mobile broadband review 2014h1

8/11/2019 Mobile Broadband Review 2014H1

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Mobile Broadband

Review 2014H1


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Mobile Broadband Review 2014H1 Contents

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Contents

1 Introduction.................................................................................................................................... 1

2 Network Insights........................................................................................................................... 2

2.1 PS Traffic Models in Different Networks .......................................................................... ........................................... 2

2.1.1 PS Signaling Increasing Dramatically in 4G Networks ............................................................................................. 2

2.1.2 Network Architecture Changes Contributing to Signaling Increases ............................................................... .......... 3

2.2 RAN Traffic Models in Different RATs .......................................................... .............................................................. 4

2.2.1 Status for UMTS and LTE Network Rates ..................................................................... ........................................... 4

2.2.2 Reasonable Number of Subscribers Helping Increase LTE Spectrum Efficiency...................................................... 5

2.3 Traffic Distribution of Typical LTE Networks ........................................................... ................................................... 6

2.3.1 Significant Difference in Traffic Distribution of LTE Networks ................................................................... ............ 6

2.3.2 10% Video Consumption in an LTE Network Higher Than That of UMTS .............................................................. 8

3 Experience Insights ....................................................................................................................... 9

3.1 Status for Live Network Experience ............................................................... .............................................................. 9

3.1.1 Network Experience Improvements Lower Than Air Interface Capability Enhancement ......................................... 9

3.2 Influencing Factors ..................................................................................................................................................... 10

3.2.1 Air Interface Bandwidth and Network Architecture Determining User Experience ................................................ 10

3.3 Progress in the Acceptance Test Criteria of Experience Coverage ................................................................... .......... 11

3.3.1 Operative and Available Quota Commitment ................................... ............................................................. .......... 11

3.3.2 Practice .................................................................................................................................................................... 11

4 User Behavior Insights ............................................................................................................... 13

4.1 Time Distribution of Video Playing ......................................................................................................... ................... 13

4.1.1 More Smooth Time Distribution of Video Playing in 4G Network Than in 3G and Wi-Fi ..................................... 13

4.2 User Behaviors in Video Playing and Microblog ....................................................................................................... 14

4.2.1 More Video Consumptions in 4G than in 3G .......................................................... ................................................. 14

4.2.2 VIP's Influence Higher than Other Users in Microblog ........................................................................................... 14

4.3 Microblog Users' Behavior Trend ........................................................ ............................................................... ........ 15

4.3.1 Number of Chinese Characters ............................................................................... ................................................. 15

4.3.2 Proportion of Microblogs Containing Images ......................................................................................................... 16

4.3.3 Individual Users Forwarding More Than VIP Users ............................................................................................... 17

5 Appendix ...................................................................................................................................... 18

5.1 Overview .................................................................................................................................................................... 18


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Mobile Broadband Review 2014H1 Contents

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5.2 Data Sources ............................................................................................................................................................... 18

5.3 Contact Information ........................................................ .............................................................. .............................. 18


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Mobile Broadband Review 2014H1 Figures

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Figures

Figure 2-1Comparison of UMTS and LTE network architecture ............................................................... .......... 3

Figure 2-2Comparison of UMTS and LTE network rates (2013Q2) .......................................................... .......... 4

Figure 2-3Relationship between LTE DL spectrum efficiency and the number of online subscribers ................. 5

Figure 2-4Traffic distribution in typical LTE networks (2014Q1) ............................................................. .......... 6

Figure 2-5UMTS and LTE traffic distribution comparison in the same carrier's network (2014Q1) ................... 8

Figure 3-1Experience testing result for the global commercial networks (2014Q1- Q2) ..................................... 9

Figure 3-2Influencing factors for user experience and their relationships ........................... .............................. 10

Figure 3-3Acceptance principles for carrier O's xMbps network (2014Q1 - Q2) .............................................. 11

Figure 3-4Overview of xMbps Anytime Anywhere ............................................................. .............................. 12

Figure 4-1Time distribution of video playing on Sohu Video APP (2014Q2) .................................................... 13

Figure 4-2Percentage of playback with different quality videos on various networks (2014Q2) .............. ........ 14

Figure 4-3Comparison of influence of different users (2014Q2) .................................................... ................... 14

Figure 4-4Number of Chinese characters per post for each type of users (2014Q2) .......................................... 15

Figure 4-5Proportion of Microblogs containing images for each type of users (2014Q2) ................................. 16

Figure 4-6Proportion of Microblogs forwarded by each type of users (2014Q2) .............................................. 17


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Mobile Broadband Review 2014H1 Tables

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Tables

Table 2-1PS traffic models in typical networks globally (2014Q1) ............................................................ .......... 2

Table 2-2LTE traffic models comparison in typical scenarios ......................................................... ..................... 5

Table 2-3Traffic distribution of videos in different resolutions in typical LTE networks ..................................... 7

Table 2-4Monthly traffic tariff comparison in typical LTE networks ......................................................... .......... 7

Table 3-1Acceptance solutions of carrier O's xMbps network......................................................... ................... 11


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Mobile Broadband Review 2014H1 1 Introduction

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1 IntroductionThis report consists of three parts: Network Insights, Experience Insights, and User BehaviorInsights. The Network Insights describes the traffic models and traffic distribution of 4G and

3G networks, the differences between 4G and 3G networks, and the causes for the differences.

The Experience Insights explores the main factors that affect users' experience and theprogress of xMbps network deployment. The User Behavior Insights analyzes the videoconsumption in different networks as well as the microblog users' behavior, characteristics,and development trend.

The major findings are as follows:

The traffic model in the PS (Packet Switched) network from 2G/3G evolving to 4G: The

increased signaling load brought by paging and handover, the flattened network architectureand changed talking modes are the root causes.

A reasonable number of online subscribers is helpful to enhancing the spectrum efficiency of

LTE networks.

The share of video services on the LTE network is about 10% higher than that of the UMTS

network as far as a certain mobile carrier is concerned. Even among the relatively developed

LTE networks, the share of HD videos varies a lot. The data traffic package quota and tariff,as well as carriers' business orientation have significant impact on the consumption of HD

videos.

New progress was made in the acceptance test criteria of Experience Coverage (for example

xMbps anytime anywhere): the number of xMbps requests, the fill rate of xMbps andtransmitted carrier power (TCP) utility should be combined to decide the criteria for

optimization/expansion, and accept by comparison of the performance counters before or after

the optimization/expansion.

Testing results of the live networks show that the improvement in the quality of user

experience is disproportionate to that in the air interface data rate, and only a coordinatedoptimization of the air interface and network architecture can offer the best user experience.

The statistics of Sohu Video show that the video consumption per user is more active in the

4G network than in 2G/3G network. The percentage of the 4G users choosing HD or higher

definition format videos is much higher than that of 2G/3G users (more than 20%).


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Mobile Broadband Review 2014H1 2 Network Insights

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2 Network Insights2.1 PS Traffic Models in Different Networks

2.1.1 PS Signaling Increasing Dramatically in 4G Networks

Table 2-1PS traffic models in typical networks globally (2014Q1)

PS Traffic Model

2014Q1

2G 3G 4G

Intra SGSN/MME RAU/TAU per attached subscriber @

Busy Hour

6.38 2.42 1.79

Inter SGSN/MME RAU/TAU per attached subscriber @Busy Hour

0.71 1.06 0.12

Paging times per attached subscriber @ Busy Hour (PS)

(124 eNodeBs for each TA list)1.84 2.44 11.64

Service Request times per attached subscriber @ Busy

HourNA 11.35 30.67

Intra MME /SGSN HO times per attached subscriber @Busy Hour

0.02 0.10 8.02

Inter MME /SGSN HO times per attached subscriber @

Busy Hour

0.00 0.01 0.22

Average packet size @ Busy Hour (Bytes) 374.00 556.00 735.00

Average traffic per active bearer @ Busy Hour (Kbps) 0.81 25.00 110.00

Average online time per active bearer @ Busy Hour

(min)NA 78.97 121.84

Data source: PS LMT, Huawei

As can be seen fromTable 2-1,Paging is a signaling killer. Paging times (paging times for

Broadcast Services excluded) for each attached 4G user is 11.6, 4.8 times larger than that of


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3G (if 124 eNodeBs are deployed in a tracking area (TA) list, the paging request load forMME brought by each user is 595 times bigger than that of SGSN in 3G networks). In

addition, handover times for each attached 4G user are larger than that of 3G. The changes in

network architecture (the entity that performs paging and handovers move from RNC in 3Gnetwork to MME in the 4G network) and in voice calling modes account for these.

The number of 4G service requests is 2.7 larger than that of 3G. The paging channel (PCH)

deployment in 3G networks reduces the number of signaling messages, while the DynamicDiscontinuous Reception (DRX) is not deployed in the 4G network so far.

The average packet size in 4G is 1.3 times that of 3G; the traffic volume per user during busy

hours is 4.4 times that of 3G.

The dynamic DRX feature is to reduce the signaling overhead and save UE power consumption when

UEs perform instant messaging and presence class services. It dynamically configures the UE InactiveTimer and Uplink Synchronization Timer and uses the DRX algorithm in the out-of-synchronizationstate to enable the UE online and save the UE power consumption.

2.1.2 Network Architecture Changes Contributing to SignalingIncreases

Figure 2-1Comparison of UMTS and LTE network architecture

Data source: PS LMT, Huawei

The impact of LTE network architecture being flat lies in two sides: on the one hand, the

end-to-end round trip time (E2E RTT) is reduced significantly (> 20 ms); on the other hand,MME interacts with eNodeB directly, so that one MME will process the signaling messages

from multiple eNodeBs (for example, a paging occurs in different TAs, which involvehundreds of eNodeBs).

At the same time, in the LTE network, all the handovers between eNodeBs should beprocessed by MME, dramatically increasing the signaling messages; while in the UMTS

network, most of the handovers are processed in the same RNC, and only the signalingmessages in the scenario where the UEs migrate between different RNCs are processed bySGSN.

Finally, with the expansion of the scale of LTE deployment, macro sites and micro sites will

coordinate more, sites will become denser; a TA list may include more sites, thus behaviors,

such as paging, handover, etc will create greater requirements on signaling capacity of MME.


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2.2 RAN Traffic Models in Different RATs

2.2.1 Status for UMTS and LTE Network Rates

Figure 2-2Comparison of UMTS and LTE network rates (2013Q2)

Data source: Huawei Wireless Network

The samples from the Korean carrier B are few, and they performed not too ideally in average. Therefore,the average network rate of carrier B is low.

The data of LTE networks for West Europe and North America is absent.

As to 3G downlink rate, Norway is 5 times of the global average rate, performing far better

than China, Southeast Asia, and the Middle East. As to 3G uplink rate, most countries

fluctuate around the global average rate, among which Thailand tops by 2.65 Mbit/s.

As to 4G downlink rate, carrier A of United Arab Emirates performs better than any other

carrier. As to 4G uplink rate, carrier A of Malaysia performs better than any other carrier.

Carrier B has advantages over carriers A and C in respect of 3G network in China. However,it performs worse than the latter two in respect of LTE network.


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2.2.2 Reasonable Number of Subscribers Helping Increase LTESpectrum Efficiency

Figure 2-3Relationship between LTE DL spectrum efficiency and the number of onlinesubscribers

Source: Huawei Wireless Network

As shown inFigure 2-3,a reasonable number of online subscribers helps increase LTE

spectrum efficiency. On one hand, if the number of online subscribers is small, the number ofsubscribers fluctuates more intensely and there is a large probability that the service

requirements are small, causing low spectrum efficiency. On the other hand, if the number ofonline subscribers is big, the peak-to-average (PAR) ratio of online subscribers is smaller. In

this case, many resources will be consumed by signaling, and few of them are used for datatransmission; therefore, the DL spectrum efficiency is low.

Table 2-2LTE traffic models comparison in typical scenarios

Scenario

UE inactiveTimer (s)

DL average userexperience rate(Mbit/s)

UL average userexperience rate(Mbit/s)

Peak-to-Average Ratio ofonline users

DL/ULtrafficratio

Scenario 1 20 8.26 0.69 2.58 10.04

Scenario 2 10 8.09 1.27 1.74 9.15

Scenario 3 5 10.73 1.54 3.57 8.74

Scenario 4 10 11.88 1.64 2.38 7.44

Scenario 5 20 13.33 2.30 1.95 7.5

Scenario 6 15 9.25 1.25 1.56 7.74


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Scenario UE inactiveTimer (s)

DL average userexperience rate(Mbit/s)

UL average userexperience rate(Mbit/s)

Peak-to-Average Ratio ofonline users

DL/ULtrafficratio

Scenario 7 20 9.53 1.33 2.44 9.36

Source: Huawei Wireless Network

DL user experience rate = data volume that is successfully transmitted in a statistical period / time for

data transmission

As shown inTable 2-2 shows, the DL average user experience rate during busy hours in

advanced LTE networks is stable (standard deviation/mean value = 19%). However, the ULaverage experience rate fluctuates a lot (standard deviation/mean value = 34%). The

fluctuation of PAR of online subscribers (1.53.6) and the UL/DL traffic ratio (710) in

different LTE networks is significant.

2.3 Traffic Distribution of Typical LTE Networks

2.3.1 Significant Difference in Traffic Distribution of LTENetworks

Figure 2-4Traffic distribution in typical LTE networks (2014Q1)


Generally, SNS consumes 8% of total daily traffic that users spend on smart phones, though

this figure may vary in different carriers and regions.


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Table 2-3Traffic distribution of videos in different resolutions in typical LTE networks

Carrier240P VideoShare

360P VideoShare

480P VideoShare

720P VideoShare

1080P VideoShare

A 37% 39% 18% 6% 0%

B 5% 26% 25% 32% 12%

C 21% 44% 16% 19% 0%

D 12% 35% 26% 27% 0%

Table 2-4Monthly traffic tariff comparison in typical LTE networks

Carrier

Average

MonthlyTrafficConsumptionPer User(Gigabytes)

AverageMonthlyExpenditure(Dollars)

AverageAnnualIncome in2012 (Dollars)

Percentage ofExpenditurein MonthlyIncome

Description

A 2 41.958 38,250 1.32%

Value added service: a

free movie ticket every

Wednesday

B 3 58.206 22,670 3.08%

Top 1 U+HDTV app with

2 million users; 1.6million U + Navi daily

users; contractedpackages for traffic tariff

C 2 47.472 36,560 1.56%

Value-added service: the

music app Newsic Dailyfor free, and Now TV

England Premier LeagueChannel for free

Data Source: The data for users' expenditure was retrieved on 11thAugust, 2014 from the

corresponding carrier's website. The users' monthly traffic consumption was a mean value

from the industry consulting report, and the monthly expenditure (with local currency unit)was from the most suitable data traffic package quota and tariff. The numbers in the preceding

table were calculated based on the daily currency by the currency calculator provided byHexun.com. The data for average annual income comes from the statistics published by WorldBank in 2012.

In advanced LTE networks, the percentage of HD and higher resolution videos varies a lot.

The data traffic package quota and tariff, as well as carriers' business orientation have

significant impact on the consumption of HD videos.


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2.3.2 10% Video Consumption in an LTE Network Higher ThanThat of UMTS

Figure 2-5UMTS and LTE traffic distribution comparison in the same carrier's network (2014Q1)


In the relatively advanced LTE networks, the video consumption is about 10% higher thanthat of UMTS, indicating that the higher network rate can stimulate the video consumption.


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Mobile Broadband Review 2014H1 3 Experience Insights

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3 Experience Insights3.1 Status for Live Network Experience

3.1.1 Network Experience Improvements Lower Than AirInterface Capability Enhancement

Figure 3-1Experience testing result for the global commercial networks (2014Q1- Q2)

Data source: Huawei mLAB

From 3G to LTE, the improvements in Page-loading Speed and user experience (i.e.

Page-loading Duration) is disproportionate to those of the air interface rate (i.e. DL Speed in

Speedtest). Therefore, to improve the web experience is still a long way off.

As the LTE air interface rate improves and the video content delivery networks are optimized,the video Initial Buffering Downloading Speed is accelerated dramatically and the videoexperience is improved a lot. However, due to the downloading speed limits from video

websites when playing the video and the less popularity of higher definition videos, theAverage Downloading Speed is only improved a little.


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3.2 Influencing Factors

The findings of mLAB's analysis on OTT transmission mechanism are as follows:

User experience = Size of the content / Actual speed

Actual speed = MIN (Air interface rate, TCP throughput)

3.2.1 Air Interface Bandwidth and Network ArchitectureDetermining User Experience

Figure 3-2Influencing factors for user experience and their relationships


User experience depends not only on the data rate over the air interface (i.e. Experience

Coverage: xMbps Anytime Anywhere), but also on RTT determined by network architecture.If the air interface resources are not limited, user experience is mainly affected by the RTT.Therefore, attention should be paid to network architecture optimization to decrease RTT,which includes the optimization of RTT in the wireless network as well as that caused by the

OTT services network architecture (like CDN deployment). If the bandwidth is not a

bottle-neck, the shorter the RTT, the faster the speed, and the greater the demand for the airinterface bandwidth.

A coordinated optimization of air interface and RTT will improve user experience at thelowest costs.


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3.3 Progress in the Acceptance Test Criteria of ExperienceCoverage

3.3.1 Operative and Available Quota Commitment

Figure 3-3Acceptance principles for carrier O's xMbps network (2014Q1 - Q2)

Data source: Huawei Radio Inventory Solutions

New progress was made in the acceptance test criteria of Experience Coverage (Brand:

xMbps anytime anywhere): the number of xMbps requests, the fill rate of xMbps and TCPutility should be combined to decide the criteria for optimization/expansion, and accept bycomparison of the performance counters before or after the optimization/expansion.

3.3.2 Practice

Table 3-1Acceptance solutions of carrier O's xMbps network

Scenario

Definition

Solution Proposal

Scenario 1 xMbps requirements > 300, xMbps

fill rate < 30%, TCP >60%

Capacity Expansion based on

experience (Sector splitting/Small cell)

Scenario 2 xMbps fill rate < 30%, TCP 100

Network Optimization (RANFeature/ACP - Auto Cell PlanningSolution)

Scenario 3 HSDPA user > 20, TCP > 70% Capacity Expansion based ontraditional resource(s) utility

Scenario 4 xMbps fill rate < 30%, TCP >50%, xMbps requirement < 100

Optimization or analyses of the(x/2)Mbps fill rate

Other excluding the above scenarios None


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Data source: Huawei Radio Inventory Solutions

Figure 3-3 corresponds with scenario 1 listed inTable 3-1.

Figure 3-4 shows vividly the idea for Experience Coverage (Brand: xMbps anytimeanywhere).

Figure 3-4Overview of xMbps Anytime Anywhere


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Mobile Broadband Review 2014H1 4 User Behavior Insights

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4 User Behavior Insights4.1 Time Distribution of Video Playing

4.1.1 More Smooth Time Distribution of Video Playing in 4GNetwork Than in 3G and Wi-Fi

Figure 4-1Time distribution of video playing on Sohu Video APP (2014Q2)

Data source: Sohu Video APP

The peak hours for video playing range from 12:00 to 13:00 and from 20:00 to 24:00.Compared with the 2G / 3G / Wi-Fi curves in the chart, the time distribution curve of video

playing in the 4G network is much smoother.


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4.2 User Behaviors in Video Playing and Microblog

4.2.1 More Video Consumptions in 4G than in 3G

Figure 4-2Percentage of playback with different quality videos on various networks (2014Q2)

Data source: Sohu Video APP

The percentage of the 4G users choosing HD or higher definition format videos is muchhigher than that of 2G/3G users (more than 20%).

4.2.2 VIP's Influence Higher than Other Users in Microblog

Figure 4-3Comparison of influence of different users (2014Q2)


Among the four types of microblog users, individual VIP users take the lowest proportion.However, they publish more microblogs, have more fans, and are followed more than other

types of users, and therefore have greater influence.

695

4038

31808

7521

0

5000

10000

15000

20000

25000

30000

35000

0

500

1000

1500

2000

2500

3000

3500

4000

Individual Users Expert Users Individual VIP

Users

Institutional VIP

Average Number Of Microblogs posted

Average Number Of Followed Users

Average Number Of Fans


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4.3 Microblog Users' Behavior Trend

4.3.1 Number of Chinese Characters

Figure 4-4Number of Chinese characters per post for each type of users (2014Q2)


The average number of Chinese characters per microblog is increasing. The average numberof Chinese characters per microblog from individual VIP users is greater than that from

individual users.

The average number of Chinese characters per microblog now is 71 based on the user

proportions and through weight calculation.


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4.3.2 Proportion of Microblogs Containing Images

Figure 4-5Proportion of Microblogs containing images for each type of users (2014Q2)


The proportion of microblogs containing images has been slightly increasing, showing aroughly stable trend on the whole. Individual VIP users publish more microblogs containing

images than other types of individual users.

The proportion of microblogs containing images now is 72.45% based on the user proportions

and through weight calculation.


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4.3.3 Individual Users Forwarding More Than VIP Users

Figure 4-6Proportion of Microblogs forwarded by each type of users (2014Q2)


The proportion of common users who forward other users' microblogs is slightly higher thanthat of individual VIP users who forward other users' microblogs. Nearly half of the currentmicroblogs are forwarded ones on the whole.

The proportion of forwarded microblogs now is 56.78% based on the user proportions andthrough weight calculation.

The data for analyzing the Microblog usersbehavior was retrieved by MBB Robot, with 15,000

samples so far.

Rules for defining the types of users:

Individual users: most of them are common people, including the users who are not authenticated asVIP and have attracted a large number of fans, accounting for 91.43% of the total users.

Active users: the users who are very active among the individual users. They have tags for being

active and a larger number of microblogs and fans than the common users, accounting for 7.18% of

the total users.

Individual VIP: identified Microblog users who are often famous in their fields and have a lot fans,

accounting for 0.71% of the total users.

Institutional VIP: the users include government department, companies, and websites, accounting for

0.68% of the total users.


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Mobile Broadband Review 2014H1 5 Appendix

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5 Appendix5.1 Overview

This report was written by Huawei Wireless Traffic Model Analysis Team. Based on the data

from global typical commercial mobile networks, the results of live mobile networks' speedtests, web browsing experience tests, and streaming service experience tests, the statistics ofOTT services characterics, and the statistics of Sohu Video APP. This report tries to

objectively reflect the status and trend for mobile broadband, terminals, services, and userexperience/behavior. However, this report does not present the accuracy and integrity of the

information.

In respect of privacy, all the names of carriers are anonymous in this report. Limited by thenumber of samples and the rapid development of mobile broadband, Huawei retains the rights

to modify the later versions of this report and will not be responsible for the results caused bythese modifications.

5.2 Data Sources

The original data from the global commercial mobile networks that cooperate with Huawei;

The test results from the tests by MBB Explorer APP in the typical commercial networks;

The statistical results by using MBB Robot to collect the data of OTT services characterics;

Statistical results by analyzing the users and the video playing in the Sohu Video APP.

5.3 Contact Information

Author: Peng Zhenyu/00068822

Email: [email protected]

mLAB: [email protected]


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Mobile Broadband Review 2014H1 Terms and Definitions

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Terms and Definitions

Terms Definitions

3G The Third Generation of mobile telecommunications technology, whichsupports high speed data transmission. There are three standards branded with

3G: CDMA2000, WCDMA, and TD-SCDMA.

4G The Fourth Generation of mobile telecommunications system. There are two

standards for LTE networks: LTE TDD and LTE FDD.

eNodeB Evolved Node B is a type of base station specifically for LTE networks.

Compared with the NodeB in 3G network, eNodeB integrates the functions of

RNC, allowing lower response times.

LTE The Long Term Evolution is the fourth generation of mobiletelecommunications standard, released by 3GPP. It uses OFDM and MIMO to

greatly increase the data transmission capacity and speed of radio accessnetwork.

MME The mobility management entity is an EPC entity that performs the logicfunctions related with signaling.

RAU A routing area (RA) is applied in the packet switched (PS) network of UMTS.

The routing area update is an important part of the mobility management in

the GPRS network, to help identify the locations of UE and enable UE paging.

RTT The round trip time is the elapsed time for the data to be sent and received

between the transmitter and the receiver.

SGSN The serving GPRS support node is a functional entity in the PS network of the

GPRS/WCDMA, providing functions such as packet data routing and

forwarding, mobility and session management, logical link management,

authentication and encryption, and charging data record (CDR) generation andoutput.

Spectrum

Efficiency

The spectrum efficiency is a measure of the performance of encoding methods

that code information as variations in an analog signal. Spectrum efficiency =

Traffic rate/Bandwidth. The unit for spectrum efficiency is bits/Hz.

TAU Tracking area (TA) is applied in the EPS. The UEs both in idle and connected

modes are registered in a TA and managed by EPC. If the TA of the UEs ischanged, the registration information will be changed accordingly. A tracking

area update (TAU) informs EPC whether the UEs are available. If thehandover is performed or the tracking area identity (TAI) is not included in the

TA list, TAU must be performed.


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Mobile Broadband Review 2014H1 Terms and Definitions

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Terms Definitions

TCP The transmitted carrier power is used to monitor DL transmission. It is limited

by the maximum transmit power of the base station's power amplifier.

UMTS The Universal Mobile Telecommunications System is the third generation

mobile telecommunications standard released by 3GPP.


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Mobile Broadband Review 2014H1 Reference Documents

Reference Documents

1. Liu Pingping, Research on the Technologies to Reduce the Peak-to-Average Ratio inOFDM, Northwest, 2010.6

2.

"eRAN8.0 Feature Documentation DRX and Signaling Control Feature ParameterDescription", Huawei Technologies, Co., Ltd., 2014.5

3.

Differences between 3G and 4G Network Architecture, accessed from

http://network.chinabyte.com/414/12557414.shtml,2013.3

4. Zhu Min, "South Korea: Advantages for LTE Development", Huaxin Consulting Co.,Ltd., accessed fromhttp://www.srrc.org.cn/NewsShow9177.aspx,2014.2

5. Guo Luqing, "A Comparison of 4G Charges between China and other Countries",accessed fromhttp://biz.21cbh.com/2014/kuaibao_319/1102834.html,2014.3

6.

Guo Xiaofeng, "South Korean 4G Network Experience: 300RMB for 6 gigabytes trafficvolume"

7.

Don Mac Vittie, "Myths of Bandwidth Optimization", F5 Networks, Inc., 2012

8. Li Wenbin and Gen Bo, "Theoretical Analysis on TCP Throughput 0.2", 2009.6

9. J. Padhye, V. Firoiu, D. Towsley and J. Kurose, "Modeling TCP Reno performance: A

Simple Model and Its Empirical Validation", IEEE/ACM Trans. on Networking, vol. 8,no. 2, pp. 133-145, April 2000.

10.

Yang Chengming, "Empirical Analysis of Microblog Users' Behavioral Characteristics",

Business School of East China Normal University, 2011.6
http://network.chinabyte.com/414/12557414.shtmlhttp://www.srrc.org.cn/NewsShow9177.aspxhttp://biz.21cbh.com/2014/kuaibao_319/1102834.htmlhttp://biz.21cbh.com/2014/kuaibao_319/1102834.htmlhttp://www.srrc.org.cn/NewsShow9177.aspxhttp://network.chinabyte.com/414/12557414.shtml