ericsson review: hspa evolution for future mobile-broadband needs

The communications technology journal since 1924 2013 • 9

HSPA evolution for future mobile-broadband needs August 28, 2013

HSPA evolution for future mobile-broadband needs As HSPA continues to evolve, addressing the needs of changing user behavior, new techniques develop and become standardized. These techniques provide network operators with the flexibility, capacity and coverage needed to carry voice and data into the future.

achieved by securing: capacity – to handle growing smart-phone traffic cost-efficiently;flexibility – to manage the wide range of traffic patterns efficiently; andcoverage – to ensure good voice and app user experience everywhere.

App coverageFor smartphone applications, like social networking and video stream-ing, to function correctly, access to the data network and a network that can deliver a defined minimum lev-el of performance is needed. The rela-tionship between the performance requirements (in terms of data speed and response time) of an application and the actual performance delivered by the network for that user at their location at a given time determines how well the user perceives the perfor-mance of the application.

The term app coverage denotes the level of network performance need-ed to provide subscribers with a sat-isfactory user experience for a given application. In the past, the task of dimensioning networks was simpler, as calculations were based on deliv-ering target levels of voice coverage and providing a minimum data rate. Today’s applications, however, have widely varying performance require-ments. As a result, dimensioning a network has become a more dynam-ic process and one that needs to take these varying performance require-ments into consideration, for apps that are currently popular with subscribers.

FootprintIllustrated in Figure 2, at the end of 2012, 55 percent of the world’s

replacing voice-centric feature phones. For less than USD 100, consumers can purchase highly capable WCDMA/HSPA-enabled smartphones with dual-core processors and dual-band oper-ation that support data rates up to 14.4Mbps. This price-to- sophistication ratio has turned the smartphone into an affordable mass-market product, and has accelerated the increase in smartphone subscriptions – estimated to rise from 1.2 billion at the end of 2012 to 4.5 billion by 20181.

Ericsson ConsumerLab studied a group of people to assess how they perceived network quality and what issues they encountered when using their smartphones. The study identi-fied two key factors that are essential to the perceived value of a smartphone: a fast and reliable connection to the data network, and good coverage2.

These findings highlight an impor-tant goal for operators: to provide all network users with high-speed data services and good-quality voice services everywhere. This can be

N I K L A S JOH A NSSON, L I N DA BRUS, E R I K L A R SSON, BI L LY HOGA N A N D PET E R VON W RYCZA

BOX A Terms and abbreviationsCELL_FACH Cell forward access channelCPC Continuous Packet ConnectivityDPCH Dedicated Physical ChannelEUL Enhanced UplinkHS-DSCH High-Speed Downlink Shared ChannelHSDPA High-speed Downlink Packet AccessHSPA High-speed Packet AccessHSUPA High-speed Uplink Packet AccessLPN low-power node

M2M machine-to-machineMBB mobile broadbandMIMO multiple-input multiple-outputROT rise-over-thermalSRB Signaling Radio BearerUL uplinkURA_PCH UTRAN registration area paging channelUTRAN Universal Terrestrial Radio Access NetworkWCDMA Wideband Code Division Multiple Access

Mobile broadband (MBB), providing high-speed internet access from more or less anywhere, is becoming a reality for an increasing proportion of the world’s population. There are several factors fuelling the need for high-performance MBB networks, not the least, the growing number of mobile internet connections. As Figure 1 illustrates, global mobile subscriptions (excluding M2M) are predicted to grow to 9.1 billion by the end of 2018. Nearly 80 percent of mobile subscriptions will be MBB ones1, indicating that MBB will be the primary service for most operators in the coming years.

Impact of affordable smartphonesTo a large extent, the rapid growth of MBB can be attributed to the wide-spread availability of low-cost MBB-capable smartphones, which are

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E R I C S S O N R E V I E W • AU GUST 28 , 2013

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population was covered by WCDMA/HSPA, a figure that is set to rise to 85 percent by the end of 20181. Today, many developed markets are nearing the 100 percent population coverage mark3. This widespread deployment, together with support for the broadest range of devices, makes WCDMA/HSPA the primary radio-access technology to handle the bulk of MBB and smart-phone traffic for years to come.

Since its initial release, the 3GPP WCDMA standard has, and continues to, evolve extensively. Today, WCDMA/HSPA is a best-in-class voice solution with exceptional voice accessibility and retainability. It offers high call reten-tion as well as being an excellent access technology for MBB, as it delivers high data rates and high cell-edge through-put – all of which enable good user experience across the entire network.

The continued evolution of WCDMA/HSPA in Releases 11 and 12 includes sev-eral key features that aim to increase network flexibility and capacity to meet growing smartphone traffic and secure voice and app coverage.

Evolution of traffic patternsApplications have varying demands and behaviors when it comes to when and how much data they transmit. Some apps transmit a large amount of data continuously for substantial periods of time and some transmit small packets at intervals that can range from a few seconds to minutes or even longer. Applications have vary-ing demands, typically sending lots of data in bursts, interspersed with peri-ods of inactivity when they send little or no data at all.

Rapid handling of individual user requests, enabled by high instanta-neous data rates, improves overall net-work performance as control-channel overhead is reduced and capacity for other traffic becomes available soon-er. So, if a network can fulfill requests speedily, all users will experience the benefits of reduced latency and faster round-trip times.

Web browsing on a smartphone is a classic example of a bursty application, both for uplink and downlink commu-nication. When a smartphone requests the components of a web page from the network (in the uplink) they are

transferred in bursts (in the downlink), and the device acknowledges receipt of the content (in the uplink). As a result, uplink and downlink performance becomes tightly connected and there-fore better uplink performance has a positive effect on downlink data rates as well as overall system throughput.

For web browsing, the instantaneous downlink speed for mobile users needs

to be much higher on average than the uplink speed. However, the number of services requiring higher data rates in the uplink, such as video calling and cloud synching of smartphone data, is on the rise.

As user behavior changes, traffic- volume patterns also change, and mea-surements show it is becoming more common for uplink levels to be on

FIGURE 1 Mobile and MBB subscriptions (2009-2018)1

Mobile subscriptionsMobile broadband

2009 2010 2011 2012 2013 2014 2015 2016 2017 20180

2,000

1,000

3,000

4,000

6,000

5,000

8,000

7,000

9,000

10,000

Subscriptions/lines (million)

FIGURE 2 Population coverage by technology (2012-2018)

100

80

60

40

20

2012 2018 2012 2018 2012 20180

% p

op

ulat

ion

cove

rag

e

(Source: Ericsson1)

>85%>90%

~55%

>85%

~10%

~60%

GSM/EDGE WCDMA/HSPA LTE

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par with downlink levels, and in some cases even outweigh the down-link traffic. Consequently, continuing to develop data rates to secure uplink-heavy services is key to improving over-all user performance.

High performance networksThe standard approach used to create a high-performance network with wide coverage and high capacity is to first improve the macro layer, then densify it by deploying additional macro base stations, and finally add low power nodes (LPNs) in strategic places, such as traffic hotspots, that can offload the macro network.

Each step addresses specific perfor-mance targets and applies to different population densities, from urban to rural – as illustrated in Figure 3. The evolution of WCDMA/HSPA includes a number of features that target macro layer improvement and how deploy-ments where LPNs have been added can be enhanced.

Improving the uplinkFeatures in the 3GPP specification have recently achieved substantial improve-ment of uplink capabilities. Features such as uplink multi-carrier, higher-order modulation with MIMO, EUL in CELL_FACH state, and Continuous Packet Connectivity (CPC) have multi-plied the peak rate (up to 34Mbps per carrier in Release 11) and increased the number of simultaneous users a net-work can support almost fivefold.

Given the high uplink capabilities already supported by the standard, the next development (Release 12) will enable and extend the use of these capabilities to as many network users as possible.

The maximum allowed uplink inter-ference level in a cell, also known as maximum rise-over-thermal (ROT), is a highly important quantifier in WCDMA networks. This is because the maximum allowed interference level has a direct impact on the peak data rates that the cell can deliver.

Typically, macro cells are dimen-sioned with an average ROT of around 7dB, which enables UL data rates of 5.7Mbps (supported by most commer-cial smartphones), and secures voice and data coverage for cell-edge users.

FIGURE 3 Where to improve, densify and add

ImproveDensifyAdd

ImproveDensify

Improve

Denseurban

Urban Suburban Rural

Area traffic density

FIGURE 4 Relationship between maximum interference and peak rate

UL ROT

Rate

Y

X

Y = Maximum interference handled by the network

X = Maximum uplink data rate that can be achieved

Legend

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High data rates, such as 11Mbps (avail-able since release 7) and 34Mbps (avail-able since release 11) require ROT levels greater than 10dB and 20dB respective-ly. Figure 4 illustrates the relationship between ROT and peak data rate.

The maximum uplink interference level permissible is determined by a number of factors including the den-sity of the network, the capability of the network to handle interference (for example with advanced techniques such as Interference Suppression), and the capabilities of the devices in the network, including both smartphones and legacy feature phones.

The Lean Carrier solution, intro-duced in Release 12, is an additional capability that helps operators meet the needs of high-data-rate users. This multi-carrier solution is built on the Release 9 HSUPA dual-carrier one that is currently being implemented in commercial smartphones. The dual-carrier solution allows two carriers, primary and secondary, to be assigned to a user. By doing this, the traffic gen-erated by the user can be allocated in a flexible way between the two carriers, while at the same time doubling the maximum peak rate achievable.

The Lean Carrier solution optimizes the secondary carrier for fast and flexi-ble handling of multiple high-data-rate users, through more efficient grant-ing and lower cost per bit. The solution is designed to support multiple bursty data users in a cell transmitting at the highest peak rates without causing any uplink interference among themselves or to legacy users. To maximize energy efficiency, the Lean Carrier solution should cost nothing in system or ter-minal resources on the secondary car-rier until the user starts to send data.

Lean Carrier can be flexibly deployed according to the needs of the network. For example, the maximum ROT on a user’s secondary (lean) carrier can be configured to support any available uplink peak data rate, while the maxi-mum ROT on a user’s primary carrier can be configured to secure cell-edge coverage for signaling, random access and legacy (voice) users.

Rate adaptation is another technolo-gy under study that results in increased network capacity for some common traffic scenarios, such as areas where

subscribers are a mix of high and low-rate users or areas where there are only high-rate users. High uplink data rates require more pow-er. Maintaining a fixed data rate at the desired quality target in an envi-ronment where interference lev-els vary greatly can result in large fluctuations in received power. To avoid such fluctuations, the concept of rate adaptation can be applied. High-rate users are assigned with a fixed received-power budget, and as interference levels change, bit rates are adapted to maintain the desired quality target, while not exceeding the allowed power budget. In short, as illustrated in Figure 5, the bit rate is adapted to received power, and not the power to the rate.

Limiting fluctuations in received power for high-rate users is good for overall system capacity because these high-rate users can transmit more efficiently, and other users in the system, including low-rate ones such as voice users, consume less power when power levels are stable and predictable.

Maintaining a device in connect-ed mode for as long as possible is another technique that can be used to improve performance of the uplink.

Smartphone users want to be able to rapidly access the network

from a state of inactivity. Maintaining a device in a connected-mode state, such as CELL_FACH or URA_PCH, for as long as possible is one way of achiev-ing this – access to the network from these states is much faster than from the IDLE state. In recent releases, con-nected mode has been made more effi-cient from a battery and resource point of view through the introduction of fea-tures such as CPC, fractional DPCH and SRB on HS-DSCH. As a consequence it is now feasible to maintain inactive devices in these states for longer.

As the number of smartphone users increases, networks need flexi-ble mechanisms to maintain high sys-tem throughput, even during periods of extremely heavy load. Allowing the network to control the number of con-currently active users, as well as the number of random accesses, is one such mechanism.

Improvements that enable high throughput under heavy load, and allow users to benefit from lower laten-cy in connected mode, while enabling service-differentiated admission deci-sions and control over the number of simultaneous users, have been pro-posed for Release 12.

Expanding voice and app coverageGood coverage is crucial for positive smartphone user experience and cus-tomer loyalty2, which for operators

FIGURE 5 Rate adaptation results in predictable interference levels

Baseline: Fixed ratevariable power

Received power

DATA

Control

DATA

Control

Time

Rate adaptation: Fixed received power and variable rate

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lower-rate speech codecs, where-as, four-way receiver diversity and advanced antennas can improve cov-erage for both voice and data.

Uplink transmit diversity was intro-duced in Release 11. This feature sup-ports terminals with two antennas to increase the reliability and coverage of uplink transmissions and decrease overall interference in the system. It works by allowing the device to use both antennas for transmission in an efficient way using beamforming. Figure  6 illustrates how the radio transmission becomes focused in a given direction, resulting in a reduc-tion in interference between the device and other nodes, and improving over-all system performance.

An additional mode within uplink transmit diversity is antenna selection. Here, the antenna with the best radio propagation conditions is chosen for transmission. This is useful, for exam-ple, when one antenna is obstructed by the user’s hand. Uplink transmit diversity increases the coverage of all uplink traffic for voice calls and data transmissions.

With Release 11, multi-flow HSDPA transmissions are supported. This allows two separate nodes to transmit to the same terminal, improving per-formance for users at the cell edge and resulting in better app coverage.

In Release 12, simultaneous app data and voice call transmissions will become more efficient, and the time it takes to switch transmission time interval from 10ms to 2ms is consid-erably shorter. These improvements increase both voice and app coverage.

Enhancing small-cell deploymentsThe addition of small cells through deploying LPNs in a macro network – resulting in a heterogeneous network – is a strategic way to improve capacity, data rates and coverage in urban areas. Typically, the deployment of LPNs is beneficial in hotspots where data usage is heavy, to bridge coverage holes cre-ated by complex radio environments, and in some specific deployments such as in-building solutions.

Figure 7 shows the performance gains in a heterogeneous-network deployment (described in Box B). Offloading to small cells not only

FIGURE 7 System-level gains – for scenario described in Box B

1W5W

0

50

Average Cell edge

100

150

200

250

300

User throughput gain (percent)

 BOX B   The systemThe scenario shown in Figure 7 is for bursty traffic. Four LPNs have been added to each macro base station in the network, and 50 percent of the users are located in traffic hotspots. The transmission power for the macro base station was 20W, and 1W and 5W LPNs were deployed.

LPNs were deployed randomly and no LPN range expansion was used. Gains are given relative to a macro-only deployment. Offloading was 32 percent for 1W LPNs and 41 percent for 5W LPNs, where offloading is a measure of the percentage of traffic served by the LPN.

FIGURE 6 Release 11 uplink transmit diversity beamforming

translates into securing voice coverage and delivering data-service coverage that meets the needs of current and future apps.

There are several ways to improve coverage for voice and data. One way

is to use lower frequency bands, and refarming the 900MHz spectrum from GSM, for example, provides a consid-erable coverage improvement when compared to 2GHz bands. Voice cover-age can be significantly extended with

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1. Ericsson Mobility Report, June 2013, available at: http://www.ericsson.com/res/docs/2013/ericsson-mobility-report-june-2013.pdf

2. Ericsson ConsumerLab report, January 2013, Smartphone usage experience – the importance of network quality and its impact on user satisfaction, available at: http://www.ericsson.com/news/130115-ericsson-consumerlab-report-network-quality-is-central-to-positive-smartphone-user-experiences-and-customer-loyalty_244129229_c

3. International Communications Market Report 2011, Ofcom, available at: http://stakeholders.ofcom.org.uk/binaries/research/cmr/cmr11/icmr/ICMR2011.pdf

References

FIGURE 8 LPN deployment scenarios

LPN LPN

LPN

Macro

LPNs deployed as separate cells on the same carrier

RNC

LPN LPN

LPN

Macro

LPNs deployed as part of a combined cell on the same carrier

RNC

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provides increased capacity for han-dling smartphone traffic, it also results in enhanced app coverage.

To maximize spectrum usage, the traditional macro base stations and LPNs share the same frequency, either with separate or shared cell identi-ties. These deployments, illustrated in Figure 8, are referred to as separate cell and combined cell.

It is possible to operate both sepa-rate and combined-cell deployments based on functionality already imple-mented in the 3GPP standard, and such deployments have been shown to pro-vide substantial performance benefits over macro-only deployments.

Today, combined cells tend to be deployed in specific scenarios, such as railroad, highway and in-building envi-ronments. Separate-cell deployments, on the other hand, are more generic and provide a capacity increase in more common scenarios.

In 3GPP Release 12, small-cell range expansion techniques and control channel improvements are being introduced to enable further offload-ing of the macro network. Mobility performance enhancements for users moving at high speeds through small cell deployments are also being inves-tigated by 3GPP.

When a macro cell in a combined-cell deployment is complemented with additional LPNs close to users, the data rate and network capacity is improved. By allowing the network to reuse the same spreading codes in different parts of the combined cell, the cell’s capacity can be further increased – a technique being studied in Release 12. And as there is no fundamental uplink/ downlink imbalance in a combined cell, mobility signaling is robust, sig-naling load is reduced, and network management is simplified.

In summary, heterogeneous net-works are essential for handling grow-ing smartphone traffic because they support flexible deployment strategies, increase the capacity of a given HSPA network, and extend voice and app cov-erage. The improvements standard-ized in Release 12 will further enhance these properties.

ConclusionsWCDMA/HSPA will be the main

technology providing MBB for many years to come. Operators want WCDMA/HSPA networks that can guarantee excellent user experience throughout the whole network cover-age area for all types of current and future mobile devices. The prerequi-sites for networks are:

capacity – to handle growing smart-phone traffic cost-efficiently;flexibility – to manage the wide range of traffic patterns efficiently; andcoverage – to ensure good voice and app user experience everywhere.

HSPA evolution, through the capabili-ties already available in 3GPP and those under study in 3GPP Release 12, aims

to fulfill these prerequisites. There are several ways to improve voice and app coverage. Enhancements to the uplink improve the ability to quick-ly and efficiently serve bursty traf-fic – improving user experience and increasing smartphone capacity. Small-cell improvements will increase network capacity for smartphone traf-fic and further improve voice and app coverage.

With all of these enhancements, WCDMA/HSPA, already the dominant MBB and best-in-class voice technolo-gy, has a strong evolution path to meet the future demands presented by the growth of MBB and highly capable smartphones globally.

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© Ericsson AB 2013

Niklas Johansson

is a senior researcher at Ericsson Research. He joined Ericsson after receiving his M.Sc. in

engineering physics and B.Sc. in business studies from Uppsala University in 2008. Since joining Ericsson, he has been involved in developing advanced receiver algorithms and multi-antenna transmission concepts. Currently, he is project manager for the Ericsson Research project that is developing concepts and features for 3GPP Release 12.

Peter von Wrycza

is a senior researcher at Ericsson Research, where he works with the development and

standardization of HSPA. He received an M.Sc. (summa cum laude) in electrical engineering from the Royal Institute of Technology (KTH), Stockholm, Sweden, in 2005, and was an electrical engineering graduate student at Stanford University, Stanford, CA, in 2003-2005. In 2010, he received a Ph.D. in telecommunications from KTH.

Erik Larsson

joined Ericsson in 2005. Since then has held various positions at Ericsson Research,

working with baseband algorithm design and concept development for HSPA. Today, he is a system engineer in the Technical Management group in the Product Development Unit WCDMA and Multi-Standard RAN and works with concept development and standardization of HSPA. He holds an M.Sc. in engineering physics (1999) and a Ph.D. in signal processing (2004), both from Uppsala University, Sweden.

Billy Hogan

joined Ericsson in 1995 and works in the Technical Management group in the Product Development

Unit WCDMA and Multi-Standard RAN. He is a senior specialist in the area of enhanced uplink for HSPA. He works with the system design and performance of EUL features and algorithms in the RAN product, and with the strategic evolution of EUL to meet future needs. He is currently team leader of the EUL Enhancements team for 3GPP release 12. He holds a B.E. in electronic engineering from the National University of Ireland, Galway, and an M.Eng in electronic engineering from Dublin City University, Ireland.

Linda Brus

joined Ericsson in 2008. Since then, she has been working with system simulations, performance

evaluations, and developing algorithms for WCDMA RAN. Today, she is a system engineer in the Technical Management group in the Product Development Unit WCDMA and Multi-Standard RAN, working with concept development for the RAN product and HSPA evolution. She holds a Ph.D. in electrical engineering, specializing in automatic control (2008) from Uppsala University, Sweden.

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