The growth market mobile broadband business model

  • 1,550 views
Uploaded on

Presented at the 5th Annual Mobile Network Evolution Conference, Singapore 23 March 2010.

Presented at the 5th Annual Mobile Network Evolution Conference, Singapore 23 March 2010.

More in: Technology
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
No Downloads

Views

Total Views
1,550
On Slideshare
0
From Embeds
0
Number of Embeds
1

Actions

Shares
Downloads
175
Comments
0
Likes
1

Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide
  • Very often, it is claimed – especially from Femtocell equipment vendors – that Femtos enable ‘huge savings” in the macro network and only by this make the business case! So, we decided to take a closer look! Please mind: The DFP data demand (Kim Larsen) has been used as input. Further we used the Network Economic RAN and Femto cost model for this calculation. Please also mind that this is a strategic analysis, i.e. that the modelled cost increase due to traffic demand is not aligned with local budgets (click)
  • We assume that only those “heavy users” will get a Femto. (Please mind that this is an important assumption. As in reality not every heavy user is likely to accept a Femto – he may not like the concept or does not have the necessary broadband subscription– our cost saving calculations should be regarded as an upper limit ! Now we know the number of Femtos, which need to be deployed in each year. We look into the Femto cost model (click – Femto TCO curve is blinking) and get the cost of Femto deployment for each year. As even with a deployment of Femtocells, the traffic in the macro network will continue to grow, we again have to look in RAN model and calulate the increase in TCO of the Macro network compared to the base year, this time however including the offload effect of Femtos. (click – Macro TCO curve - incl. Femto – is blinking) The upgrade costs of the Macro network which occur despite Femto deployment have to be added on top of the costs of the femto deployment itself. These total costs incurred by Femtos can now be compared to the costs without Femtos (thus the Macro upgrade costs stand alone) So - (click: animation starts – bottom graph appears)
  • We assume that only those “heavy users” will get a Femto. (Please mind that this is an important assumption. As in reality not every heavy user is likely to accept a Femto – he may not like the concept or does not have the necessary broadband subscription– our cost saving calculations should be regarded as an upper limit ! Now we know the number of Femtos, which need to be deployed in each year. We look into the Femto cost model (click – Femto TCO curve is blinking) and get the cost of Femto deployment for each year. As even with a deployment of Femtocells, the traffic in the macro network will continue to grow, we again have to look in RAN model and calulate the increase in TCO of the Macro network compared to the base year, this time however including the offload effect of Femtos. (click – Macro TCO curve - incl. Femto – is blinking) The upgrade costs of the Macro network which occur despite Femto deployment have to be added on top of the costs of the femto deployment itself. These total costs incurred by Femtos can now be compared to the costs without Femtos (thus the Macro upgrade costs stand alone) So - (click: animation starts – bottom graph appears)
  • … to summarize….
  • … to summarize….
  • We assume that only those “heavy users” will get a Femto. (Please mind that this is an important assumption. As in reality not every heavy user is likely to accept a Femto – he may not like the concept or does not have the necessary broadband subscription– our cost saving calculations should be regarded as an upper limit ! Now we know the number of Femtos, which need to be deployed in each year. We look into the Femto cost model (click – Femto TCO curve is blinking) and get the cost of Femto deployment for each year. As even with a deployment of Femtocells, the traffic in the macro network will continue to grow, we again have to look in RAN model and calulate the increase in TCO of the Macro network compared to the base year, this time however including the offload effect of Femtos. (click – Macro TCO curve - incl. Femto – is blinking) The upgrade costs of the Macro network which occur despite Femto deployment have to be added on top of the costs of the femto deployment itself. These total costs incurred by Femtos can now be compared to the costs without Femtos (thus the Macro upgrade costs stand alone) So - (click: animation starts – bottom graph appears)
  • We assume that only those “heavy users” will get a Femto. (Please mind that this is an important assumption. As in reality not every heavy user is likely to accept a Femto – he may not like the concept or does not have the necessary broadband subscription– our cost saving calculations should be regarded as an upper limit ! Now we know the number of Femtos, which need to be deployed in each year. We look into the Femto cost model (click – Femto TCO curve is blinking) and get the cost of Femto deployment for each year. As even with a deployment of Femtocells, the traffic in the macro network will continue to grow, we again have to look in RAN model and calulate the increase in TCO of the Macro network compared to the base year, this time however including the offload effect of Femtos. (click – Macro TCO curve - incl. Femto – is blinking) The upgrade costs of the Macro network which occur despite Femto deployment have to be added on top of the costs of the femto deployment itself. These total costs incurred by Femtos can now be compared to the costs without Femtos (thus the Macro upgrade costs stand alone) So - (click: animation starts – bottom graph appears)
  • We assume that only those “heavy users” will get a Femto. (Please mind that this is an important assumption. As in reality not every heavy user is likely to accept a Femto – he may not like the concept or does not have the necessary broadband subscription– our cost saving calculations should be regarded as an upper limit ! Now we know the number of Femtos, which need to be deployed in each year. We look into the Femto cost model (click – Femto TCO curve is blinking) and get the cost of Femto deployment for each year. As even with a deployment of Femtocells, the traffic in the macro network will continue to grow, we again have to look in RAN model and calulate the increase in TCO of the Macro network compared to the base year, this time however including the offload effect of Femtos. (click – Macro TCO curve - incl. Femto – is blinking) The upgrade costs of the Macro network which occur despite Femto deployment have to be added on top of the costs of the femto deployment itself. These total costs incurred by Femtos can now be compared to the costs without Femtos (thus the Macro upgrade costs stand alone) So - (click: animation starts – bottom graph appears)
  • We assume that only those “heavy users” will get a Femto. (Please mind that this is an important assumption. As in reality not every heavy user is likely to accept a Femto – he may not like the concept or does not have the necessary broadband subscription– our cost saving calculations should be regarded as an upper limit ! Now we know the number of Femtos, which need to be deployed in each year. We look into the Femto cost model (click – Femto TCO curve is blinking) and get the cost of Femto deployment for each year. As even with a deployment of Femtocells, the traffic in the macro network will continue to grow, we again have to look in RAN model and calulate the increase in TCO of the Macro network compared to the base year, this time however including the offload effect of Femtos. (click – Macro TCO curve - incl. Femto – is blinking) The upgrade costs of the Macro network which occur despite Femto deployment have to be added on top of the costs of the femto deployment itself. These total costs incurred by Femtos can now be compared to the costs without Femtos (thus the Macro upgrade costs stand alone) So - (click: animation starts – bottom graph appears)
  • We assume that only those “heavy users” will get a Femto. (Please mind that this is an important assumption. As in reality not every heavy user is likely to accept a Femto – he may not like the concept or does not have the necessary broadband subscription– our cost saving calculations should be regarded as an upper limit ! Now we know the number of Femtos, which need to be deployed in each year. We look into the Femto cost model (click – Femto TCO curve is blinking) and get the cost of Femto deployment for each year. As even with a deployment of Femtocells, the traffic in the macro network will continue to grow, we again have to look in RAN model and calulate the increase in TCO of the Macro network compared to the base year, this time however including the offload effect of Femtos. (click – Macro TCO curve - incl. Femto – is blinking) The upgrade costs of the Macro network which occur despite Femto deployment have to be added on top of the costs of the femto deployment itself. These total costs incurred by Femtos can now be compared to the costs without Femtos (thus the Macro upgrade costs stand alone) So - (click: animation starts – bottom graph appears)
  • We assume that only those “heavy users” will get a Femto. (Please mind that this is an important assumption. As in reality not every heavy user is likely to accept a Femto – he may not like the concept or does not have the necessary broadband subscription– our cost saving calculations should be regarded as an upper limit ! Now we know the number of Femtos, which need to be deployed in each year. We look into the Femto cost model (click – Femto TCO curve is blinking) and get the cost of Femto deployment for each year. As even with a deployment of Femtocells, the traffic in the macro network will continue to grow, we again have to look in RAN model and calulate the increase in TCO of the Macro network compared to the base year, this time however including the offload effect of Femtos. (click – Macro TCO curve - incl. Femto – is blinking) The upgrade costs of the Macro network which occur despite Femto deployment have to be added on top of the costs of the femto deployment itself. These total costs incurred by Femtos can now be compared to the costs without Femtos (thus the Macro upgrade costs stand alone) So - (click: animation starts – bottom graph appears)
  • We assume that only those “heavy users” will get a Femto. (Please mind that this is an important assumption. As in reality not every heavy user is likely to accept a Femto – he may not like the concept or does not have the necessary broadband subscription– our cost saving calculations should be regarded as an upper limit ! Now we know the number of Femtos, which need to be deployed in each year. We look into the Femto cost model (click – Femto TCO curve is blinking) and get the cost of Femto deployment for each year. As even with a deployment of Femtocells, the traffic in the macro network will continue to grow, we again have to look in RAN model and calulate the increase in TCO of the Macro network compared to the base year, this time however including the offload effect of Femtos. (click – Macro TCO curve - incl. Femto – is blinking) The upgrade costs of the Macro network which occur despite Femto deployment have to be added on top of the costs of the femto deployment itself. These total costs incurred by Femtos can now be compared to the costs without Femtos (thus the Macro upgrade costs stand alone) So - (click: animation starts – bottom graph appears)
  • We assume that only those “heavy users” will get a Femto. (Please mind that this is an important assumption. As in reality not every heavy user is likely to accept a Femto – he may not like the concept or does not have the necessary broadband subscription– our cost saving calculations should be regarded as an upper limit ! Now we know the number of Femtos, which need to be deployed in each year. We look into the Femto cost model (click – Femto TCO curve is blinking) and get the cost of Femto deployment for each year. As even with a deployment of Femtocells, the traffic in the macro network will continue to grow, we again have to look in RAN model and calulate the increase in TCO of the Macro network compared to the base year, this time however including the offload effect of Femtos. (click – Macro TCO curve - incl. Femto – is blinking) The upgrade costs of the Macro network which occur despite Femto deployment have to be added on top of the costs of the femto deployment itself. These total costs incurred by Femtos can now be compared to the costs without Femtos (thus the Macro upgrade costs stand alone) So - (click: animation starts – bottom graph appears)
  • We assume that only those “heavy users” will get a Femto. (Please mind that this is an important assumption. As in reality not every heavy user is likely to accept a Femto – he may not like the concept or does not have the necessary broadband subscription– our cost saving calculations should be regarded as an upper limit ! Now we know the number of Femtos, which need to be deployed in each year. We look into the Femto cost model (click – Femto TCO curve is blinking) and get the cost of Femto deployment for each year. As even with a deployment of Femtocells, the traffic in the macro network will continue to grow, we again have to look in RAN model and calulate the increase in TCO of the Macro network compared to the base year, this time however including the offload effect of Femtos. (click – Macro TCO curve - incl. Femto – is blinking) The upgrade costs of the Macro network which occur despite Femto deployment have to be added on top of the costs of the femto deployment itself. These total costs incurred by Femtos can now be compared to the costs without Femtos (thus the Macro upgrade costs stand alone) So - (click: animation starts – bottom graph appears)
  • We assume that only those “heavy users” will get a Femto. (Please mind that this is an important assumption. As in reality not every heavy user is likely to accept a Femto – he may not like the concept or does not have the necessary broadband subscription– our cost saving calculations should be regarded as an upper limit ! Now we know the number of Femtos, which need to be deployed in each year. We look into the Femto cost model (click – Femto TCO curve is blinking) and get the cost of Femto deployment for each year. As even with a deployment of Femtocells, the traffic in the macro network will continue to grow, we again have to look in RAN model and calulate the increase in TCO of the Macro network compared to the base year, this time however including the offload effect of Femtos. (click – Macro TCO curve - incl. Femto – is blinking) The upgrade costs of the Macro network which occur despite Femto deployment have to be added on top of the costs of the femto deployment itself. These total costs incurred by Femtos can now be compared to the costs without Femtos (thus the Macro upgrade costs stand alone) So - (click: animation starts – bottom graph appears)
  • We assume that only those “heavy users” will get a Femto. (Please mind that this is an important assumption. As in reality not every heavy user is likely to accept a Femto – he may not like the concept or does not have the necessary broadband subscription– our cost saving calculations should be regarded as an upper limit ! Now we know the number of Femtos, which need to be deployed in each year. We look into the Femto cost model (click – Femto TCO curve is blinking) and get the cost of Femto deployment for each year. As even with a deployment of Femtocells, the traffic in the macro network will continue to grow, we again have to look in RAN model and calulate the increase in TCO of the Macro network compared to the base year, this time however including the offload effect of Femtos. (click – Macro TCO curve - incl. Femto – is blinking) The upgrade costs of the Macro network which occur despite Femto deployment have to be added on top of the costs of the femto deployment itself. These total costs incurred by Femtos can now be compared to the costs without Femtos (thus the Macro upgrade costs stand alone) So - (click: animation starts – bottom graph appears)
  • We assume that only those “heavy users” will get a Femto. (Please mind that this is an important assumption. As in reality not every heavy user is likely to accept a Femto – he may not like the concept or does not have the necessary broadband subscription– our cost saving calculations should be regarded as an upper limit ! Now we know the number of Femtos, which need to be deployed in each year. We look into the Femto cost model (click – Femto TCO curve is blinking) and get the cost of Femto deployment for each year. As even with a deployment of Femtocells, the traffic in the macro network will continue to grow, we again have to look in RAN model and calulate the increase in TCO of the Macro network compared to the base year, this time however including the offload effect of Femtos. (click – Macro TCO curve - incl. Femto – is blinking) The upgrade costs of the Macro network which occur despite Femto deployment have to be added on top of the costs of the femto deployment itself. These total costs incurred by Femtos can now be compared to the costs without Femtos (thus the Macro upgrade costs stand alone) So - (click: animation starts – bottom graph appears)
  • … to summarize….
  • Thank you very much….
  • We assume that only those “heavy users” will get a Femto. (Please mind that this is an important assumption. As in reality not every heavy user is likely to accept a Femto – he may not like the concept or does not have the necessary broadband subscription– our cost saving calculations should be regarded as an upper limit ! Now we know the number of Femtos, which need to be deployed in each year. We look into the Femto cost model (click – Femto TCO curve is blinking) and get the cost of Femto deployment for each year. As even with a deployment of Femtocells, the traffic in the macro network will continue to grow, we again have to look in RAN model and calulate the increase in TCO of the Macro network compared to the base year, this time however including the offload effect of Femtos. (click – Macro TCO curve - incl. Femto – is blinking) The upgrade costs of the Macro network which occur despite Femto deployment have to be added on top of the costs of the femto deployment itself. These total costs incurred by Femtos can now be compared to the costs without Femtos (thus the Macro upgrade costs stand alone) So - (click: animation starts – bottom graph appears)

Transcript

  • 1. The growth market broadband business model 5th Annual Mobile Network Evolution Conference, Singapore 23 March 2010. Dr. Kim Kyllesbech Larsen International Network Economics, Technology, T-Mobile.
  • 2. Story.
    • Broadband evolution.
    • Europe usage trends.
    • Growth markets.
    • Demand and spectrum.
    • NGMN business models.
    • Key messages.
  • 3. High-speed internet access everywhere. CS Voice 1980 1990 2000 2010 2020 Note Ultimate performance will depend on available spectrum bandwidth, carrier-aggregation and link-budget. 3G UMTS/HSPA NGMN The mobile broadband evolution Voice GPRS UMTS HSDPA HSPA+ NGMN < 0.128 < 0.384 < 14 1 < 48+ 1 < 200+ 1 0.014  10 1  27  1,000  4,000  14,000 Speed in Mbps GPRS
  • 4. Major NGMN Success Factors. Complete eco-system needs to be ready in time. High throughput & capacity
      • Low
      • latency
    Performance delivery on today’s network grid Mobile high speed requires high speed backhaul “ Killer” experience. Legacy compatibility. Efficiency increase Backhaul. Eco system. Spectrum. 1400 MHz 1700 MHz 2700 MHz Sufficient and suitable spectrum for coverage & capacity 400 MHz Optimization Planning Operations I&C Potential savings Illustration ? 150 120 100 80 60 40 20 140
  • 5. NGMN a natural evolution for legacy operators. The 3G legacy network. NGMN all-IP, NGMN 3G evolutionary. PS CN NB NB GGSN SGSN IP networks SIM Backhaul IP and/or ATM PDN eNB eNB GW MME IP networks SIM IP Backhaul IMS NGMN is evolutionary, with much higher capacity (per Hz).
    • Backwards compatible and interoperable with legacy.
    • All-IP with new possibilities for legacy mobile operators (e.g., IM and VoIP).
    • Higher spectral efficiency, better quality and much more capacity (per Hz).
    Air: UL=SC-FDMA & DL=OFDMA Air: UL=BPSK & DL=QPSK HLR HSS
  • 6. NGMN similar to, but also very different from WiMax. NGMN is all-IP and SIM-based WiMax is all-IP and SIM-less. IP Core RN IP Backhaul RN Internet ASN GW AAA HA PDN eNB eNB GW MME IP networks SIM IP Backhaul IMS NGMN for WiMax players is not obvious.
    • NGMN different QoS and security mechanisms than WiMax.
    • NGMN architecture more complex (and costly) than WiMax.
    • NGMN introduces SIM-based authentication, WiMax is SIM-less.
    Air: UL=DL=OFDMA Air: UL=SC-FDMA & DL=OFDMA HSS
  • 7. Mobile broadband traffic trends in (iPhone) Europe. Dongles amount to ca. 5% of 3G active base and drives up-to 70% of the data volume. Terminal type & usage. 3G traffic per (active) terminal.  1  1/3  250
    • 3 main categories of terminals & usage
      • Dongle/laptop (heavy fixed-like usage).
      • iPhone/Google phone (with supporting service ecosystem).
      • “ Handset-like” mobile multimedia-enabled devices (Nokia, Sony-Ericsson, LG, etc.).
    In relative usage Active terminals% Usage% (total volume) Dongles iPhone-like Handsets iPhone-like Dongles Handsets
  • 8. Why NGMN in growth markets (and anywhere else). Higher efficiency. Better connected. New business. Mitigate 3G capacity crunch. Growth markets in Asia. HH 1 2008: 30+%, 200+ mn and 2014: 50+% and 500+ mn. 2G  3G PC penetration Broadband access GPRS EDGE UMTS HSPA LTE 1 1:3 1:5 <1:300 <1:3000 today 1 Cost per Mega Byte.
  • 9. Broadband wireless access vision. Technology enables Connected Life and Work … At home. On the move. At work. Connecting the next 1 billion un-connected.
  • 10. Asia growth markets at a glance. Growth markets double digit growth. Technology adaptation.
    • Until 2014 it is expected that:
      • Mobile revenue growth 10% pa.
      • Data revenue growth 20% pa.
      • Subscriber growth double digit.
    • 2G at around 50% in 2016.
    • 3G to reach more up-to 40%.
    • NGMN high capacity solution for Asian growth markets.
    2G 3G NGMN 0% 20% 40% 60% 80% 100% 2008 2010 2012 2014 2016 2018 2020 2022 2024 Countries included : China, India, Indonesia, Malaysia, Pakistan, Philippines, Thailand & Vietnam. Source : until 2014 based on Pyramid Research Dec 2009 projections. After 2014 technology diffusion modeling applied to the market dynamics consistent with previous period and user terminal adaptation rates. Note NGMN=LTE in Pyramid nomenclature. ILLUSTRATION
  • 11. Speeding towards a 3G traffic jam? Customer adaptation. 2  15 MHz @ 1800 MHz spectrum. 2  10 MHz @ 2.1 GHz spectrum. 2G 3G 4G 0% 20% 40% 60% 80% 100% 2008A 2010F 2012F 2014F 2016F 2018F 2020F 2022F 2024F Asian mobile operator with 13 million customers and ca. 15% market share. 0 10 20 30 0 5 10 15 -40 -20 0 20 2010 2012 2014 2016 2018 2020 2022 2024 -20 -10 0 10 DL+UL DL / UL DL+UL DL / UL 3G capacity crunch 4G 2010 2012 2014 2016 2018 2020 2022 2024
  • 12. The growth-market legacy mobile operator near-future. The 3G traffic jam!
    • 3G capacity and quality crunch within the next 2 – 3 years.
    • Slow down migration from 2G  3G, migrate to NGMN instead.
    • New spectrum demand.
    • Re-farming existing 900/1800 MHz spectrum if possible (in time).
    Empty 2G roads - in time?
    • 5 MHz in 3G will only take up ca. 1 MHz in NGMN.
    • NGMN could mitigate the 3G capacity crunch.
    • NGMN re-farmed 2G spectrum might be too late or too little.
  • 13. How to perfect existing legacy spectrum. Re-farm own spectrum and/or acquire new spectrum for NGMN. Spectral efficiency & capacity. Migration & re-farming.
    • 3G is 3 – 5  more effective than 2G per Hz.
    • The 3G usage per Hz is at least 6 times (and growing) higher than in 2G.
    • Most mobile operators have less 3G spectrum than 2G spectrum, e.g.:
      • Sun Cellular (Philippines) 2  15 MHz @ 1800 MHz vs 2  10 MHz @ 2100 MHz.
      • T-Mobile (UK) 2  30 MHz @ 1800 MHz vs 2  10 MHz @ 2100 MHz.
    • 3G spectrum will congest faster than might be expected from pure spectral efficiency considerations.
    • NGMN is at least 5  more effective than 3G per Hz (for broadband data).
    Illustration 3G (2  10 @ 2100) 2G (2  15 @ 1800) 3G  2G Customer migration from 3G  NGMN Free 2G  NGMN (2  15 @ 1800) NGMN New Customers After some time 2G to 4G migration.
  • 14. Legacy mobile operator
  • 15. Legacy mobile operator migrating to NGMN. Business model – legacy. Saturation economics. Mobile (legacy-like) network. Top-line & margin pressure. Revenue Opex Ebitda SATURATION MODE 0 Legacy sites locations pre-LTE Radio nodes (GSM & UMTS)
    • Mobile (everywhere) coverage philosophy.
    • Mitigating 3G capacity crunch.
    • Providing high-speed mobile internet access.
    • Replacing existing legacy business.
    • Interoperable with legacy (2G, 3G) networks.
    Voice ARPU Data ARPU Subscriptions - 6% + 8% + 10% Radio nodes (NGMN) Additional site locations due to capacity and NGMN. 10 th of thousands of radio nodes and mix of technologies, coverage driven.
  • 16. Legacy mobile operator migrating to NGMN (cont’). Threats. Opportunities. Weakness. Strength.
    • In-sufficient 2G & 3G spectrum for NGMN.
    • Loosing high ARPU market share to more flexible Greenfield operators.
    • Un-managed broadband demand driving spectrum assets into exhaustion.
    • Mitigating 3G crunch by migrating traffic.
    • Better broadband data quality & services.
    • Higher ARPU potential by addressing poor fixed broadband availability.
    • Synergy in business model and network.
    • Market share scale, purchasing power and strong cash-positions.
    • Strong spectrum position and variation.
    • New spectrum needed (added cost).
    • Networks optimized for ultra-low ARPU, incompatible with mobile broadband.
    • Operation of multiple technologies.
  • 17. Greenfield attacker business model
  • 18. Greenfield BWA operator’s NGMN deployment. Business model - opportunistic. Growth economics. Broadband wireless access. Wireless DSL & nomadic growth. Revenue Opex Ebitda GROWTH 0 Subscriptions 2 – 4  Mobile ARPU 0
    • Wireless DSL and nomadic services.
    • Demand driven deployment.
    • No ambition to provide 100% coverage.
    • VoIP and IM services as well as broadcast.
      • Substitute CS voice and SMS.
      • eMBMS broadcast options.
    - 2% to 4% 2mn+ LTE Nodes = site locations Capacity nodes & sites (LTE) Thousand radio nodes, 1-single technology covering urban areas, demand driven.
  • 19. Greenfield BWA operator migrating to NGMN (cont’). Threats. Opportunities. Weakness. Strength.
    • Too many players with more or less same spectrum position and business model.
    • Priced out of the market by financially stronger legacy operators.
    • Growth limitation due to limited spectrum assets.
    • Business model (wireless DSL) not (yet) captured by legacy mobile operators.
    • Providing wholesale access and legacy traffic off-loading.
    • Consolidation with other Greenfields securing stronger spectrum position.
    • One single technology to optimize.
    • Fast rollout supporting wireless fixed-like broadband market.
    • Better wireless broadband network than legacy operator’s 3G networks.
    • Scale and limited spectrum depth & type.
    • Migration to NGMN (from WiMax) will be complex, costly and with customer impact.
    • No SMS and VoIP-only options available.
  • 20. Legacy Mobile vs. Greenfield BWA business model. Legacy mobile operator.
    • Mature and emerging markets.
    • Near 100% pop & geographical coverage.
    • FDD-based with strong spectrum position.
    • Multiple access technologies.
    • Mobile voice primary revenue stream and broadband data secondary.
    • Macro-mobility main value add.
    • High Opex and very high Capex pressure due to country-wide coverage.
    • NGMN migration likely within FDD domain and possibly on legacy spectrum
    • Attractive in emerging markets.
    • Urban city-based coverage, demand-based rollout.
    • TDD-based with limited spectrum position.
    • 1-single access technology.
    • Broadband data primary revenue stream with premium ARPU. Voice (VoIP) can be offered as add-on.
    • House-hold based wireless DSL with nomadic mobility.
    • Lower overall Opex & Capex due to significant reduced rollout footprint.
    • NGMN migration likely within TDD domain and with new spectrum requirements.
    BWA Greenfield operator.
  • 21. Summary. NGMN can mitigate the 3G traffic jam. NGMN attacks (poor) fixed broadband services with wireless DSL, nomadic & mobile services. Greenfield operators likely to become growth limited without additional spectrum.
  • 22. Thank you very much! Acknowledgement: Michael Lai (P1 Malaysia), Minoo Abedi, Dirk Sch ö neboom, Stefan Wilhelm, Zhou Yi, Alan Yeo, Jordan Yeo, Denis Gautheret and many other talented colleagues in DTAG. Contact: [email_address] Tel: +31 6 2409 5202 http://nl.linkedin.com/in/kimklarsen
  • 23. Backup … mobile economics in Asia growth markets. Is a profitable NGMN business viable with very low ARPU conditions? Asia growth markets trends. South-East Asia ARPU.
    • Mobile ARPU is ca. 3.5 % of GDP/Capita.
    • DSL ARPU is ca. 10% of GDP/Capita.
    • High prepaid share with an average of 87% with some markets above 90%.
    • Pyramid Research projects the annual blended ARPU decline at least until 2014.
    • However, nominal GDP expected to grow with more than 10% pa until 2014.
    • By 2014 more than 420 mn mobile broadband users (in APAC) projected to generate more than 140bn US-dollars in data-related revenues .
    ARPU Zone Nominal GDP per capita per month $0 $10 $20 $30 $40 $600 India China Nominal GDP per capita per month $0 $10 $20 $30 $40 $0 $200 $400 Countries included : China, India, Indonesia, Malaysia, Pakistan, Philippines, Thailand & Vietnam. Source : Pyramid Research Dec 2009. BWA ARPU Zone $36 EU mobile blend 2008 Ph DSL / Cable Mobile Prepaid Mobile Contract Mobile blend