evidence for change.

The simplicity of this last data category leads to a very simple user interface shown conceptually in Figure 5 overleaf. The input on the left is set up to specify the MNO name, the spectrum block allotted to him in each band, and the market share of services that he is likely to capture in each band. The output is the site count for each operator in each band.



Figure 4 - Family of Curves

Figure 4: Family of Curves

Concept: Spectrum versus Site Count

Summary and Conclusion

There is a need to estimate the amount of spectrum needed for various services as mobile networks evolved from GSM (2G) through 3G and on to the so-called but ill-defined Long Term Evolution. There have been various studies under the banners of WINNER and SPECULATOR1, giving names to elaborate tools developed. These tools were used to calculate that around 500MHz is needed in developed countries to support IMT-2000 services but that an astronomical 1700MHz of spectrum will be needed to support IMT-Advanced services. WINNER and SPECULATOR are publicly available.

This paper describes a method and a tool. This tool does not aim to replace these international tools but rather seeks to answer a different but related question: if a regulator were to want to enter discussions with MNOs in its nation-state about re-farming the GSM spectrum whilst considering other allocations in the 2100MHz band, what would the costs be. Cost is described in this InterConnect tool by site count, a proxy for cost in the currency of the nation-state.

1 Takaqi T and Walke B H (eds) 2008, Spectrum Requirement Planning in Wireless Communications Model and Methodology for IMT-Advanced, pp60-64, John Wiley and Sons Ltd, London, England.



Figure 5 - Inputs and Outputs

Inputs and outputs...

Consulting in communications regulation & strategy

Band Op. A Op. B Op. C

900 2 x 12.5MHz

2 x 10MHz

0

Share 53% 30%

1800 0 0 2 x 20MHz

Share 60%

2100 2 x 10MHz

2 x 20MHz

2 x 10MHz

Share 47% 70% 30%

Operator/Market Share

Calculate

Figure 5: Inputs and Outputs

Summary and Conclusion

There is a need to estimate the amount of spectrum needed for various services as mobile networks evolved from GSM (2G) through 3G and on to the so-called but ill-defined Long Term Evolution. There have been various studies under the banners of WINNER and SPECULATOR, giving names to elaborate tools developed. These tools were used to calculate that around 500MHz is needed in developed countries to support IMT-2000 services but that an astronomical 1700MHz of spectrum will be needed to support IMT-Advanced services. WINNER and SPECULATOR are publically available.

This paper describes a method and a tool. This tool does not aim to replace these international tools but rather seeks to answer a different but related question: if a regulator were to want to enter discussions with MNOs in its nation-state about re-farming the GSM spectrum whilst considering other allocations in the 2100MHz band, what would the costs be. Cost is described in this InterConnect tool by site count, a proxy for cost in the currency of the nation-state.

The figure below shows one interim output of the tool. It illustrates some things that are intuitive:

That it is possible to allocate too little spectrum such that the site count is very high. This would make the MNO’s business case unviable.

That it is possible to give too much spectrum such that the marginal cost of spectrum (in terms of the currency of sites) is too low. This would of course be wasteful.

That there is a point where if too little spectrum is awarded, the cost grow quickly.

Inputs and outputs...

The figure below shows one interim output of the tool. It illustrates some things that are intuitive:• That it is possible to allocate too little spectrum such that the site count is very high.

This would make the MNO’s business case unviable;• That it is possible to give too much spectrum such that the marginal cost of spectrum

(in terms of the currency of sites) is too low. This would of course be wasteful;• That there is a point where, if too little spectrum is awarded, the cost grows

quickly.

The quantity of spectrum needed for each market player across each of a number of bands can be computed. The model requires data for the nation-state in question and for the services and technology to be deployed. It returns a site count. By being based on real data, the results it gives are objective. It can be expanded to consider monetary cost including spectrum fees already paid. Whilst it is for the spectrum regulator to determine the rules under which the model is used, it can be used equitably to develop spectrum re-farming policy.



Figure 6 - A Core Set of Curves: Sites versus Spectrum for 30% Market Sharenote that 3G 1800 and IMT-2000 are coincident (black curve) as are GSM 900 Primary & DCS1800 and IMT-2000 900 & 3G 900 (light blue curve)

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

0 5 10 15 20 25 30 35 40 45

Site

s

Spectrum

Spectrum vs Sites

Band 1 Band 2 Band 3 Band 4 Band 5 Band 6 Band 7

Market Share = 30%

Consulting in communications regulation & strategy

IMT-2000-900

GSM 900 Primary

GSM 900 Extended 3G 900 DCS1800 3G1800 IMT-2000

Core

Figure 6: A Core Set of Curves: Sites Versus Spectrum for 30% Market Share

(note that 3G 1800 and IMT-2000 are coincident (black curve) as are GSM 900 Primary & DCS1800 and IMT-2000 900 & 3G 900 (light blue curve))

The quantity of spectrum needed for each market player across each of a number of bands can be computed. The model requires data for the nation-state in question and for the services and technology to be deployed. It returns a site count. By being based on real data the results it gives are therefore objective. It can be expanded to consider monetary cost including spectrum fees already paid. Whilst it is for the spectrum regulator to determine the rules under which the model is used, it can be used equitably to develop spectrum re-farming policy.

The Author

John Berry is InterConnect Communications’ Director of Spectrum Services and a radio communications expert with 30 years’ experience in the mobile, fixed and broadcast radiocommunications industries, military radiocommunications and in radio spectrum management. The holder of a BSc in Electrical and Electronic Engineering, a BA in European studies and an MBA majoring in technology management, John is a Chartered Engineer and a Fellow of both the Institution of Engineering and Technology and of the Chartered Management Institute. John’s role within InterConnect is to lead the development of the spectrum services

product line. In this he manages major spectrum management projects and is an active consultant across the spectrum management domain and in wireless network design and implementation.

Prior to joining InterConnect, John spent some 13 years as Managing Director of ATDI Ltd, leading a series of major radio and spectrum management consultancy and software engineering projects which contributed hugely to Europe’s telecommunications infrastructure and spectrum management policies. Prior to that, he acted as Business Unit Manager for MEL Communications (part of Thales Communications), establishing a civil products group within this military systems integrator majoring on spectrum monitoring, spectrum management and communications planning. John has also served in product development and marketing management roles for Maxon and Philips, covering product design, systems engineering and network planning.

John has presented some 60 technical papers and 20 technical/management workshops across Europe on spectrum-related topics, and is a patent holder in radio measurement techniques.

John may be contacted on +44 1291 638407 or e-mailed at [email protected]

InterConnect Communications

InterConnect Communications is a wholly-owned subsidiary of Telcordia Technologies Inc., based in the United Kingdom, and a leading provider of consultancy services on spectrum and wireless technology issues.

InterConnect has over 20 years experience in managing the radio spectrum at international, national and local levels, and has evaluated, specified, procured and implemented spectrum management and monitoring systems for all size of regulator and administration in countries across the globe. InterConnect has not just worked with numerous organisations to implement such systems but is recognised in its own right as one of the world’s leading independent experts, with knowledge of the capabilities of all manufacturers in the field. We have supported the procurement of a wide range of spectrum management (and monitoring) systems using national and World Bank procurement rules.

For more details of InterConnect’s radio spectrum services, please visit http://www.icc-uk.com/spectrum.php or e-mail us at [email protected]




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