smart networks for smart devices 15072010 final

7/28/2019 Smart Networks for Smart Devices 15072010 Final

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Nokia Siemens Networks

Smart Networks forSmart Devices

The Smartphone ChallengeStarting in 2007, the amount of mobile

data consumed globally exploded,

catching most industry watchers and

operators by surprise. As a result, the

mobile broadband industry has since

been focusing on meeting the needs of

laptop users, with the main challenge

being how to provide enough data

capacity profitably.

However, while all the attention of the

industry was on the management of

large volumes of data, a stealth issue

was lurking just below the surface:

smartphone network activity. The

arrival of feature-rich smartphones

ushered in a brand new world of data

usage, featuring rich applications that

were always connected to the network

and let end users stay in touch

with friends via instant messaging,

Facebook, and other universally

popular applications. Operators

were pleased when they saw that

smartphones were, on average,

generating only about one-sixth of

the data traffic that laptops were.

the latest Facebook update or instantmessage, that come from smartphones

with their always-on applications,

generate signalling traffic that is,

on average, eight times as much

traffic as laptops generate. While

operators were dimensioning their

networks to cope with large amounts

of laptop-generated data, no one was

dimensioning their networks to cope

with large amounts of signalling traffic.

And when the network elements that

handle signalling traffic overload, they

are no longer able to handle additional

data or voice calls thus leading to the

significant degradation of quality seen

in many smartphone-heavy operator

networks globally.

In addition, keeping the smartphone in

the active data transmission mode

requires battery power. The longer a

smartphone is kept in the active state,

the shorter the battery life thus

leading to user complaints about

unexpectedly poor smartphone battery

performance. This is the problem that

faces all operators today: To ensure

the quality of experience for all users

by managing smartphone signallingtraffic volume, while simultaneously

ensuring the longest possible handset

battery lifetime.

Then the trouble started. End usersin the US and Europe started

complaining that the quality of their

voice and data services was no

longer good. In some densely

populated cities, the troubles were

particularly obvious, and the end

user complaints particularly loud.

Analysis of the network traffic showed

that surprise! smartphones were

the problem. But how could that be?

If the average smartphone generates

one-sixth of the traffic of a laptop,

how can they degrade the quality

of an entire network? End users

were also bitter about how short

the battery life of smartphones

seemed to be.

The answer lies in the different ways

that laptops and smartphones are

used. Laptops consume large amounts

of mobile data in big chunks as users

browse web pages or download files.

Smartphones, on the other hand,

make many small connections to the

network, carrying small amounts of

data each time. Some push email

applications, for example, can be set

to look for new mails as often asevery 30 seconds, generating many

connections to the network, but not

much data. Each time any device

connects to the network, no matter

how much data is involved, there is

background signalling traffic that opens

and closes the data session. All those

little pings to the network, looking for


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2 Smart Networks for Smart Devices

The Nokia Siemens Networks

Solution

The Nokia Siemens Networks solution

to the Smartphone Challenge lies in

how it handles the different states of

the handset (see Figure 1).

As Figure 1 demonstrates, vendors

other than NSN keep the handset

when not in use in the Idle mode,

which uses very little battery. When

the handset connects to the network,

30 signaling messages are required

to take the handset up to the active

state to transmit the data and to return

it to Idle again. Sending all of these

signaling messages takes time, so the

end user has to wait an average of

two seconds for the initial connection.

Because waiting two seconds is not a

good user experience, other networkswait in the active mode for a while, just

in case the user requests more data,

so that the next response time will be

pleasingly short. However, being in

the active mode drains the handset

battery. Therefore, some handset

manufacturers have developed

handset software (fast dormancy)

that actively returns the handset to the

battery-saving Idle state very quickly

after data transmission to lengthen

battery lifetime. Moving up and down

from Idle to Active more often does

lengthen battery lifetime, but it also

generates more signals which the

network then must manage.

Nokia Siemens Networks handles

signaling differently. To begin with,

handsets not in use are kept not in the

Idle state, but another state called

Cell_PCH. In Cell_PCH, handsets use

no more battery power than they do in

the Idle state, but fewer signals are

needed to move the handset into the

Active state required for sending data:

12 signals for a large amount of data,

and three signals for a very small

amount. Because the number ofsignals is smaller, the latency is far

shorter than in other networks that are

sending 30 signals each time, and

averages 0.5 seconds. This is an

acceptable amount of time to wait for

a new bit of data, so Nokia Siemens

Networks networks are able to have

shorter timer settings, taking handsets

back down to the Cell_PCH quickly

thus providing the same reduced

battery consumption that other

networks achieve with fast dormancy.

Fewer signals and a shorter active-

state timer setting means that Nokia

Siemens Networks, alone among all

network suppliers today, offers

operators both less signaling and

reduced battery consumption

simultaneously.

In addition, Nokia Siemens Networks

management of the Radio Network

Controller (RNC), the network element

that handles the majority of the

signaling traffic, reduces the likelihood

of network overload and poor end-user

experience. Other vendors RNCs are

typically divided into sub-racks, each of

which handles a different geographic

area. If one sub-rack reaches capacity,

no more signaling traffic can be

processed in that area, leading to the

knock-on effect seen in several

networks around the world where too

many smartphones in a small area

have reduced the ability of non-

smartphone customers in the same

area to make even basic voice calls.

In contrast, Nokia Siemens Networks

has a pooled RNC, in which the whole

RNC element handles the signaling

from the entire responsibility area of

that RNC. The entire RNCs capacity

must be exceeded before there are

any performance issues, and operators

only need to properly dimension one

element to prevent problems, instead

of dimensioning many sub-racks

individually and risking network

performance issues if they get even

one wrong.

Fewer signals, longer battery lifetime,

and greater effective RNC capacity

means that operators with Nokia

Siemens Networks can offer their

smartphone customers indeed, all

customers the high-quality network

and handset performance that they

expect from their service provider.

Real Solutions, Real ResultsInspired by hearing Nokia Siemens

Networks claim that their network

supported a longer battery lifetime

for end users, a CSP in the MiddleEast tested the Nokia Siemens

Networks-provided network against

another suppliers network in their

region. They found that smartphones

Figure 1: The Beauty of Cell_PCH


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3Smart Networks for Smart Devices

Figure 2: Middle East CSP battery consumption testing of Nokia Siemens Networks performance

versus another suppliers network

Figure 3: Nokia Siemens Networks generates up to 50% less signalling traffic in a live

commercial network

on the Nokia Siemens Networks

network had an average battery

lifetime of 11 hours, while smartphones

on the network from a different supplier

had an average battery lifetime of

six hours. The CSP was so pleased

with their confirmation of the NokiaSiemens Networks statements that

they agreed to issue a joint press

release announcing their findings

(see test results in Figure 2).

Even more thorough external

verification has come from Canada. In

May 2010, Signals Research Group

released an independent paper called,

Smartphones and a 3G Network,

which examined the differences in

smartphone-generated signalling traffic

and handset battery life between a

commercial Nokia Siemens Networks

3G network in which the Cell_PCH

feature was enabled and a commercial

3G network from another supplier in

which Cell_PCH was not enabled

(a different supplier from that pictured

in Figure 2).

Key findings from the report include:

3G network congestion is due largely

to the high amount of smartphone-

generated signaling traffic which

overwhelms the resources of central

network elements, thus preventing

them from coping with further data oreven voice traffic.

Some of the most popular

smartphone applications are also

some of the greatest generators of

signaling traffic, including instant

messaging, web browsing, and

map use.

Frequent keep alive messages

can have a material impact on the

expected life of the battery. An

application that sends one keep

alive message every minute uses

the same battery power in only eight

hours as keeping the handsets

backlight on for a full hour. An operator that has implemented

Cell_PCH and selected appropriate

network inactivity timer settings is

able to significantly reduce the

The Signals Ahead report concludesthat the wireless industry, including

operators, infrastructure suppliers,

handset manufacturers, and

application developers, needs to

amount of signaling traffic in itsnetwork while increasing the

expected lifetime of the battery.

Overall, the Nokia Siemens

Network-provided network with

Cell_PCH enabled generated an

average of 40% fewer signals from

high-signalling applications than

the other suppliers network, with a

simultaneous battery life increase

of 30% (see Figures 3 and 4).


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work together to address the

signaling and battery lifetime

challenges posed by smartphones.

Nokia Siemens Networks agrees

wholeheartedly with this statement

and is proud to be leading the

industry in its discovery of newsmartphone-oriented modes of

operation, not only technically,

but also with developments such

as its Smart Labs, in which new

smartphone handset software

versions and applications can be

tested before release so that Nokia

Siemens Networks can get ahead of

the curve and advise operators on

how to prepare for new smartphone

challenges before they arise.

Figure 4: Smartphones using always-on style applications have up to a 30% longer battery life on

Nokia Siemens Networks

Copyright 2010 Nokia Siemens Networks. All rights reserved.

Nokia Siemens Networks, Karaportti 3, FIN-02610 ESPOO, FINLAND www.nokiasiemensnetworks.com

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