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T E C H N O L O G Y W H I T E P A P E R
As data usage escalates, mobile service providers need a new
approach to delivering
a high quality of experience, while keeping costs down.
Alcatel-Lucent enables this
business and infrastructure transformation, with its pioneering
lightRadio architecture,
which distributes intelligence between the radio head, on-site
processors and centralized
processing over high-bandwidth and low-latency optical networks.
The architecture
also provides optimal configurations for each service providers
requirements, including
backhaul needs, to reduce the networks total cost of ownership
(TCO) significantly.
These innovations can allow service providers to benefit from
increased wireless demand,
while deploying highly optimized networks, reinforced by
powerful radio, transmission
and antenna advances.
This paper is one in a series authored by Alcatel-Lucent that
discuss the current state
of wireless networks and the benefits of transitioning to a
lightRadio architecture
that supports data and video traffic, now and well into the
future.
Portfolio: White Paper 2Economic analysis
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Table of contents
1 1.Introduction
1 2.Mobileserviceproviderpainpoints
1 2.1 Explosion of mobile devices and data traffic
3 2.2 Networks are not uniformly data loaded a new challenge
3 2.3 Mobile data profitability challenges
5 3.ImprovingmobiledataeconomicswithlightRadio
5 3.1 Alcatel-Lucent lightRadio
6 3.2 lightRadio economics at site level
8 3.3 Network evolution economics
9 3.4 Additional solutions to optimize data economics
9 4.Conclusion
10 5.Authors
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1. Introduction
Mobile service providers are facing many challenges today, as
they operate in a rapidly evolving market. End-user data usage is
rapidly increasing, with the proliferation of new devices, content
diversification and new multimedia applications. These new trends
result in:
Increased wireless data traffic that must be handled by networks
that were designed for voice transport.
End user expectations that data throughput speeds and QoS for
mobility services will be similar to those delivered by fixed
networks.
Declining revenue per bit from new applications, such as
streaming Internet video, compared to earlier offerings, like voice
and SMS, that generated extremely high revenue per bit. (Mobile
data now generates only 35 percent of revenues while consuming 54
percent of resources.)
New value chains, with players from IT, television and web
domains, that erode operators revenues but leave them with
transport costs.
It is imperative that service providers adapt both their
business and infrastructure to this changing landscape. This paper
highlights the pain points that result from todays key trends,
analyzes their impact on service providers economics and describes
what can be done to bring about improvements.
2. Mobile service provider pain
points2.1ExplosionofmobiledevicesanddatatrafficThe trend toward
smartphone and widescreen device adoption is continuing to
accelerate, with the number of smart devices in use expected to be
potentially 18 times higher in 2015 than in 2010. These new smart
devices will strongly impact network bandwidth and signaling
requirements, in varying ways.
For example, recent network traffic studies indicate that
BlackBerry and Android devices stress control and signaling
functions more than bandwidth. Conversely, Air cards (which support
continuous data sessions) and Apple iPhones and iPads impact
bandwidth more than signaling. In addition, the use of new mobile
multimedia services, connected device applications and
machine-to-machine services is expected to grow as the new wireless
IP infrastructures being implemented today sets the stage for rich
innovation and expansion of the wireless ecosystem.
What will mobile service providers face as this enriched
ecosystem and device proliferation combine with new technologies
that enable higher throughput? This combination is likely to result
in more diversified mobile applications, increased traffic per user
device and greater mobile device density. For example,
Alcatel-Lucent studies forecast that, in 2015, the number of
smartphones in urban areas will increase to 12,800 per urban square
kilometer, compared with approximately 400 per square kilometer
today: a 32-fold increase. The studies also indicate that global
wireless data traffic will grow 30 fold over the next five years.
In other words, the combination of all these factors is leading to
an unprecedented explosion of usage, referred to by experts as the
mobile data traffic tsunami.
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Figure 1. World-wide wireless traffic evolution (Source:
Alcatel-Lucent)
Global aggregate mobile traffic (Pbytes/month)
Feature phones Smartphones Widescreen devices
7,000
6,000
5,000
4,000
3,000
2,000
1,000
02010 2011 2013 2014 20152012
Consequently, mobile service providers need to deploy more
capacity in their networks, by increasing the number of sites and
using the latest technologies, such as LTE. However these steps can
raise other issues.
For example, increasing the number of sites addresses the need
for additional capacity. But it can result in higher costs for
operations, site rental, power consumption, civil works and in
increased network management complexity. In addition, service
providers are facing regulatory constraints that make it difficult
to acquire new sites and re-negotiate rights on existing sites to
introduce new technologies or make renovations.
Figure 2 shows key drivers of the total cost of ownership (TCO)
for a high-capacity macro indoor site in a European urban area.
Civil works, site rental and transmission are the top contributors
to radio access TCO. Consequently, service providers can realize
significant savings by decreasing or containing their site
footprint and associated network-related operating costs.
Figure 2. Radio access TCO breakdown reference
Site rental20%
Powerconsumption
7%
Operations7%
Maintenanceand repair
6% Equipment11%
Civil work14%
E&I&I3%
ND&O3%
Transmission29%
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Deploying new technologies, such as LTE, can help meet capacity
demands and lower cost per megabyte (MB) significantly. But to meet
future data demands at the lowest cost per MB, operators must
continue deploying solutions that reduce costs like site rental,
power consumption and operations.
2.2NetworksarenotuniformlydataloadedanewchallengeCapacity needs
are not uniform in the network. Some base stations are more heavily
loaded by wireless data traffic than others, and mobile networks
are witnessing a clear geographical disparity in base station load.
Therefore, a mix of flexible capacity-improvement solutions will be
needed to efficiently address both very dense, usually urban,
wireless data areas and lighter loads in rural areas.
As shown in the Figure 3, traffic is not uniform over time,
either, as users locations and usage patterns vary through the day,
changing the load on different base stations.
Figure 3. Wireless cells daily load (Source: Alcatel-Lucent
Wireless Network Guardian)
15
Traf
fic
(%)
10
5
25
20
0
Midday
Cell 1 Cell 2
Cell 3
Cell 4
MidnightMidnight
Today, mobile service providers are deploying solutions that
address each individual sites busy hour/peak hour capacity needs,
but this capacity is not fully used during off-peak periods.
Increased capacity utilization, while meeting peak demand, is key
to improving network economics.
2.3MobiledataprofitabilitychallengesWireless service providers
are all seeing dramatic increases in data traffic, as 3G
capabilities become widespread and new 4G capabilities are
deployed. However, not all providers are experiencing the same
level of growth in their data revenues. A subscriber with a
smartphone who uses 600 MB per month puts 6000 times more load on a
network than a heavy SMS user without a smartphone. But the
smartphone user brings in only about twice as much data revenue,
resulting in a declining revenue-yield per MB. Bell Labs analysis
estimates that the current cost per MB on a traditional
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macro network is between 5.5 US cents and 9.5 US cents for more
efficient and higher utilization networks. The range depends on
market, operator efficiency, density of cells and traffic carried.
As a result, wireless data traffic and associated costs are
starting to encroach on wireless data revenues and profitability
for many operators, as shown in Figure 4.
Figure 4. Costs compared with revenue for mobile data traffic
(Source: Alcatel-Lucent)
30
$/su
bsc
rib
er/m
on
th
20
10
50
40
0
20122006 2007
Source: Bell Labs Modeling and Network Planning Conservative
traffic model assumptions
2008
Revenue/subscriber
2009 2010 2011
Network cost/subscriber
Service providers can apply several options to counter this
scissor effect. For example, they can deploy usage caps, throttle
bandwidth for users who exceed usage caps and increase pricing for
mobile data services. However, in a competitive environment, such
strategies may increase churn by sending high-end users to other
operators that offer lower-priced mobile data services with higher
usage limits and no caps.
Leading operators are addressing this dual opportunity and
threat to their business by unscissoring both these curves. On the
revenue side, they are introducing new services, frequently with
third-party application and content partners, that are priced and
sold as services rather than data traffic. On the cost side, they
are planning and introducing new wireless technologies and
solutions that drive down the cost per bit transferred over their
network. This approach allows them to contain their overall total
cost of ownership and thus improve margins. With lower cost per
bit, operators can, in turn, introduce lower-priced plans that
expand the market by making services available to users who could
not otherwise afford them.
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3. Improving mobile data economics with lightRadio
To help mobile service providers contain their TCO, while
addressing their capacity needs, Alcatel-Lucent has developed key
simplifications in the network architecture, called lightRadio.
3.1Alcatel-LucentlightRadiolightRadio is a new product family
designed to dramatically improve network capacity while lowering
cost per bit. It delivers 2G, 3G and LTE technologies with a
defined path to LTE Advanced, and it works with multiple scale
points, from large macro-cells to small metros, across all
deployment morphologies from rural to dense urban. lightRadio also
includes the five radio access elements antennas, radios, baseband,
controllers and management. But it broadens the baseband
architecture to distributed intelligence; for example, in the
conventional baseband unit and centralized baseband.
lightRadio includes the following features:
Wideband active antenna arrays that can improve available
capacity by 30 percent, in urban and suburban settings, and survive
array element failure.
Multi-band remote radio heads that reduce the on-tower equipment
needed to service multiple frequency bands by a factor of two or
three.
Remotely programmable software-defined baseband, with digital
modules that can be used and reused for any demand mix of GSM,
WCDMA and LTE.
Digital modules usable in three deployment modes:
All-in-one for zero site footprint with minimum backhaul
Conventional BBU for easy transition of current sites
Centralized baseband with zero footprint, reduced OPEX, load
balancing and a path to 80-percent capacity gains, with coordinated
multi-point (CoMP) and inter-cell interference coordination
(ICIC)
Centralized baseband, facilitated by IQ signal aggregation and
state-of-the art compression, to minimize transport
requirements
Common family of macro and metro cell scale points that provides
consistent functionality, along with hot-spot data offload, and up
to six times greater capacity from the same spectrum lease.
Controllers software virtualized and separate from hardware to
allow Advanced Telecommunications Computing Architecture (ATCA),
Blade Server and private cloud delivery for lower cost and elastic
capacity
Wireless IP intelligence that understands the network and
responds to change more quickly
Self-optimizing network capabilities that automate complex
management of heterogonous networks
Network-wide visibility across wireline and wireless IP
elements
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3.2lightRadioeconomicsatsitelevelAn extensive TCO study,
conducted by Alcatel-Lucent Bell Labs Business Modeling, examined
different disruptive RAN architectures and innovative features that
can help mobile service providers face todays key operating
challenges. The study focused on a high-capacity macro indoor site
in a European urban area, in 2013. The findings from this
exhaustive analysis show the impact on five-year TCO provided by
different components of the new lightRadio architecture, compared
to a traditional state-of-the-art converged RAN solution, from both
a CAPEX and an OPEX perspective.
The new lightRadio architecture moves away from the traditional
architecture, with its static assignment of fixed-purpose and
digital processing functionality, to a shelf-based baseband unit
(BBU), typically located at each base station. The lightRadio
distributes intelligence appropriately between the radio head,
on-site processors, and centralized processing over high-bandwidth,
low-latency optical networks. This approach provides optimal and
flexible configurations for each service providers operating
requirements, including backhaul needs, thus minimizing TCO.
Figure 5. TCO benefits per disruptive lightRadio RAN features
and design
Expenses/components With controller cloud (*)
Zero footprint RF
With BB in RF (**)MB RRH and WB active
array antennasAdvanced OA&M
and SON
+
+
+ +CAPEX
Equipment
Civil works
E&I&I
ND&O
+++ + ++
++ ++ +++ +
+ ++ ++
OPEX
Transmission
Site rental
Power consumption
Operationsand maintenance
3.2.1 Zero footprint RF
The lightRadio architecture offers zero footprint options,
eliminating the need for a temperature enclosure to house a
conventional baseband unit. This option saves on heating and
cooling costs, as well as site rental costs in some cases. For new
or expanding sites, civil works costs to establish a pad and
enclosure can be eliminated. This point is critical in some new
urban sites, because they have no place for cabinet-mounted gear to
be located. Some operators are also considering elimination of
on-site battery backup, because secured AC power is now available
in some locations or the delivery grid is considered sufficiently
reliable. This step can provide additional savings.
The lightRadio architecture offers zero footprint deployment
options to meet varied operator needs.
The all-in-one option puts the baseband in the remote radio head
(RRH). It also works with restricted bandwidth backhaul.
The centralized baseband option achieves zero footprint and
enables easy load balancing and baseband maintenance and
augmentation. Although this option requires fiber for transport, it
makes the future LTE-Advanced features, CoMP and ICIC, easier to
implement.
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3.2.2 Multiband remote radio head and wideband active array
antenna
The wideband active array antenna (AAA) enables operators to
electrically control vertical downtilt, yielding approximately 30
percent gains in usable capacity. Working across multiple frequency
bands reduces costs and improves flexibility, and it is inherently
multi-technology.
The multiband RRH allows an operator with multiple frequency
bands to reduce the number of radio heads on a tower by half or
more.
3.2.3 Advanced OA&M and SON
To optimize network management, lightRadio automates manual
activities, using advanced OA&M and self-organizing network
(SON) capabilities, and provides process simplification and
flexibility with the controller cloud, multiband RRH and wideband
active array antenna. These capabilities reduce the number of
network operations needed to deploy and manage the network, as well
as maintain it.
As a result, lightRadio brings TCO efficiencies from 25 percent
to 66 percent on key cost components, as shown in Figure 6. These
components represent 48 percent of the overall TCO for a
high-capacity site in an urban area.
Figure 6. lightRadio benefits on TCO components
Siterental
-66%
-51%
Powerconsumption
-60%
Civilworks
-25%
Operationsand maintenance
Compared with a traditional state-of-the-art converged RAN
solution, these disruptive RAN architecture designs and innovative
features can reduce overall TCO by at least 20 percent over five
years for an existing high-capacity site in an urban area with
reductions of at least 28 percent reduction for new sites. (The
extent of reduction depends, in part, on site geography.)
3.2.4 Benefits from better compression techniques
As a result of data traffic increases, operators are introducing
new 3G carriers, adding LTE with wider bandwidths and using
advanced MIMO antennas to improve performance. These increases,
combined with centralization of baseband processing, can place a
significant load on the backhaul network. To address these demands,
Alcatel-Lucent is pioneering Common Public Radio Interface (CPRI)
compression techniques that reduce traffic by a factor of nearly
three. Research at Bell Labs promises further improvements to come,
allowing backhaul costs to be minimized. Exact cost savings from
compression will be highly dependent on specific service provider
and site requirements.
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3.2.5 Alcatel-Lucent commitment to reducing power
consumption
Alcatel-Lucent has already begun implementing several energy
efficiency options within lightRadio. The energy benefits of
lightRadio are based on:
Elimination of temperature-controlled enclosures for the
conventional baseband unit
Radio designs tuned to minimize off-peak power consumption
AAA to eliminate RF power losses in cables from RRH to passive
antennas
3.3NetworkevolutioneconomicsService providers can choose from a
number of options when evolving the network to cope with an
increased demand in capacity, and the solutions can be adopted
successively or alternatively. These choices depend on service
providers unique circumstances, in terms of capacity growth,
spectrum availability, time to market and overall competitive
situation.
In the following example, Bell Labs used the Wireless Strategy
Optimizer (discussed in section 3.4.3) to compare the total cost of
ownership for six different evolution scenarios for a Radio Access
Network. The network operated in an urban area, served 20 million
subscribers and was designed to meet wireless data traffic growing
30-fold over the next five years. The scenarios evaluated
included:
1. The base scenario, where traffic growth is managed by
deploying more capacity using 2G and 3G technologies, only, and
limited spectrum refarming.
2. 3G+ is deployed for capacity enhancement.
3. 3G+ and 3G small cells are both deployed.
4. LTE copes with capacity enhancement without 3G+
deployments.
5. LTE, 3G+ and 3G small cells are simultaneously used to absorb
traffic increases.
6. Traffic growth is managed through lightRadio and small
cells.
Figure 7. Benchmark on network TCO analysis over five years of
evolution
2010 2011
3G, 2G only
3G+
Smallcells
LTE
LTE andsmall cells
lightRadio
2012 2013 2014
0%
-10%
-20%
-30%
-40%
-50%
-60%
-70%
-22%
-27% -27%
-33%
-51%
Figure 7 shows the results for this five-year TCO comparison.
For a Radio Access Network that serves 20 million subscribers in an
urban area, lightRadio delivers TCO reductions of 51 percent over
five years, compared with the 2G- and 3G-only base scenario.
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In addition to TCO savings, the Wireless Strategy Optimizer
takes into account the subscriber migration and spectrum costs,
providing the service provider with a full view of their network
evolution costs.
3.4AdditionalsolutionstooptimizedataeconomicsAlcatel Lucent and
Bell Labs have developed several additional solutions to help
service providers cope with todays data explosion, optimize their
network investments and improve their overall economics.
3.4.1 Wireless Network Guardian
The Alcatel-Lucent 9900 Wireless Network Guardian (WNG) provides
an unparalleled view of how IP applications, devices and
subscribers load wireless networks, helping to determine the users
quality of experience (QoE). By collecting field data from the
service providers network, the Alcatel-Lucent 9900 WNG gives
service providers better ways to characterize subscriber group,
device and application behaviors, so they can understand the
associated impact on their network utilization, efficiency and
performance. This data can be input to the new data traffic
forecasting model to enable better capacity planning.
3.4.2 Mobile Data Analysis Model (MDAM)
Bell Labs has developed a methodology for characterizing mobile
data traffic. It is based on a detailed subscriber model that
captures a users experience with an application including how
frequently the subscriber invokes the application, the impact on
the session of various application options, and per-subscriber
bearer and signaling load characterization. This methodology has
been successfully incorporated into the Bell Labs Mobile Data
Analysis Model (MDAM), which forecasts bearer and signaling loads
resulting from mobile data applications. MDAM maintains an
applications database with a variety of traffic profile information
for data applications, and it uses the Alcatel-Lucent Wireless
Network Guardian as a critical source of current usage pattern
data.
3.4.3 Wireless Strategy Optimizer
Bell Labs has developed an advanced methodology and model,
called the Wireless Strategy Optimizer (WSO), to help service
providers plan their strategies for complex network evolution.
These complexities arise when many variables are involved,
including multiple technologies and spectrum bands, many types of
data-centric devices (such as voice, smartphones and datacards) and
multiple planning morphologies, as well as different usage patterns
and cell site densities.
These factors produce a complex system with thousands of
variables and constraints. But the WSOs holistic modeling can
analyze all key parameters simultaneously and compare all possible
strategy options and network evolution scenarios. It offers a
scientific approach to selecting the best TCO optimized strategy
for a service providers circumstances.
4. Conclusion
To address their geographically heterogeneous capacity needs
over time, mobile service providers must deploy several
technologies, including 2G, 3G and 4G, and several solutions,
including macro cells and small cells. This evolution, especially
the introduction of LTE and small cells, will improve the economics
of capacity growth, bringing down the cost per bit.
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In addition, operators need to rely on disruptive architectures
and designs that can provide all the necessary flexibility,
velocity and agility required for their capacity deployments. For
example, an operator that deploys a disruptive lightRadio
architecture will successively benefit from the TCO reductions
offered by small cells, as well as macro cells. The overall TCO
reductions for an existing high-capacity, fiber-fed site in an
urban area compared to traditional state-of-the-art converged RAN
solution are projected to be at least 20 percent over five years.
For a new site, they are at least 28 percent. This savings is over
and above any improvements in cost per bit that may be achieved by
migration to LTE, introduction of metro-cells and future
LTE-Advanced opportunities with the potential for significantly
improving spectral efficiency.
In conclusion, mobile service providers have clear challenges
ahead, as they adapt to the new wireless ecosystem created by
innovative devices, attractive applications and the resulting
explosion in usage. The latest wireless RAN innovations and
disruptions will allow service providers to benefit from this
increased demand, while deploying a lightRadio architecture that is
highly optimized and reinforced by powerful digital processing,
radio, transmission and antenna innovations.
5. Authors
[email protected]
GuruPatil [email protected]
JonathanSegel [email protected]
NicolasLanglois [email protected]
PatrickLagrange [email protected]
MarkBass [email protected]
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www.alcatel-lucent.com Alcatel, Lucent, Alcatel-Lucent and the
Alcatel-Lucent logo are trademarks of Alcatel-Lucent. All other
trademarks are the property of their respective owners. The
information presented is subject to change without notice.
Alcatel-Lucent assumes no responsibility for inaccuracies contained
herein. Copyright 2011 Alcatel-Lucent. All rights reserved.
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