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Make better business decisions
11/09/2009
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30/03/2011
Modeling mobile broadband
network costs:
LTE and offload case studies
Dimitris Mavrakis – Senior Analyst | Networks30th March 2011
Our legacy
The problem
Our model
Case studies
Presentation outline
Our legacy
11/09/2009www.informatm.com
©Confidential
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30/03/2011
• WCIS: 5 million data points, 10000+ cellular handsets, MNO ownership, network
summary data
• Intelligence Centre: Quantitative and qualitative analysis, including subscriber,
traffic and base stations forecasts
Informa’s key strengths
How can we make this data relevant to the business case of a
mobile operator or an infrastructure vendor?
• I.e translate our subscriber and traffic data to revenues, ROI, CAPEX,
and network TCO?
• First step towards this is to estimate cost to transfer a GB (Cost/GB) and
network costs
• Why should we do this?
30/03/2011www.informatm.com
©Confidential
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30/03/2011
Challenges facing mobile operators
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Reve
nu
es
or
tra
ffic
Traffic (cost?)
Revenues
Voice driven networks• All users treated equally
• Simple dimensioning
• Simple to add more capacity
• Abundant backhaul capacity
Voice Data
Mobile broadband networks• All users not treated equally
• Complex dimensioning
• Variety of upgrade options
• Backhaul challenges
Operators need answers
• When will the network face congestion and demand capacity upgrades?
• What is the most cost effective solution to meeting future traffic demand?
• What are the key network cost drivers?
• How do different geotype deployment strategies affect the cost per GB?
• Is LTE needed in the short to medium term?
• What are the savings from data offload, including WiFi and femtocells?
• What are the savings from introducing network optimisation?
• Analyse the impact of indoor traffic versus outdoor traffic?
Given the current and expected growth in mobile traffic, what are the
most cost effective ways that operators can deploy future networks
to successfully manage traffic demand?
30/03/2011www.informatm.com
©Confidential
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Our model
11/09/2009www.informatm.com
©Confidential
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Inputs
• Network deployment scenarios• Radio access Technologies: HSPA, HSPA+, LTE
• Traffic Management: Optimization, policy based management, offload
• Spectrum: Various options for each technology
• Relevant network costs• Network OPEX + Depreciation of Network CAPEX = Total Cost of Ownership (TCO)
• Cost classification and behaviour (Traffic Demand Scenarios)• Service category: mobile Internet, social networking, portable Internet etc
• Technology: HSPA, HSPA+, LTE
• Geotype: Dense Urban, Urban, Suburban, Rural
• Indoor/outdoor traffic segmentation
• Methodology validation
• Results validation
Methodology outline
30/03/2011www.informatm.com
©Confidential
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Population information
• Total population
• Distribution (per geotype)
• Operator subscriber base and targets
Country information
• Total area (per geotype)
• Coverage requirements
Traffic demand
• Capacity requirements
• Per technology
• Per geotype
• Per device type
• Per subscriber
• Indoor/outdoor
Network deployment
• Spectrum
• Technology
• Backhaul
• Core network
• Offload
• Optimization
Network
TCO
Cost/GB
Traffic
demand
methodology
30/03/2011www.informatm.com
©Confidential
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Country
demographics
Operator network coverage
Operator subscriber
base
Operator network
traffic
Option 1: Traffic
by device type
only
Option 2: Traffic
by device type &
traffic class
Traffic optimisation
Total traffic demand
Network
deployment
model
Network
deployment
model
Network
deployment
model
•Population size & growth
•Population density by
geotype (dense urban,
urban, suburban, rural)% coverage of population by geotype
•Penetration of population•Subscribers by device type (non-smartphones, smartphones& portable devices)
2 options depending on information availability
Average MB per device typeIndoor & outdoor traffic splitTraffic by geotype
Average MB per device type per traffic classIndoor & outdoor traffic splitTraffic by geotype
By device type, traffic class & geotype
By device type, traffic class, geotypeOptimised & unoptimised
Case study: UK operatorHSPA vs LTE
30/03/2011www.informatm.com
©Confidential
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UK market: Subscriber information
11/09/2009www.informatm.com
©Confidential
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Dense Urban16,625,473
27%
Urban22,167,297
36%
Suburban15,164,784
25%
Rural7,686,764
12%
• Dense Urban and suburban areas dominant
• Rural deployments still driven by coverage
UK: traffic profiles
30/03/2011www.informatm.com
©Confidential
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0
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2010 2011 2012 2013 2014 2015
Ac
tive
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(m
illi
on
s)
Non-smartphone Smartphone Portable Total
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Non-smartphone data Smartphone data Portable data
Inflection point in 2014 not enough to drive
smartphone traffic higher than portable
Device classAverage traffic per month
Annual growth rate
Non-smartphone 25MB 30%
Smartphone 250MB 30%
Portable 2GB 30%
UK network modeling parameters
30/03/2011www.informatm.com
©Confidential
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Dense Urban parameters
Technology WCDMA 100% coverage
Technology HSPA 90% coverage
Technology HSPA+ (hotspot) 20% coverage
Backhaul technologyMix of T1/E1 for WCDMA/HSPA sites and Point-to-point RF or leased fiber for HSPA/HSPA+ and hotspots
Urban parameters
Technology WCDMA 100% coverage
Technology HSPA 80% coverage
Technology HSPA+ 30% coverage
Backhaul technologyMix of T1/E1 for WCDMA/HSPA sites and Point-to-point RF or leased fiber for HSPA/HSPA+
Suburban parameters
Technology WCDMA 90% coverage
Technology HSPA 70% coverage
Backhaul technologyMix of T1/E1 for WCDMA/HSPA sites and Point-to-point RF or leased fiber for HSPA/HSPA+
Rural parameters
Technology WCDMA 70% coverage
Technology HSPA 30% coverage
Backhaul technology T1/E1 for WCDMA coverage and Point-to-point RF for HSPA
Baseline WCDMA and
HSPA network
Geotype Constraint
Dense Urban 2013
Urban No constraint
Suburban 2013
Rural 2012
Capacity constraints
UK network costs
30/03/2011www.informatm.com
©Confidential
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0
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2011 2012 2013 2014 2015
Ne
tork
TC
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US
$ m
illi
on
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Dense Urban Urban Suburban Rural
Worst case scenario:
Capacity upgrades will be handled
through new base station additions
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Co
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S$
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UK case study: Key takeaways
• Network costs are dominated by OPEX (~80% of annual TCO)
• Dense HSPA network can generally handle traffic
– Apart from capacity hotspots that need to be managed
• LTE does not present an economically viable solution to meet with traffic
demands.
• A new LTE deployment will cost a minimum of US$58 million compared
to upgrades to existing networks, assuming that the LTE deployment
begins during 2013
30/03/2011www.informatm.com
©Confidential
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US operator case studyWiFi offload
30/03/2011www.informatm.com
©Confidential
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US network modeling parameters
11/09/2009www.informatm.com
©Confidential
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• Area modeled: Dense Urban
• Operator market penetration: 30% (today) increasing to 32% (2015)
• Traffic profiles:
– Non-smartphone = 15MB
– Smartphone = 250MB
– Portable = 3GB
– Annual traffic growth = 30%
• Spectrum used for mobile network
– 850MHz and 1.9GHz for WCDMA and HSPA/HSPA+
• Backhaul
– T1/E1, owned/leased fiber and microwave
US WiFi offload assumptions
• No cost to operator
• No visibility on user behavior and traffic
Private offload (home access
point)
• Operator leases WiFi capacity from third party
• Average cost of $1/GB offloaded
Public offload –leased capacity
• Operator installed WiFi network
• Number of hotspots: 23,000 today increasing to 50000 (2015)
• CAPEX per hotspot: $1000 today decreasing to $800 (3015)
• OPEX per hotspot: $200 today decreasing to $100 (2015)
Public offload –owned capacity
30/03/2011www.informatm.com
©Confidential
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Data offloaded: 10% of total portable traffic and 20% total
smartphone traffic
US network offloaded traffic
30/03/2011www.informatm.com
©Confidential
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Tra
ffic
(P
B a
nn
ua
lly)
Total traffic Traffic after offload
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To
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aff
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Dense Urban Urban Suburban Rural
US network base stations
30/03/2011www.informatm.com
©Confidential
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To
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Only new base station upgrades New base stations with WIFi offload
US network scenario comparison
30/03/2011www.informatm.com
©Confidential
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2011 2012 2013 2014 2015
An
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New BTS only New BTS and upgrades Private offload Public offload - leased Public offload - owned
WiFi offload key takeaways
• Offload strategies need to be carefully addressed in order to avoid additional costs.
• Private WiFi offload
– Best case in terms of cost, but no visibility on user behavior or traffic patterns.
• Public WiFi
– Best suited to solve capacity constraints in congested areas and operators can either partner with a
hotspot provider or deploy their own networks.
• Leasing WiFi
– Additional costs may break the offload business case and increase overall network costs as high as
radio access upgrade costs.
• Operator owned public WiFi
– Best suited to offload traffic in congested areas and allow operators to control the user experience
while providing necessary headroom for radio access networks.
– Costs involved in deploying nationwide hotspot networks but the available WiFi capacity to the
mobile operator can be significant.
• Specialist solutions for WiFi offload will appear in the market during 2011, including
gateways that interface WiFi with cellular networks. Standardization is also ongoing to
integrate two networks and allow mobility between WiFi and cellular networks.
30/03/2011www.informatm.com
©Confidential
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Overall conclusions
• Capacity constraints only appear in hotspots
–Selective upgrades necessary
• LTE not economically viable
–From current capacity demands perspective
–Other reasons for deploying now: first to market and future
• Even WiFi offload needs careful management
–Leasing WiFi bandwidth can be expensive
• Variety of tools available to operator
–Policy, optimization, offload are some examples
30/03/2011www.informatm.com
©Confidential
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11/09/2009
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30/03/2011
Thank you.
Dimitris MavrakisSenior Analyst, NetworksInforma Telecoms & Media
Email: [email protected]