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Modern Telecommunication ... The Very Basic.

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I have for some time worked on training notes (eventually a book) that particular targets the un-initiated or persons / companies interested in understanding how Telco works and thinks. Particular focusing on Economics and Business Models.

These notes where used in a recent training I gave in Myanmar and as such many of the examples are particular to Myanmar.

For the initiated this is likely going to be too easy and sometimes even feel like cheating (just a bit).

Stay tuned as I will be updating these particular slides frequently and as I tailor make them for particular requests or interests.

In case you are interested in the actual training get in touch.

Published in: Technology

Modern Telecommunication ... The Very Basic.

  1. 1. Modern Telecommunication The Very Basics Dr. Kim Kyllesbech Larsen, TechNEconomy. Training Material 2016.
  2. 2. Anonymous Art
  3. 3. Compounded Annual Growth Rate CAGR • Growth Year 2014 2015 2016 2017 CAGR Data Volume 3.45 4.83 6.28 7.53 ~ 30% Yr by Yr growth 50% 40% 30% 20% Wiki Data Volume 2017 Data Volume 2014
  4. 4. Profit & loss (P&L). Wiki Total Revenue Technology Cost (ca. 15% – 20+%) Usage Cost− Market Invest SAC & SRC − = EBITDA (APAC ca. 45%) Personnel Cost Other Cost − − − Network Depreciation− Spectrum Amortization− Capex (new rollout  +20+% of Revenue)− Spectrum invest (0.5 – 1.0 $ per MHz-Pop)− + New Revenue? Defend philosophy! Stop / Slow Revenue Decline New business? QoS, LTE, IoT, Media/TV, FMC/FMS, … Efficiency game Optimize: Defend / Slow Ebitda Decline Increased cash pressure New technology (Fiber, LTE, 5G,..) & Modernize SAC: Subscriber Acquisition Cost SRC: Subscriber Retention Cost EBITDA: Earnings Before Interest, Tax, Depreciation & Amortization Cash Careful! Cash calculation involves more than what is depicted here! EBITDA & Margin (EBITDA/Revenues) Key metrics for assessing financial health of business Note: From Revenue we can calculate the ARPU (Average Revenue per User) by Revenue divided by the Average over Period Users.
  5. 5. Mega, Giga, Tera, Peta, Exa … Bytes Name Symbol 10n Decimal Yotta Y 1024 1 000 000 000 000 000 000 000 000 Zetta Z 1021 1 000 000 000 000 000 000 000 Exa E 1018 1 000 000 000 000 000 000 Peta P 1015 1 000 000 000 000 000 Tera (Trillion) T 1012 1 000 000 000 000 Giga (Billion) G 109 1 000 000 000 Mega (Million) M 106 1 000 000 kilo k 103 1 000 Source: Cisco VNI Global IP Traffic Forecast, 2014–2019 Global IP Traffic 1992: 0.001 GB per second. ↓× 30 over 5 years 1997: 0.03 GB per second. ↓× 3,333 over 3 years 2000: 100 GB per second. ↓ CAGR +44% per year 2014: 16,000 GB per second. ↓ CAGR +46% per year 2019: 50,000 GB per second. 100 MB ~ 4 minutes Youtube at HD (720p). 700 MB ~ size of standard movie on normal DVD. 1 GB ~ 5 minutes of 4K UHD TV viewing. 10 GB or 5 hours of Youtube watching per month. 25 GB ~ 1 Blue-ray movie size. 1 TB ~ 250,000+ HD songs (~ 1+ million hours of music). 1 PB ~ 13+ years of HD-TV videos. 50 PB ~ Entire written works of Mankind from the beginning. 4.5+ Billion Years (GY) ~Age of Earth 7000 Yotta atoms In a typical human body ~ 100 T Ants in the world ~ Number of planets in the Universe Less than 50 k elephants left in the wild ~ 50 M died as a direct consequence of WW II Wiki
  6. 6. Minutes, Bytes & bits per second. 6 • Voice Usage is well defined & understood, it is a capacity & cost driver! • Calls measured in minutes (or Erlang). • Network Impact per time unit of voice usage is “always” the same (i.e., fixed bandwidth or resource allocation). • Voice Usage is well defined & understood, it is a capacity & cost driver! • Calls measured in minutes (or Erlang). • Network Impact per time unit of voice usage is “always” the same (i.e., fixed bandwidth or resource allocation). Voice Minutes • Byte B is a measure of total information consumed; ∝ ∑ ; …    , rb is the supplied network bit rate in bits per second. • Its a volumetric unit of data consumption and similar (in principle) to a Voice Minute. • Network impact per time unit of data usage can vary enormeously (i.e., variable bandwidth or resource allocation). • Byte B is a measure of total information consumed; ∝ ∑ ; …    , rb is the supplied network bit rate in bits per second. • Its a volumetric unit of data consumption and similar (in principle) to a Voice Minute. • Network impact per time unit of data usage can vary enormeously (i.e., variable bandwidth or resource allocation). Byte (8 bits) MB, GB, TB, … Note ∝ ∑ ∆ =    , rb is constant. e.g., 12.2 kbps • bits per second is a fundamental measure of the information rate. • For data consumption the bit rate can (and often will) vary significantly between one and another instant of time. • Networks are planned according with the expected maximum gross demanded bit rate arising from all users. • bits per second is a fundamental measure of the information rate. • For data consumption the bit rate can (and often will) vary significantly between one and another instant of time. • Networks are planned according with the expected maximum gross demanded bit rate arising from all users. bits per second kbps, Mbps, Gbps Byte is NOT a capacity or cost driver!!! Bits per second is the capacity or cost driver!!! Wiki
  7. 7. 7 Throughput drives network expansion & cost …Volume (Bytes) does NOT! TRAFFIC PROFILES 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Hour of Day Throughput Mega Bits per second (Mbps) 9 HOURS 4 HOURS 1 2 Traffic profile 2 same volume as 1, but 40% higher busy hour throughput. To keep same user experience in the busy hour more network capacity needed. Higher invest level and network OPEX required. Same volumetric (Byte) demand can cause vastly different network cost and invest levels. Wiki
  8. 8. Video streaming requirements & impact. Resolution Width x Height Video Rate Audio Rate 360p 0.5 – 1.0 Mbps 0.128 – 0.512 Mbps 480p (ED) 0.7 – 2.5 Mbps 720p (HD) 3.0 – 5.0 Mbps 1080p (Full HD) 4.0 – 8.0 Mbps 1440p 7.0 – 10 Mbps 2160p (4K UHD) 25 – 45 Mbps Note: p stands for progressive scanning where all lines of each frame are drawn in sequence. Best Video Format for Mobile: MPEG4, Best Video Codec for Mobile: H.264, Audio Codec: AAC (Advanced Audio Codec). Source: Sandvine Global Internet Phenomena, Asia-Pacific & Europe, September 2015. Busy Hour Traffic Distribution – APAC (based on bits per second) Example: Radio cell sector has 1,000 users in the busy hour. Each watching 4 Minutes video stream (e.g., Youtube). Every 4 seconds a new video might be watched (0.25 per second). On average over 4 minutes one would expect 60 simultaneous video streams, which at 720p would be a BH demand of min. 180 Mbps or at 480p it would be min. 42 Mbps. Wiki 4 min (duration) x 60 sec/min x ¼ videos/sec (arrival of new views)
  9. 9. Circuit-switched connections. Circuit Switched (CS) Connections A B - End-2-End well defined circuit fully reserved until user (or network) breaks connection. - There is no changes to the circuit path throughout a call. - Capacity is reserved 100% throughout a call, irrespective of activity. - Highly reliable with less delay. - If path is broken (due to quality or outage), service is lost and needs to be built up again. - It tends to be in-efficient in its use of switching and transmission resources. - Public Switching Telephony Networks (PSTN) are circuit switched in nature. - Today many PSTNs have migrated to VoIP and (so-called) Next Generation (NG) IP switching networks. Communication paths usually called circuit. Wiki Network resources 100% reserved when connection established. No statistical advantage from variation in usage.. Connection establish from A to B and kept until user breaks it.
  10. 10. Packet-switched connections. Packet Switched (PS) Connections A B - Uses Content (e.g., voice or data) broken up in so-called (IP) packets & send over the network. - The path is changed based on quality, traffic and priority. - Network resources only used when user packets send over the network. - Can be very reliable although more delay sensitive than circuit switched. - Packet prioritization possible which can provide almost same quality as a circuit switched connections. - PS Networks tend to be very efficient due to the statistical nature of packet transmission. - Most modern switching networks (e.g., LTE, 3G HSPA) are PS-based. Wiki Network resources used only when user uses. Packets (of use) statistically distributed. Packets of use can be transmitted via many different paths Uses broken down into (IP) packets and send into the PS network. All (IP) packets re-assembled (re-built) into a continues stream of content. 123 1 1 1 1 2 2 2 2 3 3 3
  11. 11. What brings meat to your noodles? (in Europe: we would say what brings the butter on your bread).
  12. 12. ? Write (maximum) 3 sentences down describing what drives your business.
  13. 13. Telecommunications in General Tele-communications is the exchange of information (bits) over a distance by electronic or optical means. A complete, single telecommunications connection consists of at least two devices, each device equipped with a transmitter and a receiver. Ancient Greek means at a distance.
  14. 14. We are (almost) all Mobile High GDP APAC Europe North America APAC EMEA Latin America Sources: United Nations, Department of Economic & Social Affairs, Population Division. . Mobile Penetration is based on Pyramid Research and Bank of America Merrill Lynch Global Wireless Matrix Q1, 2014. Index Mundi is the source for the Country Age structure and data for %tage of population between 15 and 64 years of age and shown as a red dotted line which swings between 53.2% (Nigeria) to 78.2% (Singapore), with an average of 66.5% (red dashed line). Mobile Penetration Urban Population 2013
  15. 15. Most urban areas have 3G Mobile Broadband High GDP APAC Europe North America APAC EMEA Latin America Sources: United Nations, Department of Economic & Social Affairs, Population Division. . Mobile Penetration is based on Pyramid Research. Index Mundi is the source for the Country Age structure and data for %tage of population between 15 and 64 years of age and shown as a red dotted line which swings between 53.2% (Nigeria) to 78.2% (Singapore), with an average of 66.5% (red dashed line). 3G Penetration Urban Population Urban Area 2013
  16. 16. Revenue slows down, Cost grows faster … & that’s a problem for profitability! REVENUE GROWTH EXCEEDS GROWTH OF OPEX OPEX GROWTH EXCEEDS GROWTH OF REVENUE CAGR 2007 to 2013 High GDP APAC Europe North America APAC EMEA Latin America Source: Bank of America Merrill Lynch Global Wireless Matrix Q1, 2014.
  17. 17. 18 18 Telco at a Cross-road SMS Revenue In decline Voice Revenue In decline Data Revenue Slow to pick up The traditional mobile access-based business model of Voice, SMS & Data inevitably will decline. Access in decline Monetizing the 4th Wave
  18. 18. Lets go back to …
  19. 19. The very old days … A B A B
  20. 20. History at a glance. • 7th March 1876 Graham Bell receives patent for the telephone. • 10th of March 1876 Graham Bell makes the “first” telephone call. • 1876 Bell makes first long distance call (6 miles ~ 10 km). • 1876 telephone switchboard exchange invented (Puska, Hungary). • 1877 First commercial telephony company (Germany). • 1878 First US commercial telephony company (New Haven, Connecticut). • 1880 Graham Bell invented the Photo-phone transmitting voice signal over an optical beam. • 1917 Patent for a “pocket-size folding telephone with a very thin carbon microphone” (Finland). • 1926 First transatlantic telephone call (London, UK – New York, USA). • 1930 First experimental videophones. • 1930s Concept of digital switching developed in Europe and USA. • 1936 First video phone service (Germany). • 1941 Multi-frequency dialing introduced. • 1946 First commercial mobile phone call.
  21. 21. History at a glance. • 1960 First laser was built (USA). • 1962 Telstar telecom satellite (TV pictures, telephone calls & fax images). • 1965 First electronic switching system in commercial service. • 1965 First working optical-fiber data transmission system (Borner, Germany). • 1968 First fully digital central switch in commercial service (London). • 1969 ARPANET (Advanced Research Projects Agency Network) Live. • 1975 First commercial fiber communications systems developed. • 1978 (D)WDM concept first published. • 1980 First (D)WDM working system. • 1990 First working worldwide web (WWW) as we know it today (Tim Berners-Lee). • 2000 First commercial photonic crystal fibers. • 2012 Record breaking 1.05 Peta bits per second over 52.4 km of 12-core optical fiber.
  22. 22. History at a glance. • 1917 Patent for a “pocket-size folding telephone with a very thin carbon microphone” (Finland). • 1946 First commercial mobile phone call • 1978 First NMT (Nordic Mobile Telephone) call made (Finland). • 1991 First GSM phone call and service (Finland). • 1992 First SMS Message (Vodafone UK). 1993 First commercial SMS service (Telia, Sweden). • 2000 First commercial GPRS (General Packet Radio Service on GSM) services (first mobile packet data). • 2001 First commercial UMTS (Universal Mobile Telephony Service) by NTT DoCoMo (Japan). • 2003 EDGE (Enhanced Data rates for GSM Evolution) in commercial service. • 2004 GSM surpasses 1 Billion Users. • 2006 GSM surpasses 2 Billion Users. • 2007 HSDPA (High Speed Data Packet Access on UMTS) launches. • 2007 iPhone 1 (June 29th) – GSM/GPRS/EDGE. • 2008 iPhone 3G (July 11th) • 2008 Global Mobile Connections surpass 4 Billion. • 2009 First Commercial LTE (Long Term Evolution) Network launches (Sweden & Norway, TeliaSonera) • 2010 iPad 1 (April 3rd) • 2010 Global Mobile Connections surpass 5 Billion. • 2011 First LTE Network in South Asia Sri Lanka Telecom Mobiltel (96 Mbps). • 2014 VoLTE (Voice over LTE) in commercial service (first ~ May 2014, Hong Kong, Singapore, USA). • 2014 LTE-advanced in commercial service (first ~ June 2014).
  23. 23. Important drivers to consider.
  24. 24. Important drivers to consider. Gordon Moore’s (co-founder of Intel) law: transistor count double every two years. GPU particular important for development of Artificial Intelligence & Virtual/Augmented Reality Apps. The higher the number of Transistors the higher the performance +10Yrs × ~ 100
  25. 25. Important drivers to consider. Average Top-50 Max Top-50 On average over period a factor 2 in power reduction per year has been achieved. Very few Data points Approx. factor 10 improvement per 5 years On average 20+% improvement per year
  26. 26. Important drivers to consider. Note: after 2005 GPU outperform the CPU processing power in terms of GFLOPS so maximum performance should be used to calculate the initial price! Ca. factor 6 reduction per year In cost of computing!
  27. 27. Important drivers to consider. Last 5 years cost of Flash has reduced a factor 10+ Last 3 years cost of SSD has reduced a factor 2.5 Last 5 (10) years cost of Memory has reduced a factor 2.8 (50+)
  28. 28. Important drivers to consider. +10Yrs × 1,000 Improvement in storage & memory capacity
  29. 29. Access technologies development. Caution: Above does not consider contention ratio (e.g., 1:32 or 1:64), concurrent user demand, assuming vastly different bandwidths to get to the speed, nor does this consider that the technologies have very effective ranges at optimal speed plotted above. So it is a bit of an apple and orange comparison! Last 10 years more than × 1,000 Improvement in user speed
  30. 30. Last 10 years. The amount of computer power performance quantum leaped new applications (not possible prior). The cost of computing and storage has reduced dramatically Becoming cheap and un-locking boost in software-driven innovation. Access technologies have improved with at least factor 10 in user speed allowing for fast low-latency access to computing and storage on the go. What before had to be built in expensive customized hardware can now be supported by software on cheap off the shelf hardware.
  31. 31. Enablers Drivers Transistor Count ×1,000 over period Computing cost ~ 1/6 per year Last 10 Years Cost of Storage ~ 1/50 over period Storage Capacity ×1000 over period Cellular Access Speed ×1000 over period Cloudization Virtualization NFV SDN SW replacing HW functionalities Data DemandSW as a Service Storage Higher performance for much less cost Technology Progress
  32. 32. Telecom Today & Tomorrow.
  33. 33. Global mobile subscriptions per technology. Ca. 7.2 Billion Subscriptions Ca. 5.5 Billion Unique Users 75% of world population Ca. 9.2 Billion Ca. 5.3 Billion Unique user has (on average) 1.3 subscriptions 38% 42% 20% 50+% from Asia Pacific
  34. 34. Video content rules the internet Global Monthly usage in Exa-Bytes (Million GB). Note: Asia, North America & Western Europe makes up for 80% of the Total Source: Cisco VNI 2013 – 2018; 2019 & 2020 is authors projection based on VNI. 30+ Billion Full Movie DVDs 4+ DVD Movies per person per month 150 Billion Full Movie DVDs 20+ DVD Movies per person per month Mobile Ca. 20% of Total IP Traffic CDN 45+% of Total IP Traffic 60+% of Total IP Traffic in Metro Exa-Bytes Video-only traffic considered
  35. 35. APAC towards 2020 – Total IP Trafic. Ca. 50+% of World Population lives here! 40% of Global IP Traffic 55% of Total* is Metro-based 60% Consumer IP Video Traffic 40% of Total is CDN-based 2020 APAC Projections: Source: Cisco VNI 2013 – 2018; 2019 & 2020 is authors projection based on VNI. Source: Pyramid Research 2013 – 2017; 2018 to 2020 is authors own projection. 15+% of Pop have fixed broadband 15% still on 2G Up-to 20% likely to have LTE *Total always refers to the Total IP Traffic. Fixed Broadband Penetration 30% of total IP traffic from mobile. Exa-Bytes
  36. 36. MEA towards 2020 – Video Traffic only. Ca. 1 in 5 of World Population lives here! 4% of Global IP Traffic 17% of Total* is Metro-based Exa-Bytes 74% Consumer IP Video Traffic 14% of Total is CDN-based 2020 MEA Projections: Source: Cisco VNI 2013 – 2018; 2019 & 2020 is authors projection based on VNI. Source: Pyramid Research 2013 – 2017; 2018 to 2020 is authors own projection. 5+% of Pop have fixed broadband 40% still on 2G 4+% likely to have LTE *Total always refers to the Total IP Traffic. Fixed Broadband Penetration 30% of total IP traffic from mobile.
  37. 37. Fundamentals of traffic growth. Interest - Growth of customers. - Growth of traffic (per customer & total). - Growth of revenue. - Growth of profitability. Technology Adaptation #Users Usage Adaptation Usage per User ? LIMITED? × Exponential? S-curve-like?
  38. 38. Growth – technology adaptation. Technology adaptation #Users (is an IoT a user?) LIMITED? (maybe) Population Availability Economics 2014: ca. 40% of APAC1 on 3G or better 2020: 70+% of APAC1 1 Pyramid Research APAC. Subscriptions APAC 2014 ~ 1 sub per pop. By 2020 ~ 1.2 sub per pop. What about Internet of Things (IoT)? 1 Million IoT per km2 The 15 – 64 years
  39. 39. Growth – usage adaptation. Cellular Usage Adaptation Usage per User ? LIMITED? (maybe) Pricing Use Cases Technology Convenience Spectral capacity Network Speed Device performance Transport infrastructure 20 hrs. per week TV viewing @ 1Mbps unicast stream 20 GB per Month per user 2014: ~400 MB Cellular! per Month per User in APAC 2020: ~5 GB Cellular! Note: CELLULAR TV Cloud Cellular off-load
  40. 40. Global mobile revenue structure. Total Revenue 2014 was ca. 1.0 Trillion US$ Total Revenue 2020 Expected to be ca. 1.4 Trillion US$ +4.5% pa (CAGR) Note: SMS revenues are blended into the data revenues. Note! Data + Voice Revenues
  41. 41. Global mobile revenue structure. (an optimistic view) ARPU Turn around Note: SMS revenues are blended into the data revenues. This will in general pull down the pure mobile broadband data revenues. <2 % of expected global GDP per capita <2 % of expected global GDP per capita Abbreviated as ARPU
  42. 42. Asia expectations. +5.5% pa ~ 1.5 % of expected Asia GDP per capita ~ 1.0 % of expected Asia per capita Mobile Asia by 2020: • Ca. 5.0 B subscriptions. • Ca. 3.7 B unique users. • LTE ca. 20% • 3G ca. 40% • 2G ca. 40% • ARPUU ca. 9 US$ / month • ARPU ca. 5.8 US$ / month • Total Revenue 0.5+ Trillion US$ • 50+% from data. Total Revenue 2014 was ca. 0.4 Trillion US$ Total Revenue 2020 Expected to be ca. 0.5 Trillion US$ ARPUU – Average Revenue per Unique User
  43. 43. 44 Customer Economics to Consider. 0 – 25% 25%– 80% Beyond 80% ARPU Decline Customer Growth Slows Increasing Customer Acquisition Cost Revenue stagnation & decline Profitability Pressure Attractive urban areas All urban & Sub-urban areas Rural Areas Note: “Crossing the Chasm” is attributed to Geoffrey Moore from his book “Crossing the Chasm: Marketing and Selling High-Tech Products to Mainstream Customers”.
  44. 44. 45 Time USERS ARPU SERVICE REVENUES Time SMS REVENUE VOICE REVENUE DATA REVENUE TOTAL REVENUE DIGITZED REVENUES (The 4th Wave*) ? * The 4th Wave is attributed to CHETAN SHARMA, MobileFutureForward. The very basics … Mistakes & Mess deadly for profitability! Mistakes, Incompetence & Mess don’t really matter!
  45. 45. Old world communication… When 1 + 1 was 2 ... Bla … Bla bla bla Mobile Network We talked (a lot) We SMS’ed (even more) Rarely did we use the (mobile) web.
  46. 46. A new usage paradigm … 1 + 1 is no longer “just” 2 1 User Multiple Device User & application initiated bandwidth demand. Device & application (IP address, keep alive, …) driven signaling resources. Many applications
  47. 47. 48 What we strive for!
  48. 48. Changing business model.
  49. 49. 50 MOBILE CONVINIENCE HOMEDigitized! RETAIL Content SECURITY DEFENCE HEALTH SURVAILANCE SMART GRID DATA MINING TOURISM PROFESIONAL SERVICES TRANSPORT BIONICS QoE ENVIRONMENT
  50. 50. “Todays” Access Telco Environment The New Telco Environment The new competitive climate. Enabled by Technology.
  51. 51. 52 Mobile 1,400+ Billion US$ (55% Data) Global Digitized Economy 2020 Fixed 440+ Billion US$ (60% BB) Mobile Banking 400+ Billion US$ Public Cloud 370+ Billion US$ Mobile Health 60+ Billion US$ M2M 140+ Billion US$ Mobile App 30+ Billion US$ Mobile Digital Advertising 170+ Billion US$ (70+% of Total) Smartphones 250+ Billion US$ Mobile Content 8+ Billion US$ Managed Cloud Services 4+ Billion US$ Sources: http://www.statista.com/ premium account. Typically up-to 2020 has been projected based on available data. This applies to the following page as well.
  52. 52. 53 Mobile 1,400+ Billion US$ (55% Data) Global Digitized Economy 2020 Fixed 440+ Billion US$ (60% BB) Mobile Banking 400+ Billion US$ Public Cloud 370+ Billion US$ Mobile Health 60+ Billion US$ M2M 140+ Billion US$ Mobile App 30+ Billion US$ Mobile Digital Advertising 170+ Billion US$ (70+% of Total) Smartphones 250+ Billion US$ Mobile Content 8+ Billion US$ Another Trillion Dollar+ Economy in the most obvious Digital Services On top of Mobile. Managed Cloud Services 4+ Billion US$ Sources: http://www.statista.com/ premium account. Typically up-to 2020 has been projected based on available data. This applies to the following page as well.
  53. 53. 54 Mobile 1,400+ Billion US$ (55% Data) Global Digitized Economy 2020 Fixed 440+ Billion US$ (60% BB) Mobile Banking 400+ Billion US$ Public Cloud 370+ Billion US$ Mobile Health 60+ Billion US$ M2M 140+ Billion US$ Mobile App 30+ Billion US$ Mobile Digital Advertising 170+ Billion US$ (70+% of Total) Smartphones 250+ Billion US$ Mobile Content 8+ Billion US$ Another Trillion Dollar+ Economy in the most obvious Mobile Digital Services Entertainment & Media 2,500+ Billion US$ Travel & Tourism 9,800+ Billion US$ (<10% Online) Internet of Things 7,000+ Billion US$ Residential Financial Transaction Volume 5,000+ Billion US$ (50+% Online Penetration) Note: 2013 had Globaly ca. 30% Internet Users Healthcare 11,000+ Billion US$Medicine 1,400+ Billion US$
  54. 54. Spend 3 minutes writing down 3 bullet points of what makes mobile & wireless technologies attractive?
  55. 55. Pricing
  56. 56. Writing down 3 treasured items you would give up for 1 year of internet access.
  57. 57. Value of internet1 What would you give up a year for internet access. 80 80 75 74 68 48 30 27 22 1 Source: The Boston Consulting Group Report on “The Internet Economy in the G-20”, March 2012.
  58. 58. Value of internet1 Need, Love and then taken for granted? Perceived Value of Internet (relative to GDP per Capita) 1 Source: Analysis based on The Boston Consulting Group Report on “The Internet Economy in the G-20”, March 2012. 0% 10% 20% 30% 40% 0% 25% 50% 75% 100% Perceived Value of Internet (relative to GDP per Capita) Price of Internet (relative to GDP per Capita) 0% 10% 20% 30% 40% 0% 2% 4% 6% Internet penetration < 50% Internet penetration > 50% Japen & South-Korea Taken for granted Internet Penetration The perceived value of internet drops as internet becomes a commodity !
  59. 59. Normal price setting in mobile industry. 1 Most price levels are not designed in isolation from competition, In fact often competition is the main “inspiration” for pricing. 2 Quality could be speed but is not exclusively so. Price ( Volume ( Quality, Product, Time ) , Cost, Competition1, Regulation) Volume (eg Allowance vs Unlimited) Time Possible FUP based feedback COST mainly driven by Quality & Product Quality2 (eg speed, latency, …) Products (eg Bundles) Illustration e.g., Interconnect tariffs, roaming tariffs, MTR (for voice), …
  60. 60. Dimensioning of pricing + Volume Time ProductQuality Mobile Data pricing policies focus on Volume Fixed Data pricing policies focus on Speed sometimes combined with Volume limits. Most WiFi pricing policies focus on Time or bundled with mobile data plans  Mobile bundled products mainly Voice, SMS, and Data.  Fixed bundles with Media, Broadband Data, Voice & mobile access (if available).Illustration
  61. 61. Changing the game! New philosophies … new dimensions. Volume Time Quality1 Product Reduce Cost of Providing data Differentiate on Quality. Speed. Latency. Coverage. Time. Customer care & support, etc.. Always-Best-Connected Leverage Fixed and Mobile. Small Cell deployments. WiFi / Femto-cell off-load, etc.. Product value add-on VoIP. Msg & notifications. Internet Access. Social media. Mobile media player. Handset, etc.. Illustration 1 Quality could be speed but is not exclusively so.
  62. 62. Pricing fundamental. Cost Minimum Profit Price Range Price Floor Price Ceiling Strategic price Price Quantity Subject to Cost Revenues = Price × Quantity Price leakage Missing volumes Maximize Revenues Illustration
  63. 63. Pricing fundamental. Value to Customer Benefits Cost Profit Price Price – Cost = Profit Benefits = Value / Price Total Value Added Cost is a Function of the Benefits Price Ceiling Price Floor Value Extracted Value Ceded Illustration
  64. 64. Classical cellular pricing. The old world thinking. Myanmar Mobile Data Pricing: Old school data pricing philosophy where data usage comes on-top of what basic services (e.g., Voice & SMS) a customer has chosen. Telenor most sophisticated with quality differentiated price depending on speed range (i.e., up-to 500 kbps and up-to 2 Mbps). Neither MPT or Ooredoo have quality differentiated pricing. MPT appears to copy Telenor though does have a high cap data plan (6.5GB) for 25 US$ (ca. 3.85 US$ per GB). Telenor has the cheapest data prices at 3.7 US$ per GB if customer is happy with up-to 500 kbps. Group Study Most expensive! Highest Data Capacity per Customer But Not the best in Quality class US$ per GB
  65. 65. Pricing, quality & performance Group Study DL Speed UL Speed Ping DL Speed UL Speed Ping DL Speed UL Speed Ping DL Speed UL Speed Ping ms ms ms ms Telenor 2.20 1.07 222 2.81 1.35 179 1.41 0.99 142 3.57 1.22 144 Ooredoo 1.97 0.96 203 2.03 0.97 171 2.05 0.72 248 NA NA NA MPT 1.53 0.71 249 1.82 0.97 189 2.62 0.46 266 1.71 1.06 175 MECTel 0.22 0.27 577 0.20 0.29 587 0.39 0.28 441 NA NA NA Source: http://opensignal.com/coverage-maps/ for Yangon, Mandalay, Naypyitaw, etc.. Naypyitaw Average MbpsMbps Myanmar Average Yangon Average Mbps Mandalay Average Mbps Date: March 2016 Millions Telenor Myanmar Ooredoo Myanmar MPT Myanmar US$ 2014 2015 2016 2014 2015 2016 2014 2015 2016 Customers 3.4 13.7 18 - 25 2.2 5.8 6.4 - 7.4 11.0 18.0 18 - 20 Employees 367 500 < 750 949 >1000 < 1000 ARPU 5.4 5.6 5.2 - 5.8 7.5 6.1 5.5 - 6.0 Revenue 39 615 1,200 - 1,600 52 292 450 - 500 Ebitda -68 244 550 - 900 -98 -21 0 - 50 Margin -1.8 40% 45% - 55% -1.9 -7% 0% - 10% Opex 107 371 650 - 700 150 313 < 450 Capex 573 430 < 350 300 326 < 250 Capex / Revenue 15 70% 25% 6 112% 50% Ebitda - Capex -641 -186 200 - 550 -398 -347 < -200 Sites 1,500 4,200 7,000 1,200 3,450 5,000 Data Users 52% 60% 80% 80% 80% Market Share 20% 37% 42% - 48% 13% 15% 14% - 15% 66% 48% 38% - 44% Source: https://www.telenor.com/about-us/global-presence/myanmar/ & http://ooredoo.com/uploads/misc/Ooredoo_at_a_Glance_Q4_2015_v2.pdf Authors own prediction 1. Identify the operator who has the best quality in the below table 2. Go to http://opensignal.com/coverage-maps/ type Yangon into search block and on NetworkRank choose Advanced view and toggle between Telenor, Ooredoo and MPT coverage. How big a %tage difference is there between Download speeds for No. 1, 2 and 3. 3. Who appears to have the best coverage in Yangon? Move to Mandalay or another region and repeat exercise. The Table below provides an overview of financial results of Telenor and Ooredoo. 4. Compare Telenor & Ooredoo performance and identify the strongest operator. Explain why? 5. How many customers would the weaker operator need to arrive at the same revenue of the strongest? ARPU = Average Revenue Per User and comprises a blended figure considering all services.
  66. 66. Data-centric price plans (1 of 2). The Un-carrier price plan: • Choose between 2, 6, 10 GB & Unlimited 4G Data plan. You get beside your chosen data plan: - 1 Phone. - Unlimited Voice. - Unlimited SMS. - Unlimited data but at reduced speed beyond limit. - Binge On: unlimited video on most popular streaming services (Netflix, HBO, Hulu, etc..) … capped at 480p. - Music Freedom: unlimited music streaming. - Data Stash: rolls up-to 20 GB of unused 4G data forward. - No recurring service contract. $50/mo $80/mo $95/mo One-off Price = $US 0 Monthly Price = P X GB + US$ 42.5 (fixed monthly fee) Fixed monthly fee of US$ 42.5 covers all the above beside the data plan. Note: Unlimited ~ 14 GB @ 3.75 US$/GB Unlimited average consumption US$ 42.5 takes care of all stuff not covered by the variable 4G data pricing Group Study
  67. 67. Data-centric price-plans (2 of 2). handset_price + Customer Management Recurring Fee + PSMS (sms) + Pvoice(minutes) + Proaming_insurance(r.data, r.minutes, r.sms, r.geography) + Phandset_recovery_fee(terminal type) Pvolume = 0.86 US$/GB × DataLimit < ∞ Pvolume < Punlimited = P∞ (i.e., unit price → 0) Pspeed = 0 (in this example). Source: http://techneconomyblog.com/2015/02/03/mobile-data-centric-price-plans-an-illustration-of-the-de-composed/ Illustration: £ 26 or US$ 37.5 (for normal handsets) = 0.86 US$/GB × DataLimit Group Study
  68. 68. Target cost & design to cost. Illustration Revenue = $5.0 per Giga Byte (GB) unit sold (Marketing Wish) Margin > 30% → Earn >$1.5 per $5.0 Target Cost < (1 – 30%) × $5.0 = $3.5 per GB (maximum) The CFO View Technology view: Once off site investment $168,000 written of over 7 years ~ $2,000 per month. Spectrum $500 per month per site Site Lease $300 per month per site Energy (+fuel) $500 per month per site Transmission $200 per month per site Operations $500 per month per site Tech Cost per Site $4,000 per month → ~ $12,000 per month including all corporate cost. 3 sectors each of 2×10 MHz servicing with 3G → Capacity: 10 h traffic × 3600 s/h × 10 MHz × 1.4 Mbps/MHz/sector × 3 sectors × 1/8 Byte/bit → Capacity: 189,000 Mega-Byte per Day or ~ 4,000 GB per month Bottom-up we get that minimum cost per GB is $3.0 per GB (i.e., $12,000/4,000 GB). Group Study
  69. 69. Spectrum Frequency in Hz Carrier Frequency Channel Bandwidth
  70. 70. 72 The 3G traffic jam!  3G capacity and quality crunch.  Slow down migration from 2G3G, migrate to LTE 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 LTE.  LTE mitigates the 3G capacity crunch.  Re-farmed 2G spectrum too late for mi ga ng the 3G capacity crunch → migration to LTE a better option.
  71. 71. 73 Spectrum management essential.  Lots of Hz per customer … high speed!  Alternative to fixed (xDSL) broadband.  Higher speed than 3G/HSPA+. Happy startup … plenty of quality.  Geometrical growth in demand.  Start-up quality difficult to maintain.  Hz per customer drops dramatically.  Demand for (much) more spectrum  And many more capacity sites. Tougher future … growth limitations.
  72. 72. Frequency spectrum – basics (1 of 3). Frequency in Hz Illustration (idealized) Carrier Frequency Fc Channel Bandwidth B Bandwidth Examples: GSM 200 kHz UMTS 5 MHz LTE 1.25 – 20 MHz With Bandwidth aggregation (i.e., adding up bands) substantially larger effective bandwidth can be achieved. Carrier Frequency examples: GSM 900 MHz, 1800 MHz UMTS 2100 MHz (900 MHz) LTE 700MHz, 900 MHz, 1800 MHz, etc..
  73. 73. Road analogy of frequency & bandwidth. Channel Bandwidth Width of the Road~ The wider the road the more cars can I support simultaneously BChannel = WRoad Coverage Length of Carrier Frequency L  1 / Fc ~ Length of the road with a given Width How long a distance can I support a given traffic volume of cars How long a range can I support a given traffic demand of data The wider the channel bandwidth the more data traffic can I support
  74. 74. Frequency spectrum – basics (2 of 3). Paired spectrum. Frequency in Hz Frequency Division Duplex (FDD) - Illustration (idealized) Carrier Frequency FUplink Channel Bandwidth BUL Carrier Frequency FDownlink Channel Bandwidth BDL (can be > BUL) Duplex Separation Channel Spacing or Amplitude Uplink: from User to Network Downlink: from Network to User
  75. 75. Uplink Out of City Downlink Into of City Road analogy of FDD. Frequency division duplex.
  76. 76. Frequency spectrum – basics (3 of 3). Un-paired spectrum. Frequency in Hz Time Division Duplex (TDD) - Illustration (idealized) Carrier Frequency FTDD Channel Bandwidth BTDD Guard period Downlink Uplink Time From User to Network From Network to User  Whether to use TDD or FDD depends primarily on spectrum availability.  Both paired (FDD) & un-paired (TDD) technologies have benefits & disadvantages.
  77. 77. Downlink Into of City Road analogy of TDD. Time division duplex. Uplink Out of City 360 seconds 120 seconds Same road for Inbound (DL) as well as Outbound (UL) traffic
  78. 78. 29-15 MHz @ 900 25-35 MHz @ 1,800 Typical 210 MHz – 215 MHz For in-country merged operators can be 220 MHz - 225 MHz Cellular frequency spectrum overview. 1 HSPA= HSDPA + HSUPA, 2 Including 10MHz for E-GSM, 3 Values of Spectral Efficiency tends to change a lot depending on antenna technology and actual field data, 4 Typical value. GSM / GPRS / EDGE UMTS R99 HSDPA (Improved DL) HSPA1 (Improved DL & UL) LTE 0.032 – 0.128 0.064 – 0.384 0.384 - 4 2.5 (Avg.) to 14.4peak 30 (Avg.) to 170peak+ (450, 850,) 900, 1,800, (1,900) MHz (AWS: 700, 1,400, 1,700,) 2,100 MHz, 2,600 MHz UMTS extension band (though also LTE candidate) All Freq. UHF band & 700 – 2,600 MHz. Min. 220 MHz (target) 2352 MHz @ 900 2x75 MHz @ 1,800 260 MHz @ 2,100 and 270 MHz @ 2,600 AWS: 245 MHz @ 1,700 2n20 MHz (n=1,2,3…) Downlink Throughput (Mbps) 0.11 – 0.454 0.51 0.80 1.44 1.5 to 10 Downlink Spectrum Efficiency3 (Mbps per MHz) Dominated by legacy infrastructure suppliers: Nokia Networks, Ericsson, Huawei, ZTE. Note: FDD: Frequency Division Duplex Cellular Systems (i.e., operates in two separate frequency bands; 1 for Downlink & 1 for Uplink). Illustration only.
  79. 79. Coverage fundamentals Frequency & length of traveling wave. E.g., A male voice* reaches up-to double the distance of a female voice* purely based on its lower frequency range (all else being equal). (*) Male voice frequency 85 – 180 Hz vs Female voice frequency 165 – 255 Hz. The effective reach of a given wireless technology is inverse related to the carrier frequency. E.g., lower frequencies cover more length (& area) than high frequencies. The loss of signal power over a given distance is inverse related to the square of the carrier frequency.
  80. 80. Spectrum benchmarking – coverage. 900 MHz DL power Coverage area UL power (typical limitation for coverage) Illustration ×9 ×6 ×4.5 ×1 900 MHz – 800 MHz (digital dividend) 2.6 GHZ 2.6 GHz Available bandwidth for LTE LargeVery small LowHigh 190 MHz 2.1 GHz 1.8 GHz 2×60 MHz 2×75 MHz 2×35 MHz 2×30 MHz
  81. 81. Quiz 1. What carrier frequencies are the most valuable for coverage? a) Low frequencies (<2100 MHz). b) High frequencies (>1800 MHz). c) Carrier Frequency itself is not valuable, bandwidth is the valuable property. 2. Which statements below are correct? (could be more than one!) a) FDD divides the frequency spectrum up in individual codes. b) FDD stands for Forestry Defence Department. c) FDD divides a frequency spectrum into two bandwidth parts, with a frequency separation between uplink use and downlink use. d) TDD stands for Time Division Duplex. e) In China TDD is the most popular implementation of LTE. f) FDD is better than TDD.
  82. 82. Frequency link budget. Transmit Tx (path) Loss L ≤ 1 g × Tx Receive Rx = L × g × Tx Gain g ≥ 1 Convention: in dB whereLink Budget
  83. 83. Spectrum efficiency. How many bits per second can I transport per Hz of bandwidth. Frequency in Hz Illustration (idealized) Channel Bandwidth B in Hz Spectrum Efficiency = Information rate (bits per second) that can be support by a given technology and available bandwidth in Hz In general, the higher spectral efficiency the better technology!
  84. 84. Road analogy of spectral efficiency. Width of the Road WRoad 5 cars per second Per Width of Road Old Road 10 cars per second Per Width of Road Safe distance Width of the Road WRoad New Road Next Generation Road 21 cars per second Per Width of Road Width of the Road WRoad Technology Improvement Technology Improvement
  85. 85. Capacity fundamentals. Unit Capacity = Bandwidth in MHz × Spectral Efficiency (in Mbps MHz − capacity unit ) Dimension of Unit Capacity is Mbps/capacity-unit B Available BW in MHz per unit Spectral Efficiency in Mbps/MHz/ unit N Number of units
  86. 86. T-Mobile UK & Orange TD-TV Examples of frequencies & bandwidth. TDD & FDD. UL (75 MHz) DLUL (35MHz) DL UL (70 MHz) TDD (50 MHz) DL 900 MHz 1,800 MHz 2,500 MHz UL (60 MHz) DL 2,100 MHz TDD part TDD 2,300 – 2,400+ MHz part TDD / part FDD This band provides interesting backhaul P2P options in some Greenfield scenarios 3,400 – 3,800+ MHz China: SD-CDMA alloc. UL DL 400 MHz DL UL 700 MHz TDD T D D (20 MHz) (15 MHz) (20 MHz) Airway in China TDD BSNL in India
  87. 87. City coverage benchmarking. For dense cities beside coverage being relative insensitive to frequency the effective cell range decreases with increasing population density.. NYC Den Haag Houston Leeds LA Chicago Berlin Hamburg London N 2 33 A r  A: Covered (hexagonal) Area N: Number of cell sites Houston 1 1 TMUS GSM spectrum at 1,900 MHz, and their 3G in the AWS1700 band. 0.20 0.40 0.60 0.80 1.00 0 2,000 4,000 6,000 8,000 10,000 City Pop Density (pop/km2) GSM900 GSM1800 UMTS2100 Effective Cell Radius in km (City Coverage Characteristics)
  88. 88. Coverage (1 of 2) Low-frequencies (<1,800 MHz) provides excellent coverage options while higher frequencies with more available bandwidth gives higher speed performance. Typical Cell Range (km) 0.01 1 10 100 1,000 LTE450 HSPA 2100 UMTS 2100 GSM900 GSM1800 GPRS EDGE LTE 2100 LTE 2600 Femto-cells/3.6GHz WiFi Note: Illustrational purpose only real cell sites can vary greatly as well as can the actual performance Voice 10 km 0.1 Economical very attractive for sub-urban to rural & deep indoor coverage Economical attractive for urban areas & capacity demand indoor Site throughput in Mbps vs cell range in km
  89. 89. Coverage (2 of 2) Frequency and bandwidth determines the technical as well as economical performance of a given access technology. Typical Site Range (km) Voice 0.1 1 10 100 1,000 High Frequency Low Frequency High Bandwidth Low Bandwidth Below 900 MHz Above 1,800 MHz Below 10 MHz Above 20 MHz Site Throughput in Mbps (equivalent user capacity)
  90. 90. Capacity fundamentals. CAPACITY Ci = BANDWIDTH Bi MHz × EFFICIENCY ηi Mbps per MHz per Cell × CELLS Ni # Business as Usual New spectrum New technologies New macro × Innovation Re-farming Improvements Small-cells × Radical Spectrum sharing Spectrum sharing Site sharing Note: Sub−script i referes to a relevant cellular clutter area; thus the Total Capacity Ci   ( ) = Bi×Ei×Ni   i(Areas) VERY COSTLY (VERY) COSTLY EFFICIENT (VERY) COSTLY COMPLEX + EFFICIENT COMPLEX BUT EFFICIENT, QoE CHALLENGE BaU (COSTLY) BaU (COSTLY) B × $ / MHz-pop (e.g., 1 – 2 $/MHz-pop) η Modernization Terminal subsidies N Cell splits / overlay New Sites Within technology up-to 20% gain upto ceiling. Between technologies x2-3 gain Can be a signifiant capacity multiplier and result in new site avoidance. In urban areas can be difficult to achieve more density (new sites).
  91. 91. 93 ConnectivitySpectrum is the growth engine. CAPACITY Ci = BANDWIDTH Bi MHz × EFFICIENCY Ei Mbps per MHz per Cell × CELLS Ni # GSM Ctot ≈ 40k n x 0.2 MHz (TRX) (n: 6 – 15) ~ 0.52 (GSM) 0.14 – 0.33 (EDGE) 80k – 100k (Utilization ≈ 50+%) Frequencies Total Bandwidth 900 & 1800 MHz Ca. 110 MHz UMTS Ctot ≈ 600k (×15 GSM) n x 5 MHz (carrier) (n: 2 – 4) 0.5 – 1.2 (average) up-to 17 (peak) 80k -100k (Utilization* ≈ 70+%) Frequencies Total Bandwidth 2100 (900) MHz 60 (95) MHz LTE Ctot ≈ 4,500k (×8 UMTS) n x 5 MHz (carrier) (n: 6 – 10+) 1.5 – 2.0 (average) Up-to 30 (peak) 80k – 100k (Utilization* ≈ 90+%) Frequencies Total Bandwidth 700 -900MHz, 1.8GHz, 2.5GHz 210+ MHz Note: Above only FDD spectrum is considered. Bandwidth are represented by DL part (i.e., total BW = 2x(DL or UL for symmetric bands). (*) pending on terminal type and application a single customer can in theory cause the a given cell to be highly utilized in terms of bandwidth resources. LTE is supported over a very wide frequency range from 450 MHz up to 3.6 GHz
  92. 92. Spectrum is a very valuable asset. UK 2.1GHz ca. 35 Bn US$ NL 2.1GHz ca. 2 Bn US$ DE 2.1GHz ca. 38 Bn US$ IN 2.3GHz ca. 5.5 Bn US$ US 700 MHz ca. 20 Bn US$ Telenor paid $500M for 2×5 + 2×10 MHz Blended average of $0.31/MHz/pop
  93. 93. UMTS Euphoria 2000. - In March 2000 Mobile industry paid ca. 35 Billion US$ for 3G spectrum (record). - Almost $5 per MHz per pop. - ×3 the total UK mobile revenue in 2000. - ×8 the total UK mobile Ebitda in 2000 (estimate). - On-top they would need to invest at least 20 Billion US$ in 3G network infrastructure. - They would need minimum 8 – 10 Billion US$ FCF per year (over 10 years) to reach an NPV 0. - ×12 the total UK mobile FCF in 2000 (estimate). - At least 15+ years to breakeven on cash. - The internal business cases (at the time) would have had to be very optimistic to finance what was paid for the spectrum. - Value should have far exceed the 35 Billion US$ paid for spectrum including deployment investments. - In July 2000 Mobile industry paid ca. 2.0 Billion US$ for 3G spectrum. - Ca. $2 per MHz per pop. - Approx. the total NL mobile revenue in 2000. - ×2.5 the total NL mobile Ebitda in 2000 (estimate). - On-top they would need to invest at least 1.5 Billion US$ in 3G network infrastructure. - They would need minimum 0.5 Billion US$ FCF per year (over 10 years) to reach an NPV 0. - Approx. the total NL mobile FCF in 2000 (estimate). - The internal business cases (at the time) was optimistic but not as aggressive as in UK. - Value should have far exceed the 2 Billion US$ paid for spectrum including deployment investments. Telenor paid $500M for 2×5 + 2×10 MHz $0.31/MHz/pop (1/6 NL) GDP per Capita is 30× lower
  94. 94. Quiz 1. A Technology using 900 MHz covers an area a) Worse than for a frequency of 1800 MHz? b) Better than for a frequency of 1800 MHz? c) Too little information to answer question? 2. Which of the following set of parameters are important for providing cellular network capacity? a) Frequency, Number of rainy days, Number of Sites. b) Number of Sites, Bandwidth and Number of Customers. c) Number of Sites, Number of bits per second per Hz available from deployed technology and Available Spectral Bandwidth. 3. My LTE customers demand 100 Giga bit per second (Gbps) in downlink. I have 2 x 10 MHz available for LTE with an effective  of 2 bps/Hz/unit. How many units do I need to support the demand? a) 500 capacity units. b) 250 capacity units. c) 5,000 capacity units.
  95. 95. Facebook Drone Coverage The Basic Economics “The Drone Coverage Network is an exponential technology in the sense that it has the ability to Disrupt existing terrestrial-based cellular coverage networks by a factor of 10 or more on TCO and deployment-time.” “Facebook’s ambition is to built 10,000 Acquila drones which could more than easily cover all land based surface area.”
  96. 96. Coverage solutions. Caution: drawing is not to scale! Nano-satellite FB Aquila Drone Terrestrial Cellular Tower 30 – 70 meter 10 – 50 km < 2000 km DataQuality Cell Center Drone Coverage Terrestrial Coverage Distance from center Practically 10 km range FB estimate ~ 80 km Note: FB Aquila envision Laser connectivity to house holds (beyond fiber connectivity) although mentioned but not described wireless coverage as well. = GEO ~36,000 km 10 Gbps Laser beam
  97. 97. Facebook Drone Coverage Network vs standard MNO Cellular Network Coverage. Drone Network Coverage is 10× more Capex Efficient. 10× more Opex Efficient. Typically more than 10× faster deployment. Highly scalable capacity provision & options. Support all frequency ranges up-to mm-wave; thus also standard cellular/wireless frequencies 700 MHz to 5 GHz.
  98. 98. Facebook Drone Coverage – Aquila. Drone / Unmanned Arial Vehicle (UAV) 10 – 50 km Stratosphere Wingspan 42m <450kg Up-to 80 km < 20 thousand km2 • Envisioned as a constellation of 3 drones circling in the stratosphere providing covered to an area of up to 20 thousand km2. • Up-time up-to 3 month (solar powered). • Laser backhaul with 10 Gbps connectivity. • Myanmar Example: • Myanmar surface area is 676,578 km2 and we would thus require ca. 30 Facebook drone constellations (i.e., 3 drones). • Providing max WiFi speeds across coverage area. • Cellular network providing up-to 80% geographical coverage may require up-to 10,000 cellular sites, between 1.5 to 2.0 Billion US$ in Capex and easily several hundred millions of US$ in annual Opex. • Providing max speed in vicinity of tower and increasing poor quality out to cell edge with 128 kbps - 256kbps. Unlicensed WiFi or Cellular Freqs.* 10 Gbps Laser backhaul (*) Should Facebook acquire cellular frequencies or cm/mm-wave frequencies this would likewise be straightforward to deploy via a Drone-based coverage network. Wiki Note: global pop per HH is ~3.5, world surface area 510 Million km2 of which ca. 150 million km2 is land area of which ca. 75 million km2 is habitable. 3% is an upper limit estimate of earth surface area covered by urban development, i.e., 15.3 Million km2. Note: FB Aquila environs Laser connectivity to house holds although mentioned but not described wireless coverage as well.
  99. 99. 1 0 2 102 Towards Next-Generation Telco Technologies and Business Models. Converged Access Internet of Things Internet of Industries Connected Vehicles Converged Apps Vehicular Autonomy E2E Latency < 1 ms Very High Redundancy. Medium BW requirements E2E Latency ~ 1 - 50 ms Very high availability Elastic BW requirements E2E Latency ~ 50+ ms Privacy & Security protection Extreme elastic BW requirements Ultra-high Availability Very high security required Elastic E2E Latency requirements FTTx + LTE  5G Ultra-Efficiency requirements Cloud & Virtualization Seamlessness across all platforms e.g., Fixed, Mobile & other screens Ultra-Personalization Industry 4.0IoA IoT
  100. 100. Internet-of-Things (IoT). A craze of very big numbers of small things connected. - 4.3 Trillion US Dollar Market by 2024*. - 2.4× that of the Mobile Industry Revenue. - 27 Billion IoT units installed by 2024*. - 4 × that of unique mobile users. - Up-to 1 million IoT units per km2. - An urban macro cellular site might have to serve up 3 million IoT units. IoT Requirements: - (ultra) low device cost. - (ultra) low power consumption. - Near-zero maintenance. - Very long battery lifetimes. - Versatile connectivity. - Elastic latency ( 1 ms to seconds). - Elastic Bandwidth ( bps to Mbps). - Massive scalability  106 per km2(*) https://machinaresearch.com/news/the-global-iot-market-opportunity-will- reach-usd43-trillion-by-2024/
  101. 101. Quiz (1 of 2) • By 2024 27 Billion Global IOT connections are expected. • World population is expected to be 8 Billion with ca. 3.5 people per household (HH). • Planet Earth total surface area is 510 Million km2. • Land area is ca. 150 Million km2 • Ca. 75 Million km2 is habitable. • Max. 15 Million km2 is covered by urban development. 1. How many IOT connections do you have per HH and per km2 considering the total surface area of Planet Earth. 2. How many IOT connections do you have per km2 considering only land area. 3. How many IOT connections do you have per km2 considering only urban development. 4. Does the amount of IOT devices per Household seem realistic? Compare with the expected number of mobile devices per HH? 5. Assume that a typical urban cell site area of is ca. 3 km2 how many IoT connections do you get that a cell site would be required to support?
  102. 102. Quiz (2 of 2) • By 2024 27 Billion Global IOT connections are expected. • On average an active IOT connection will use 140 Bytes (approx. size of SMS). • On average an IOT is active 60 times per minute (60x24x7x365:-). 1. How many Mega Bytes will an IOT connection consume per day? 2. How many Mega Bytes will an IOT connection consume per month? 1. Compare that to the global average smartphone data consumption 2015 (ca. 1,200 MB). 3. How many Giga Bytes will an IOT connection consume per year? 4. What is the total amount of Exa Bytes (i.e., Billion Giga Byte) consumed by of all IOT connections? 5. If by 2024 the total data consumption excluding IOT is in the order of 400 Exa Bytes (i.e., 400 Billion Giga Bytes), what would the proportion of IOT data consumption be if included in the total data consumption?
  103. 103. Global IoT growth projections. 2014 – 2024. ~ 2 IoT Connections per 3 people ~2.5 IoT connections per Household ~13 IoT connections per Household Note: global pop per HH is ~3.5, world surface area 510 Million km2 of which ca. 150 million km2 is land area of which ca. 75 million km2 is habitable. 3% is an upper limit estimate of earth surface area covered by urban development, i.e., 15.3 Million km2  300+ IoT per km2 in 2014 and 1,700 IoT per km2 in 2024. ~33 IoT connections per km2 land area. ~180 IoT connections per km2 land area
  104. 104. Global IoT revenues*. (*) https://machinaresearch.com/news/the-global-iot-market-opportunity-will-reach-usd43-trillion-by-2024/ 4.3 Trillion US$ CAGR 17% 0.9 Trillion US$ Ca. 160 US$/IOT/Yr Ca. 13 US$/IOT/Yr IoT Device Revenues  approx. 52 US$ per IoT. IoT Connectivity (Access)  approx. 3.7 US$ per IoT per Yr. approx. 0.3 US$ per IoT per month. M2M/IoT Service  approx. 44 US$ per IoT per Yr. approx. 3.7 US$ per IoT per month. ALL REVENUES
  105. 105. Narrow Band (NB) IoT. Many flavours to Internet-of-Things.
  106. 106. IoT structural ecosystem. Infrastructure Transport Traffic Buildings Farm Emergency Factories Edge Gateways. Fiber Cellular WiFi Powerline Satellite Drone Billing & Operations Support Systems Billing & Operations Analysis Service Platforms 1..N QoS & Service Management Network Management Big Data Analytics SmartCity SmartFarm Home Automation Factory Automation SmartRoads eHealth Etc etc… End-users: SME, SOHO, Municipality, Private, … User or Service Provider owned Telecoms, Network Providers, MVNOs, Others Value Add service providers Services
  107. 107. Industrial revolutions. ~1870s Electrical. Steam engines scales. Industrial Iron making. ~1950s Change from mechanical & electronic technologies to digital ones. ~1780s Mechanical. First factories & mass-production, e.g., particular textiles. ~1880s First Electric Power Plants 1st 2nd 3rd 4th Revolution?
  108. 108. Industry 4.0 (4th industrial revolution) Whats in it for the Industry (Europe)? - 50% of all capital investment until 2020. - In Europe alone up-to 140 Billion Euro pa. - 18% boost in productivity. - 110 Billion Euro pa in additional revenues. - Lead to massive transformations. Definitions: Cyber-physical system: workplace carriers, assembly station & products. Requirements: - Interoperability with IoT & Internet. - Virtualization  plant & simulation models. - Localized autonomy. - RT capability ~ highly elastic latency reqs. - Service orientation. - Highly customizable / Modularity.
  109. 109. Telecom Networks.
  110. 110. Network fundamentals (simplified). Air-interface • GSM • UMTS/HSPA • LTE/LTE-Adv • WiFi • 5G, etc… Cell • BTS • Node-B • E-Node-B • AP Cell Access/Backhaul • Microwave (MW) • Leased Line (E1) • Fibre / Cable • Gigabit Ethernet • Satellite Backbone • Fibre/IP • Microwave IP Aggregation • BSC • RNC • IP Aggregation. • Access Cloud. Core Network Data Center Cloud IT VAS & BSS. Packet Switched (PS/IP). Circuit Switched (CS). Signalling Network. External World - Foreign Public Land Mobile Networks (FPLMN). - Public Switching Telephony Network (PSTN). - WWW = The Internet. Other mobile networks (FPLMN) Fixed Networks (PSTN) WWW MW n×E1 Fiber Fiber
  111. 111. What’s a Cloud? Source: http://www.businessnewsdaily.com/4864-cloud-computing-terms.html, note: FW: Firewall, SW: Software. Cloud Service are referenced to a computing service that resides in a secure and (possible) centralized remote (for the customer) platform. Customers procuring a cloud service from a Cloud Service Provider purchase only what they use leading to substantial Capex and Opex savings (avoidance) SaaS – SW as a Service: Offering SW (residing in the cloud) on a subscription basis based on per-user basis. Use-Case: Replaces traditional on-device SW. Examples: Microsoft Office 360, Google Apps, Salesforce, Cisco WebEx, SAP, …. PaaS – Platform as a Service: Providing strong infrastructure & SW applications for building, testing & launching new applications. Use-Case: Increase developer productivity & utilization rates while decreasing time-2-market. Examples: SAP, Apprenda, Openshift, AWS Elastic Beanstalk, Cloud Foundry, Google App, … IaaS – Infrastructure as a Service: Provides computing, storage, networking & services (e.g., FW). Use-Case: Instead of purchasing HW, users purchase IaaS based on consumption (like electricity). Examples:, Amazon Web Services, Microsoft Azure, Google Compute Engine, … Examples pf Cloud-based services
  112. 112. Benefits of cloudization. Networking Storage Servers Virtualization Operating System Middleware Execution Data Application Legacy All Internally Managed Networking Storage Servers Virtualization Operating System Middleware Execution Data Application Infrastructure as a Service IaaS Networking Storage Servers Virtualization Operating System Middleware Execution Data Application Platform as a Service PaaS Networking Storage Servers Virtualization Operating System Middleware Execution Data Application Software as a Service SaaS Source: http://news.microsoft.com/download/archived/presskits/cloud/docs/The-Economics-of-the-Cloud.pdf Internally managedInternally managed All being managed by cloud provider(s) It is possible to mix cloud providers. It is possible to mix cloud providers. Could be from different provider
  113. 113. Basic business model for the cloud Platform as a Service (PaaS) Infrastructure as a Service (IaaS) Software as a Service (SaaS) Pay as you Use Pay as you Grow Network as a Service (NaaS) Customers can save or altogether avoid IT Infrastructure and substantially reduce need of IT Staff
  114. 114. The Top Cloud Providers. As of 2014. Infrastructure as a Service (IaaS) Platform as a Service (PaaS) Software as a Service (SaaS) Storage as a Service Security as a Service X as a Service (XaaS) Other Cloud Service examples
  115. 115. When you see a network cloud Per Cloud Data Center: - 500+ Million Euro Investments. - 100s of thousand of servers. - 100s of Megawatt power. - 1000s of TFlops. (Illustration only representing Google, Facebook, Apple DCs). E.g., Deutsche Telekom’s Biere DC (2014) has approx. 15k servers over 3k square meters. (Data Center) Cloud 100s thousand homes equivalent
  116. 116. Virtualization (simply) defined. Driven by vastly improved computing power at increasing lower cost as well as cheap high performance storage. Traditional Architecture Resources underutilized (often significantly so). Sharing resources difficult. Virtual Architecture Sharing resource easy, secure & flexible. Microsoft AppsWindows 10 Linux Hadoop Mac OS X Photoshop Windows 10 Microsoft Desktop Apps
  117. 117. Basic requisites for economic benefits of cloudization and virtualization. Reliable, readily available and relative cheap energy & real-estate. (Low cost) high quality fiber optical networks for local connectivity available. Low cost high availability international (high) bandwidth to tier-1 traffic destinations.
  118. 118. Economics of cloudization. Biggest benefits relative to existing cost structure to be expected with legacy data center providers, ISPs and businesses where ICT operation is not a core business. Study materials: http://news.microsoft.com/download/archived/presskits/cloud/docs/The-Economics-of-the-Cloud.pdf Large-scale data centers (DC) should provide lower cost per server from simple economics of scale considerations. Aggregating computing demand provides statistical multiplexing gain resulting in increased server utilization & efficiency. Multitenant application model (e.g., Microsoft Office 365) reduces the app management and server cost per tenant.
  119. 119. Caution on the Business Case of Cloud & Virtualization. Old Legacy DC Design with 1:1 physical server to Services (non- virtualized) Modern DC Design Fully virtualized 60% to 70% Cost reduction* (*) Comparison should always be based on absolute cost at the same occupancy or efficiency rate. Be careful about relative TCO metrics only unless you can check the absolute cost level as well. See also Cisco “The Economics of Cloud Computing” by Bill Williams. Un-negotiated, as-is & older HW (i.e., no optimization) Newly negotiated, newest HW, Optimized (high) efficiency • Do understand your baseline! • What is the Baseline Cost including TCO (Total Cost of Ownership)? • What are the limits to optimization within legacy network? • Include the potential of new sourcing. • What is the cost per service? E.g., Server TCO, Storage TCO, Maintenance per Service, etc… Modern DC Design Virtualized Optimized NG DC Design Virtualized Optimized < 20% Cost reduction* At this time and age the above scenario is relative rare. At this time and age the above scenario is the more normal one. Newly negotiated, newest HW, Optimized (high) efficiency Un-negotiated, as-is & older HW (i.e., no fully optimization)
  120. 120. Cost of basic DC Elements. Always know the details of your baseline cost. Networking Storage Servers Virtualization Operating System Middleware SW Execution Data Application Facilities Resources / FTE Maintenance Ancillary 3rd Party Services Including transport cost SAN, NAS, HDFS, etc.. mirror sites required? COT or supplier specific Might not be relevant in baseline Opensource or supplier specific Other cost elements to be considered End user SW & data handling e.g., Salesforce. Runtime. Degree of outsourcing Note these cost elements should minimum be considered whether you are a cloud provider or cloud customer! IaaS PaaS SaaS Energy, Water, etc.. Follows from Apps & OS New Revenues? Does Cloud – Virtualization leads to new services? Or more efficient service delivery?
  121. 121. Telco Cloud & Virtualization Economics. Telco cost structure impact of migrating to cloud & virtualization. Capex impact: • Maximum 40% of Telco Capex likely to be positively impacted by Cloudization & Virtualization (i.e., IT & Core). • Of the 40% approx. 50% would be infrastructure & the remaining part Software- driven (new development 20% & maintenance 80%). • Transport (i.e., Backbone/interconnect) cost (up-to 20%) could increase. • Really depends on the degree of centralization & whether traffic remains in country or needs international transport. • Upfront investment (unless outsourced to 3rd party) would be required to design and build DC to host Telco IT and Core Network functionalities. • Assuming that Telco builds up own Cloud capabilities: overall Capex benefits (avoidance) should be expected to be relative minor as premium HW is replaced by premium SW (although HW cost is reduced, the cost of SW tends to increase) and the upfront investment to prepare DC for legacy migration cloud/virtualization. • On IT specific Capex max 40% avoidance should be expected compared to a legacy IT environment wo virtualization (i.e., Greenfield comparison). • In complete Outsourcing model substantial part of the relevant Capex (i.e., 40%) will disappear although additional transport invest may be required. potentially negatively impacted Potentially negatively impacted Opex impact: • Maximum 25% of Telco Technology Opex expected to be impacted by Cloudization & Virtualization (i.e. IT & Core). • Complete Outsourcing model: One need to consider the total cost including the benefits of Capex Avoidance (see above). While part of the legacy Opex should be expected to reduce (e.g., from personnel, energy, other) 3rd party service cost would add Opex to the cost structure. • Depending on how efficient legacy IT & Core were operated minor overall Opex saving (<10%) could be expected. • Assuming that Telco builds up own Cloud Capabilities: One should not expect more than net 10% to 20% Opex savings on the relevant Opex (i.e., 25%) and only after complete migration. During migration overall Opex is likely to be higher than legacy only. Group Study
  122. 122. Summary Relative benefits to cost structure of cloudization & virtualization. E-commerce businesses can avoid own IT infrastructure & need for substantial IT staff, benefit from economical PAYG&U* licensing (i.e., very low barrier to start-up). Legacy Data Center Providers & large non-Telco ISPs leverage scale of their existing DC infrastructure (i.e., increased business on same infrastructure). Telcos, where IT & Core Network cost structure is relative minor, will achieve improvements on relevant total cost although overall it might not be a big change. (*) PAUG&U: Pay As You Grow and Use. Highest absolute economical benefits of cloud & virtualization are achieved in Greenfield Scenarios with pure IT environments.
  123. 123. OSI goes soft. Open Systems Interconnection model. Data Link Layer (frame, e.g., MAC, PPP,) Network Layer (packet, e.g., IPv4, IPv6, ..) Physical (raw bit stream, e.g., DSL, Ethernet, …) Transport Layer (segment TCP / datagam UDP) Session Layer (data, e.g., HTTP, SMTP, …) Presentation Layer (data) Application Layer (data) 1 2 3 4 5 6 7 Good reference: https://en.wikipedia.org/wiki/OSI_model, another good reference from Duke University: http://people.ee.duke.edu/~romit/courses/f07/material/ Data plane Control plane NFV Network Function Virtualization SDN Software Definable Network Raw Transmission Relievable Transmission (start – end of stream) Address, routing & control (re)Transmission between network points back-and-forth transm. between two node Translate between network services & app. High-level API – closest to the user SW.
  124. 124. Software definable network (SDN). Driven by vastly improved computing power at increasing lower cost. • Implement Control Plane in software. • Decouple control plane from data plane. • Using commoditize routers & switches. SDN is Intelligence centralized in a controller that manage commodity devices controlled by imposed policies & configurations Application Servers Access Aggregation Core Routers Classical Data Center Application Servers SDN Domain Core Routers SDN-based Data Center SDN Controller Programmatic (SW) control plane
  125. 125. Network Function Virtualization (NFV). Driven by vastly improved computing power at increasing lower cost. • Implement Data Plane in software. • Decouple network elements from hardware. • Using commoditize hardware (e.g., OTS servers). NFV ensures that Virtual Devices are configured remotely & provisioned instantly on the OTS server farms (in the Data Centres). HSS Policy IMS NAT DPI SGSN SMSC … Service Provider (e.g., MNO) Domain Customer Domains Core Router Edge Router Fixed Mobile WiFi NetworkFunctions Classical Architecture: Mixed supplier landscape with proprietary implementations. Service Provider (e.g., MNO) Domain Customer Domains Core Router NFV Service Insertion Point Fixed Mobile WiFi NFV NFV-centric Architecture: OTS Server, Storage & switches Software HSS Policy IMS NAT DPI SGSN SMSC Virtual Edge Router Etc… Off The Shelf
  126. 126. (*) Marc Andreesen, WSJ, 2011 (source: http://www.wsj.com/articles/SB10001424053111903480904576512250915629460). Recommended reading.
  127. 127. Front-end Cloud DC Towards 5G in 2020. 5G / LTE Small Cells FTTH Access Cloud DC Software Definable Network (SDN) The Access Cloud is a Data & Computing Center supporting access & edge functionality Max 50 km Front-end Cloud DC Back-end Cloud DC Other Networks Depending on country size and size of network more than 2 front-end 100 Gbps 10 Gbps Access Cloud DC Software Definable Network (SDN)
  128. 128. Most important Telco drivers
  129. 129. GSM, GPRS & EDGE Global System for Mobile communications The 2nd, 2.5 & 2.75 Generation
  130. 130. Old world communication… When 1 + 1 was 2 ... Bla … Bla bla bla Mobile Network We talked (a lot) We SMS’ed (even more) Rarely did we use the (mobile) web.
  131. 131. Why GSM? Prior to GSM  Fragmented analogue systems (NMT, E-TACS, TACS, CNETZ, ...).  No inter-operability between existing mobile standards.  No inter-operability with fixed telephony networks.  Poor scalability of existing technologies.  National security concerns (The Russians).  Common European Market requiring a Europe-wide standard.  Growing demand for mobile telephony. NMT: Nordic Mobile Telephony, E-TACS: European Total Access Communications System.
  132. 132. GSM – a 30 year old technology. 1982: 890 – 915 MHz (UL) and 935 – 960 MHz (DL) was reserved for a Cellular System: 2×25 MHz (to be reserved across European Union member states). 1985: Decision to implement a digital cellular system. 1987: Field trials completed in Paris. GSM working group concludes that best technology would be based on Time Division Multiple Access (TDMA) & Frequency Division Multiple Access (FDMA). Memorandum of Understanding initially signed by 12 countries. 1991: First GSM call and service launched in Finland. UK, France, Germany and Italy introduces digital services based on GSM standard (phase 1). 1993: Explore GSM migration towards UMTS.
  133. 133. GSM operational requirements.  High Audio Quality.  High Spectral Efficiency.  Identical systems in all countries.  International roaming.  Open architecture.  Economical both in sparsely and in heavily populated areas.  Integration with fixed digital networks (e.g., ISDN).  Security features (e.g., Cold war era).  New features, e.g., Short-Message Service (SMS), Data, and Fax.  Easy system introduction.  Low-cost infrastructure. What was the benchmark? Explain why? Explain why? What benefits? Explain why important? Discuss what that means? ISDN: Integrated Services Digital Network … set of digital communications standards enabling simultaneous voice, video, data and other service using the traditional circuits of a given PSTN. Basically ISDN provides also access also to packet switched data networks on top of old copper infrastructure. Group Discussion
  134. 134. Basic business models of GSM. Wireless Mobility Identity & security Scalability Mobile TelephonyInterworking PLMN PSTN PLMN: Public Land Mobile Network, PSTN: Public Switched Telephone Network, also known as Plain Old Telephone Service (POTS) network. @kbps SIM
  135. 135. GSM customer. + Mobile Station (MS) = SIM + Device Note! When operators count subscribers they often do it by number of SIM cards All Subscribers are assigned a International Mobile Subscriber Id (IMSI) • IMSI is the only absolute identity a subscriber has within the cellular system. • IMSI is not hardware specific, e.g., like IMEI or MAC address. • IMSI is used in GSM, UMTS & LTE. MCC – 3 digits Mobile Country Code MNC – 3 digits Mobile Network Code MSIN – max 9 digits, first 3 digits = HLR-id Mobile Station Identification Number National Mobile Station Id (NMSI) IMSI MSISDN CC – 1- 3 digits Country Code NDC – Variable Nat. Destination Code SN – Variable Mobile Station Identification Number Mobile Station ISDN Number – max. 15 digits Mobile (Telephone) Number Unique customer id IMEI International Mobile Equipment Id … unique identifier of equipment used by the subscriber. Unique device id
  136. 136. GSM services. Overview of Phase 1 to 2+ (most important items). Tele Services: • Mobile telephony (13 kbps voice). • Incl. Half-Rate speech coding. • Incl. Enhanced Full Rate • Emergency calling (irrespective of subscription & credit). • SMS (i.e., 160 chars) • Fax Bearer Services: • CS Data (300 – 9600 bps, 14.4 kbps in 2+). • High-speed circuit switched data (HSCSD, 2+). • General Packet Radio Services (GPRS, 2+) with maximum speed of 115 kbps (theoretical). • Enhanced Data for GSM Evolution (EDGE, 2++) with maximum speed of 474 kbps (theoretical). Network Features: • Network Identity & time zone (NITZ, 2+) • CAMEL Phase 1 (prepaid roaming). • Support for Optimal Routing (SOR), particular applicable to roaming. Supplementary Services (most important): • Call Forwarding (note doesn’t work for SMS). • Call Barring (some phones supported for SMS). • Calling Line Identification (CLI). • Call Waiting. • Call Hold. • Multi-party communications (MPTY, up-to 5). • Advice of Charge (AoC, online charging info). • Unstructured Supplementary Services Data (USSD, operator-defined individual services), often used for prepaid charging and in roaming. • Operator-determined barring (ODB, operator restrict features for individual subscribers). • Closed User Group (CUG). • A few others …
  137. 137. GSM FDMA & TDMA. Frequency & Time Division Multiple Access. 1 2 3 4 5 6 8 7 200 kHz Channel Bandwidth 8 Users (or Time Slot) per Channel F1, UL 902.3 MHz Carrier Frequency Mobile to Base Station (UL) 1 2 3 4 5 6 8 7 200 kHz Channel Bandwidth 8 Users (or TS) per Channel F1, DL 947.3 MHz (+45 MHz) Carrier Frequency Base Station to Mobile (DL) 20 MHz 890 MHz 915 MHz 935 MHz 960 MHz In GSM this is also called a TRX (2×0.2 MHz) 45 MHz Duplex separation Total of 125 Channels Max, 1,000 Simult. Users 25 MHz / 0.2 MHz 125 Ch × 8 Users/Ch Time Slot can be transmitted at various specified intensities (or power levels) 1 Time Slot (TS) possible reserved of signaling.
  138. 138. 144 Connectivityspectrum is the growth engine. CAPACITY Ci = BANDWIDTH Bi MHz × EFFICIENCY Ei Mbps per MHz per Cell × CELLS Ni # GSM Ctot ≈ 40k n x 0.2 MHz (TRX) (n: 6 – 15) ~ 0.52 (GSM) 0.14 – 0.33 (EDGE) 80k – 100k (Utilization ≈ 50+%) Frequencies Total Bandwidth 900 & 1800 MHz Ca. 110 MHz UMTS Ctot ≈ 600k (×15 GSM) n x 5 MHz (carrier) (n: 2 – 4) 0.5 – 1.2 (average) up-to 17 (peak) 80k – 100k (Utilization* ≈ 70+%) Frequencies Total Bandwidth 2100 (900) MHz 60 (95) MHz LTE Ctot ≈ 4,500k (×8 UMTS) n x 5 MHz (carrier) (n: 6 – 10+) 1.5 – 3.0 (average) Up-to 30 (peak) 80k – 100k (Utilization* ≈ 90+%) Frequencies Total Bandwidth 700 -900MHz, 1.8GHz, 2.5GHz 210+ MHz Note: Above only FDD spectrum is considered. Bandwidth are represented by DL part (i.e., total BW = 2x(DL or UL for symmetric bands). (*) pending on terminal type and application a single customer can in theory cause the a given cell to be highly utilized in terms of bandwidth resources.
  139. 139. Basic GSM network architecture. Supporting Voice and SMS and ISDN-data connections. Cells Cells BTS BTS BSC MW Radio Fixed Line Core Network HLR EIR MSC IT – VAS (e.g., SMSC, VMS, IN, MMSC, IVR,..) , Billing, Rating, CRM, … PSTN FPLMN AUC VLR Many BTS to 1 BSC Many BSC to 1 MSC Several Cells per BTS Air-interface Home Location Register Subscriber details & services allowed Authentication Center Authenticate each SIM attempting to connect. Equipment Identity Register List of phones banned or monitored. Visitor Location Register Temporary Data from HLR & MS.MS MS Interconnect to external networks
  140. 140. IT & VAS landscape (data center). Billing Platform (post-paid billing) Prepaid Rating & Charging Platform (Real-Time) CRM: Customer Relationship Management. ERP: Enterprise Resource Planning Platforms (e.g., SAP, HR, Clarify…). SMS-C: SMS Center VMS: Voice Mail System IN: Intelligent Network (for prepaid) Bulk SMS-C: Wholesale SMS M2M Server: Machine- 2-Machine Server IVR: Interactive Voice Response Server. MMSC: Multi-Media Messaging Center <100 km on Fiber SAN (secondary): Storage Area Network SAN: Primary Customer Fraud Voucher Device CEM Customer Experience Management OSS: Operations Support Systems BSS: Business Support Systems IllustrationTelco Network, Intra- & internet Shops, Call Center(s), Etc.. Web Portal(s)
  141. 141. GSM elements & basic functions. HLR VLR MSCBSCBTS Backbone (transport: SDH) Backhaul (transport: MW, LL) GW PSTN FPLMN Air-interface MS MS – Mobile Station = SIM + Device. - Authentication & Authorization. - Transmit & receive voice & data over the cellular system. - Measuring surrounding cells for optimum performance. - Encoding & encryption of signals. BTS – Base Transceiver Station. - Transmit & receive radio signals from MS over the air interface. - Decode & decrypt signal from MS. - Encode & encrypt signal to MS. - Radio condition measurements from MS. - Each cell under a given BTS is served only by that BTS. Interconnect (transport: SS7, SDH) BSC – Base Station Controller. - Radio Resource management for BTS under BSCs control. - Handover (inter-cell). - Capacity & Quality optimization. - Traffic concentration towards MSC. - Operations & Management interface for whole Base Station Subsystem. Base Station Subsystem (BSS) Network Switching Subsystem (NSS)
  142. 142. GSM elements & basic functions. HLR VLR MSCBSCBTS Backbone (transport: SDH) Backhaul (transport: MW, LL) GW PSTN FPLMN Air-interface MS MSC – Mobile Switching Center. - Switching of all calls. - Signaling (control) - Paging. - Location registration. - Call setup of all MSs in area. - Handover management. - Dynamic resource allocation. - Encryption. - Billing for all subscribers in area. - Interworking with other networks. - SMSC Gateway. - Possible to have several BSS controlled by 1 MSC. HLR – Home Location Register. - subscriber related information. - Record of supplementary services subscription for each customer. - Permission control granting access to supplementary services. - Some data are permanent, others temporary changing depending on customer movements & actions. - Data Stored (perm): IMSI, MSISDN, Roaming restriction, supplementary services parameters, AUC parameters, MS category, … Interconnect (transport: SS7, SDH) VLR – Visitor Location Register. - Often integrated into the MSC. - Supports MSC in storage and retrieval of subscriber info within its area. - Info stored is temporary as it will reside there only as long as subscriber is within related MSC area. - Roaming customers will reside here as well. Data Stored: IMSI, TMSI, MSISDN, LAI, MS category, Supplementary services parameters, AUC parameters, MSC id, … Base Station Subsystem (BSS) Network Switching Subsystem (NSS)
  143. 143. Basic GSM Architecture. HLR VLR MSCBSCBTS Backbone (m × 155 Mbps) Backhaul (n × 2 Mbps) GW PSTN FPLMN n × 0.2 MHz  ~ 0.52 Mbps/MHz e.g.,, 9 TRX per site  ~ 1 Mbps backhaul which typically would result in leasing an E1 (2Mbps) / T1 (1.5Mbps) or 2 or 4x2Mbps MW Typically 155 Mbps (e.g., STM1) could support between 45 – 55 BTS with 2 Mbps transport solution (at 70% utilization). STM - Synchronous Transmission Module defined on Synchronous Optical Networking (SONET) / Synchronous Digital Hierarchy (SDH). Can support bit rates of up-to 38 Gbps (STM256)* (*) SDH: https://en.wikipedia.org/wiki/Synchronous_optical_networking, STM1: https://en.wikipedia.org/wiki/STM-1
  144. 144. Basic GSM network structure. PLMN Service Area (e.g., Telenor Myanmar Mobile Network) MSC VLR MSC VLR MSC VLR MSC VLR MSC Area (e.g., MSC Yangon) Location Area LA1 LA3 LA2 LA5 LA6 LA4 Cell1 Cell2 Cell3 Cell4 Cell8 Cell12 Cell6 … … … … PLMN: Public Land Mobile Network, MSC: Mobile Switching Center, VLR: Visitor Location Register, LA: Location Area.
  145. 145. GSM Hierarchy. PLMN MSC Area MSC Area . . . . . . LA1 LA2 LA3 LA4 . . . BSC1 BSC2 . . . BTS1 BTS2 . . . . BTSn BSCj LAi Cell1 Cell2 Cell3 Site location 3 Sector per BTS Location Regional assignment Regional assignment Operator’s footprint Every BTS radio transmitter transmit a Location Area Identity (LAI) = MCC + MNC + LAC LAI Mobile Country Code (MM 95) Mobile Network Code (OM 05) Location Area Code (MNO def.) MS VLR HLR Mobile Station (MS) location LAI info resides here Note: depending on the size of the BSC (i.e., number of cell associated with it) it is possible for a BSC to be supporting more than one LA. Similarly within a BTS it is possible that a cells might be allocated to different LA’s (though in general should only be the exception than the Rule). For GPRS/EDGE a routing areas is defined within LA
  146. 146. I have “forgotten” something … but what?
  147. 147. The SIM card.
  148. 148. Subscriber Identify Module (SIM). 1991 20122008 • The SIM card is an integral part of the overall GSM System Architecture as well as any cellular standard evolved from that such as UMTS and LTE. • Without a working SIM the mobile device will not be able to connect to the network (beside for emergency services). • The SIM card uniquely identify the subscription & telephone number (MS-ISDN) upon which billing or rating/charging (for prepaid) is based. • Note 1 subscriber can have several SIM cards (and of course devices). SIM securely store the user’s unique id associated the particular cellular network: IMSI: International Mobile Subscriber Identity. IMSI = MCC Mobile Country Code, e.g., 414 for Myanmar. + MNC Mobile Network Code, e.g., 05 for Ooredoo. + MSIN Mobile Subscription Identification Number (10 digit).
  149. 149. Adding data to GSM – GPRS & EDGE. Cell Cell BTS BTS BSC MW Radio Fixed Line Core Network HLR/AUC (EIR) VLR MSC PSTN FPLMN WWW SGSN GGSN IT – VAS (e.g., SMSC, IN, VMS, IVR,..) , Billing, Rating, CRM, CEM,… Circuit Switched (CS) Domain Packet Switched (PS) Domain
  150. 150. Coverage & capacity example. Yangon city: • Yangon Area ~ 600 km2. • Yangon Population ~ 6 Million. • Average Density 10,000 per km2. • GSM effective range 1 km per site. • Unit Coverage Area =   = 2.6 km2 • Ca. 230 sites to cover Yangon. • Ca. 690 sectors with 3 sectors per site. • Note: given population density site range best practice should be lower than 1 km! • Market share 25%. • Customers ~ 1.5 Million. • Minutes per Month per Customer ~ 100 Min. of Use (MoU). • 5 minutes per day and ca. 1 minutes in Busy Hour (BH). • Total minutes per BH 1.5 Million Minutes. • With 690 sectors we have • ~ 2,200 customers per sector (over BH). • ~2,200 BH minutes per sector (demand). • Operator has 2×5 MHz @ 900 MHz for GSM. • 25 TRX (i.e., 5 MHz / 0.2 MHz) available in network. • Re-use pattern of 7 implying 25/7 ~ 3.5 TRX per sector. • At 2% GoS and 3.5 TRX (or carriers) per cell this will only supply ca. 1,200 MoU per Sector about half the required capacity.  Result in very poor quality with severe service level. • Options: • Built more sites: ~ 1,250 sectors, +560 sectors ~ 187 sites. • More to Re-use pa ern of 4 → 6 TRX per Sector → 2,200 MoUs @ 2% GoS (however also a lot more interference). See also: http://www.wirelesscommunication.nl/reference/chaptr04/cellplan/reuse.htm & http://docplayer.net/697830-Dimensioning-and-deployment-of-gsm-networks.html Group Discussion
  151. 151. Quiz 1. What initially made GSM so attractive to consumers? a) Cool handsets (e.g., iPhone) b) Wireless & enabling mobile. c) You got your own SIM card. 2. Which statements below are correct? (could be more than one!) a) GSM is based on TDMA and FDMA (8 timeslots for each 200 kHz carrier). b) GSM was developed because engineers had nothing better to do. c) GSM spectrum structure is TDD (time division duplex). d) GSM strived for higher spectral efficiency (supporting large amount of customers) using digital technology. e) GSM introduced the SIM in order to improve identification of customers and provide better security against unlawful tapping of conversations. f) SIM stands for Subscriber Identity Module and uniquely identify the customer. g) GSM voice services are based on circuit switched technology. h) With GSM a unified mobile technology was created with sufficient scale and economics that it would be affordable for most consumers and operators.
  152. 152. UMTS & HSPA. Universal Mobile Telephony System & High Speed Packet Access. 3rd & 3.5th Generation Mobile Systems.
  153. 153. Principles behind UMTS. Wide-band Code Division Multiple Access (W-CDMA). FDMA Traffic Channels: different frequency bands are allocated to different users. Very common in analogue telephony systems, e.g., NMT & AMPS. TDMA Traffic Channels: different time slots & frequency channels are allocated to different users. Common in 2nd generation digital mobile systems e.g., GSMT & D-AMPS. CDMA Traffic Channels: different users are assigned unique code and usage transmitted over the same frequency band, e.g., UMTS & CDMA2000 (USA standard). Wide-band simply distinguish system from narrow-band (1.25 MHz) Power Power Power Source: based on Huawei presentation.
  154. 154. Understanding the Code in UMTS. Chinese Chinese Chinese Danish Danish Italian Italian Hungarian Hungarian “The Cocktail part analogy to CDMA”
  155. 155. Basic business model of UMTS. Internet in your pocket! Vision anno 2000 – 2001 (iPhone was still 7 – 8 years away!! Future = Nokia)
  156. 156. The smartphone … from 2008 onwards The “killer” device and its “killer” applications…
  157. 157. 164 Source: Pyramid Research. Voice Revenue Growth suffers as penetration of Broad Band increases!
  158. 158. 15.7 Voice SMS Appenomics not so great for operators. Apps “attacks” the highest margin. services. 22.4 1 12.7 1 Source 2010 & 2015 Pyramid Research, Western Europe. 2010A MNO Centric ARPU 2015E Apps Centric ARPU (Free) OTT VoIP and Messaging Apps can lead to dramatic loss of MNO revenue and margin. 15.7 Voice 3.4 SMS 3.3 Data 6.5 Voice 6.2 1 Data ?By 2015 more than 70% of users have a smartphone + 9.7+ Data ARPU ARPU Death to SMS. VoIP @ Home & Work. 43% Missing
  159. 159. 166 Mobile broadband… feels like this? INDUSTRY FEAR
  160. 160. A new usage paradigm … 1 + 1 is no longer “just” 2 1 User Multiple Device User & application initiated bandwidth demand. Device & application (IP address, keep alive, …) driven signaling resources. Many applications
  161. 161. 168 NOTE: WiFi is just a bridge to better cellular small-network systems become main stream with controlable spectrum assets and E2E Customer Experience Management. @ Work (2 – 4 Cells) @ Home (2 – 3 Cells) On the Go @ Home (1 – 2 Cells) On the Go 00:00 10:00 12:00 22:0017:006:00 8:00 voicedata Small Cells 14:00 Femto Cell Femto Cell On-load potential WiFi +18 month The digital consumer.
  162. 162. Customer cellular trends to be considered. Source: The “Cellular Data Usage” distribution based on detailed data mining study, Mature Market Illustration. 80% of a customers traffic is delivered to no more than 3 cells Up-to 30+ Cells 2 – 4 Cells 1 -3 Cells
  163. 163. UMTS spectrum and bandwidth. Frequency in MHz Channel Bandwidth 5 MHz Channel Bandwidth 5 MHz Duplex Separation 190 MHz Power 1,920 1,980 2,110 2,170 60 MHz 12 UMTS Channels of 5 MHz UL DL Other MHz bands are also in use for UMTS: • 1,850 - 1,910 (UL) + 1,930 - 1,990 (DL) (USA PCS-band) • E-GSM 880 – 915 (UL) + 925 – 960 (DL). • Most other bands initially earmarked for UMTS are being deployed for LTE. • Both 2100 and GSM900 bands are being re-farmed to LTE or planned to be. UMTS DL Spectral efficiency: • R99 η = 0.15 Mbps/MHz • HSDPA η = 0.9 Mbps/MHz • 2015 η = 1.5 Mbps/MHz UMTS2100 Typically operators have between 2 to 3 UMTS Channels
  164. 164. 171 Connectivityspectrum is the growth engine. CAPACITY Ci = BANDWIDTH Bi MHz × EFFICIENCY Ei Mbps per MHz per Cell × CELLS Ni # GSM Ctot ≈ 40k n x 0.2 MHz (TRX) (n: 6 – 15) ~ 0.52 (GSM) 0.14 – 0.33 (EDGE) 80k – 100k (Utilization ≈ 50+%) Frequencies Total Bandwidth 900 & 1800 MHz Ca. 110 MHz UMTS Ctot ≈ 600k (×15 GSM) n x 5 MHz (carrier) (n: 2 – 4) 0.5 – 1.2 (average) up-to 17 (peak) 80k – 100k (Utilization* ≈ 70+%) Frequencies Total Bandwidth 2100 (900) MHz 60 (95) MHz LTE Ctot ≈ 4,500k (×8 UMTS) n x 5 MHz (carrier) (n: 6 – 10+) 1.5 – 3.0 (average) Up-to 30 (peak) 80k – 100k (Utilization* ≈ 90+%) Frequencies Total Bandwidth 700 -900MHz, 1.8GHz, 2.5GHz 210+ MHz (450 MHz – 3.6 GHz) Note: Above only FDD spectrum is considered. Bandwidth are represented by DL part (i.e., total BW = 2x(DL or UL for symmetric bands). (*) pending on terminal type and application a single customer can in theory cause the a given cell to be highly utilized in terms of bandwidth resources.
  165. 165. 172 Connectivity UMTS voice capacity leapfrogging voice capacity compared to GSM. Max. 8 voice users Per MHz/Sector Max. 12 voice users Per MHz/Sector Max. 48 voice users Per MHz/Sector Source: “Voice over LTE (VoLTE)” by Miikka Poikselka, Harri Holma, et all (Wiley 2012). UMTS
  166. 166. UMTS maximum DL speed performance. Only achievable under ideal conditions and the effective real experience of customers will be a lot lower. 5 MHz 10 MHz 15MHz 20 MHz to 40 MHz 40 MHz Time R99 R11
  167. 167. UMTS maximum DL performance. Only achievable under ideal conditions and the effective real experience of customers will be a lot lower. Max. Speed in Mbps = Max. Spectral Efficiency η in Mbps/MHz × Available Spectrum in MHz Normal Range of MHz Max. Limit for most MNOs
  168. 168. Basic UMTS network architecture. Cell Cell Node-B Node-B RNC MW Radio Giga-bit Ethernet / Fibre Optical connections HSS VLR MSS NG-IT – VAS, Billing, Rating, CRM, Big Data (structured & unstructured), … PSTN FPLMN WWW MGW Policy AAASGSN GGSN RRUs RRUs RRU: Remote Radio Unit moves the Rx & Tx from cabinet to or near the antenna. Inc. AUC Node Server Baseband OSS Circuit Switched (CS) domain Packet Switched (PS) domain
  169. 169. Packet Switched (PS) Domain CS Core Basic UMTS architecture. HSS VLR MSS RNCNode-B IP Backbone (10 – 100 Gbps) Fiber IP Backhaul (typically ~ 100+ Mbps) Fiber or MW MGW PSTN FPLMN Bandwidth = n × 5 MHz mean up-to 1.2 Mbps/MHz per sector peak up-to 17 Mbps/MHz per sector Circuit Switched (CS) Domain Cloud-RAN (optional)RRUs • Moving traditional functionality (e.g., Baseband or BS Server) from site to “centralized” cloud. • Radio Resource pool SGSN IP / Core WWW Not required for Cloud-RAN RRU: Remote Radio Unit, RNC: Radio Network Controller, Radio HSS: Home Subscriber Server, VLR: Visitor Location Register, MSS: Mobile Switching Sever, MGW: Mobile Gateway, SGSN: Serving GPRS Support Node, GGSN: Gateway GPRS Support Node, AAA: Authentication, Authorization & Accounting. GGSN AAAPolicy optional @ 15 MHz DL on 3 sectors → Average Site throughput ~ 54 Mbps. Peak Site throughput ~ 378 Mbps (~ 10 ms)
  170. 170. Quiz 1. UMTS was develop with what in mind? a) Higher data rates supporting internet in your pocket. b) To make Apple & Google happy. c) An simple extension of GPRS & GSM. 2. UMTS is based on? a) FDMA only (frequency division multiple access). b) TDMA (time division multiple access) & FDMA only. c) CDMA (code division multiple access). 3. The frequency carrier bandwidth of UMTS is? a) 200 kHz. b) 1.25 MHz, 3 MHz, 5 MHz, 10 MHz, 15 MHz and 20 MHz. c) 5 MHz. 4. What has happened to voice usage and revenue after introduction of UMTS? a) Voice traffic & voice revenue has increased after UMTS. b) Voice traffic & voice revenue has decreased after UMTS. c) Voice traffic has kept increasing but voice revenue has decreased after UMTS.
  171. 171. & LTE-advanced. Long Term Evolution (advanced). 4th Generation Mobile Systems.
  172. 172. 179 UMTS growth pains. Initially with UMTS. Tougher future … UMTS growth limitations.  Need for much higher spectral efficiency.  Need for more economical technology.  Need for much more spectrum.
  173. 173. Why do we need LTE? ”The writing on the wall” … The urgency of getting something better than UMTS. UMTS spectral efficiency cannot make up for increased mobile data demand1 Mounting cash pressure resulting in End-to-profit exposure for MNOs with UMTS Time Spectral supply Spectral demand For UMTS only Breaking Point 2014 - 2016 Western Europe assessment Business model breakdown Mounting cash pressure CAGR 33% CAGR 26% Illustration The real “scissor effect”:
  174. 174. LTE status as of End-2015. Source: http://gsacom.com/paper/spectrum-bands-used-in-480-commercially-launched- lte-networks/ More than half (552 Million) of that was gained during 2015! Comprising 157 Countries. 54+% from APAC
  175. 175. The LTE Vision (2004). Care should be taken as the LTE Vision was derived comparing HSPA Release 6 (2H2014). • Spectral efficiency 2 – 4 × HSPA which was ca. 0.9 Mbps/MHz. • Achieved using OFDMA (Orthogonal FDMA) in DL and DS-FDMA (Single Carrier FDMA) in UL. • For details see “LTE for UMTS – Evolution to LTE-advanced” by Harri Holma & Anti Toskola (Wiley) • Peak data rates exceed 100 Mbps DL & 50 Mbps UL. • 10+ × the performance of HSPA at the time. • Round trip time (RTT) of 10 ms. • HSPA RTT was 40+ ms at the time. • Highly flexible spectrum bandwidth; 1.5 – 20 MHz. • Remember UMTS/HSPA came in 1 flavor, 5 MHz. • Optimized end user’s terminal power efficiency. History: • Standard approved in End-2007. • First commercial LTE networks launched 2010. • By January 2016; 1+ Billion subscriptions & 480 commercial networks.
  176. 176. The LTE advanced requirements. • Carrier aggregation of contiguous and non-contiguous spectrum allocations. • 100+ Mbps peak for highly mobile users (350km/h). • 1+ Gbps peak for nomadic and stationary users. • Scalable system bandwidth up-to 100 MHz. • Asymmetric bandwidth assignments for FDD (e.g., 20 MHz UL / 40 MHz DL). • and a lot more really cool stuff. History: • Standardization started in 2008. Standard approved 2011. • First commercial handsets in 2014/2015 (1 in 2013). • 116 operators (24%) launched LTE-advanced (primarily for carrier aggregation).
  177. 177. (Some of them)
  178. 178. FDD-LTE commercial launches. GSM legacy band of 2×75 MHz usually easy to re-purpose. (all-round coverage, good capacity) Lots of spectrum (70MHz) available, usually virgin spectrum. (good for small cells & urban coverage with good capacity) Relative scarse but in cellular sense usually virgin spectrum. (very good coverage, limit capacity) In use for UMTS and thus relative little capacity available now (overlay coverage to existing UMTS) Asia and South America. old broadcast / analogue tv spectrum (very good coverage & good capacity)
  179. 179. 187 Connectivityspectrum is the growth engine. CAPACITY Ci = BANDWIDTH Bi MHz × EFFICIENCY Ei Mbps per MHz per Cell × CELLS Ni # GSM Ctot ≈ 40k n x 0.2 MHz (TRX) (n: 6 – 15) ~ 0.52 (GSM) 0.14 – 0.33 (EDGE) 80k – 100k (Utilization ≈ 50+%) Frequencies Total Bandwidth 900 & 1800 MHz Ca. 110 MHz UMTS Ctot ≈ 600k (×15 GSM) n x 5 MHz (carrier) (n: 2 – 4) 0.5 – 1.2 (average) up-to 17 (peak) 80k – 100k (Utilization* ≈ 70+%) Frequencies Total Bandwidth 2100 (900) MHz 60 (95) MHz LTE Ctot ≈ 4,500k (×8 UMTS) n x 5 MHz (carrier) (n: 6 – 10+) 1.5 – 3.0 (average) Up-to 30 (peak) 80k – 100k (Utilization* ≈ 90+%) Frequencies Total Bandwidth 700 -900MHz, 1.8GHz, 2.5GHz 210+ MHz Note: Above only FDD spectrum is considered. Bandwidth are represented by DL part (i.e., total BW = 2x(DL or UL for symmetric bands). (*) pending on terminal type and application a single customer can in theory cause the a given cell to be highly utilized in terms of bandwidth resources.
  180. 180. 188 ConnectivityLTE voice capacity LTE voice capacity is on par or substantial better than UMTS. Max. 8 voice users Per MHz/Sector Max. 12 voice users Per MHz/Sector Max. 48 voice users Per MHz/Sector Source: “Voice over LTE (VoLTE)” by Miikka Poikselka, Harri Holma, et all (Wiley 2012). LTE
  181. 181. Basic business models of LTE. More of the same same just better! Fixed substitution Smartphones Faster 4 Zero Xtra Scalability ConvergenceLarger Data Plans
  182. 182. Basic LTE network architecture. Cell Cell BTS (GSM) Node-B (3G) eNode-B (LTE) pool Fibre (1 – 10 Gbps) HSS NG-IT – VAS, Billing, Rating, CRM, Big Data (structured & unstructured), … RRUs RRUs RRU: Remote Radio Unit Cloud RANFibre (1 – 10 Gbps) SGSN Evolved Packet Core (All-IP) S-GW Policy RADIUS MME Most LTE EPC functions likely to end up as NFV in MNO DC. P-GW IMS IT Service Cloud Backend Data Center Connect to 2G & 3G Shared with 2G/3G CS domain Expanded AAA function e.g., PCRF More complex antenna solutions → higher spectral efficiency VoIP / VoLTE
  183. 183. LTE terminal categories (backup). Up-to 3GPP Release 11 (September 2012) Cat 1 Cat 2 Cat 3 Cat4 Cat5 Cat6 Cat7 Cat8 Cat9 Cat10 cat11 cat12 3GPP Release 8 8 8 8 8 10 10 10 11 11 11 11 DL Speed Mbps 10 50 100 150 300 300 300 3000 450 450 600 600 UL Speed Mbps 5 25 50 50 75 50 100 1500 50 100 50 100 Max. #DL-SCH transport blocks Rx in a TTI 10,296 51,024 102,048 150,752 302,752 299,552 299,552 2,998,560 452,256 452,256 603,008 603,008 Max. # bits of a DL-SCH transport blocks Rx in a TTI 10,296 51,024 75,376 75,376 151,376 tbd Tbd tbd Total # of soft channel bits 250,368 1,237,248 1,237,248 1,827,072 3,667,200 3,667,200 3,654,144 359,827,7 20 5,481,216 5,481,216 7,308,288 7,308,288 Max. # of supported layers for spatial multiplexing in DL 1 2 2 2 4 2 or 4 2 or 4 8 2 or 4 2 or 4 2 or 4 2 or 4 Max. # of bits of an UL-SCH transport block Rx in a TTI 5,160 25,456 51,024 51,024 75,376 tbd Tbd tbd Support for 64 QAM in UL No No No No Yes No Yes Yes Yes Yes Yes Yes Support for 256QAM in DL No No No No No No No No No No optional Optional MiMo DL Optional 2x2 2x2 2x2 4x4 4x4 4x4 8x8 4x4 4x4 4x4 4x4 Note: In 3GPP Rel 12 a new set of terminal categories was defined: Cat0, Cat13 – Cat16.
  184. 184. 2020 and beyond
  185. 185. What will 5G bring? Standardization still work-in-progress. • Indoor user experience of 1 Gbps DL & 500 Mbps UL. • User experience @ cell edge: 300 Mbps DL & 50 Mbps UL and mobilities up to 100 km/h. • Latency from 1 - 10 ms. • IoT support 1 – 100 kbps, E2E latency seconds – hours at connection densities of up to 200 thousand per km2. Target device autonomy (lifetime) up-to 15 years. • Full Conversion of fixed and mobile services. • Elastic and dynamic service slicing (i.e., “on-the-fly” service provisioning end-2-end). Standardization timelines ~ initial submission June 2019 and detailed submission by October 2020. Source: https://www.ngmn.org/uploads/media/NGMN_5G_White_Paper_V1_0.pdf

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