HUAWEI TECHNOLOGIES CO., LTD.
Security Level:
47pt
www.huawei.com
Bridging QoE and QoS for Mobile Broadband NetworksDr. David Soldani VP Huawei European Research Centre
21-22 September 2010
http://www.etsi.org/WebSite/NewsandEvents/QoSQoEUserExperience.aspx
HUAWEI TECHNOLOGIES CO., LTD. Page 2
Curriculum Vitae – Dr. David Soldani
• 15 years in ICT industry
• 2009 – present: Huawei Technology Düsseldorf
- VP European Research Centre
- Head of IP Transformation Research Centre (IPTRC)
• 2007 – 2009: Nokia Siemens Networks (NSN)
- Head of Solutions & Services Innovation
- Head of Customer Networks & Solutions (CTO office)
• 1997 – 2007: Nokia (Finland and Italy)
- Various technical & research management positions
• 1995 – 1997: Military Navy, Sirti SpA, Rohde & Schwarz
- Various technical positions
Areas of Expertise (not exhaustive)
• Lead R&D and Customer Services organizational units
• Unit/area strategy formulation and implementation
• Technology and Innovation Management for ICT industry
• Conduct lectures at Universities, Military Academy and ICT Companies
• Perform advanced research in the fields of own expertise
• Provide consulting functions to profit and nonprofit organizations
• Supervise any type of R&D deliverables
• Published/presented many international papers
• Editor in chief and one of the main contributors to several books
• Holder of several international patents
Relevant Experience (not exhaustive)Professional Background
• Solutions for Traffic Management in Mobile Broadband Networks
• Mobile Broadband Networks (TETRA, GSM, EDGE, WCDMA, HSPA, LTE/SAE and WiMAX)
• E2E QoS, QoE and Policy Based Management Solutions
• E2E Service and Network Performance, Network Planning, Optimization and Automation
• Transport Network Layer Technologies (IP/MPLS/Ethernet)
• Fixed Broadband Networks (xDSL, xPON)
Dr. David SoldaniVP European Research Centre
HUAWEI TECHNOLOGIES CO., LTD.Huawei Technologies Duesseldorf GmbHRiesstr. 25, D - 3.0G, 80992 Munich, Germany
Tel: +49-89-1588344095Fax: +49-89-1588344446Mobile: +49-1622047695E-mail: [email protected]
Outline
• Definitions and industry trends
• Objectives of monitoring QoE indicators
• Solution layered architecture
• Bridging QoE and QoS
• Reference case
• Conclusions
HUAWEI TECHNOLOGIES CO., LTD. Page 4
Definition: Quality of Experience (QoE)
• Measurement of how well that
network is satisfying the end user's requirements
• Includes the complete end-to-
end system effects (client,
terminal, network, services infrastructure, etc.)
• QoE is also a consequence of
a user’s internal state (e.g.
expectations), the characteristics of the
designed system (e.g.
functionality) and the context(or the environment) within
which the interaction occurs5. Excellent
4. Good
3. Fair
2. Poor
1. Bad
“The overall acceptability of an application or service, as perceived subjectively by the end-user.”by ITU-T P.10/G.100
HUAWEI TECHNOLOGIES CO., LTD. Page 5
QoS and QoE parameters – Mapping Model
SubjectiveMeasurements
ObjectiveMeasurements
QoS QoE
SQoS(Network based)e.g. Packet Error Loss Ratio
ESQoS(Service based)e.g. Web Page Loading Time
MOS(Mean Opinion Score)
Objectiveevaluation
Subjectiveevaluation
Viable solutionSQoS = System QoSESQoS = E2E Service QoS
HUAWEI TECHNOLOGIES CO., LTD. Page 6
2020 Global Broadband Revenues Forecast
Source: Mobile, Fixed and Wholesale Broadband Business Models, Telco 2.0, June 2010
• Increase of 52% in revenue and more than half the revenue growth will come from wholesale and “two-sided” fees for improved access capacity and quality
• Current forecast expects mobile data traffic to grow by 300x to 500x over the next 10 years: mobile broadband will be worth $138bn (32% of total broadband revenues)
• New ‘upstream’ customers are forecast to generate over $90 billion in broadband revenues globally by 2020
HUAWEI TECHNOLOGIES CO., LTD. Page 7
1. Offloading to WiFi2. Offloading to Femtocell3. Radio network enhancements
1. Signaling management2. Macro network offload 3. Radio packet scheduling and prioritization
4. Compression, adaptation and transcoding Compression Rate-adaptation Network-sharing
5. Device-based traffic management techniques 6. Contention management & tuning TCP/IP 7. Deep packet inspection, policy-based traffic shaping & differential
charging 8. End-to-end service assurance and monitoring9. Caching, multicast & CDNs10. Congestion APIs
Key Technologies for Mobile Broadband Traffic Management
Source: Disruptive Analysis, June 2010
In many operators, there is often no single individual who "owns" the issue of data traffic, who can develop a holistic solution
In many operators, there is often no single individual who "owns" the issue of data traffic, who can develop a holistic solution
8. End-to-end service assurance and monitoring
HUAWEI TECHNOLOGIES CO., LTD. Page 8
QoE/QoS aspects addressed by all important standardization bodies
MobileVoice
VOIP MTVIPTV Data
Framework
E2E Servicemetrics
Systemmetrics
Measurement Method
GB934 GB938
TR 26.944
TS 102 250 -3/4TS 101 329 - 5
P.NAMS PEVQG.1070
P.861-862 P.563 G.107seriers
Y.1541
E.800
TS 32.410TR 32.814
MDI
Y.1541
TS 32.425
Improving QoE of RT
Communication Services
ETSI Specialist Task Force 354
UE satisfaction criteria
TS 102 250-2
KQI for PS services
ETSI STQ
TR-126
EG 202 670
HUAWEI TECHNOLOGIES CO., LTD. Page 9
Audio QoE: the state of art
P.564
G.107E-Model
1996 1998 2002
ETSI ETR 250
TS 101 329-5
P.861PSQM
P.862PESQ
P.563
ITU P.800
P.562
P.561
P.OLQAP.CQO
2005
• PESQ: intrusive method that compares the degraded signal to the original signal• P.563: non-intrusive method and does not need the original signal• P.564: model for assessing voice over IP transmission quality• E-Model: non-intrusive method and its extensions in under study (2009-2012)• P.OLQA: evolution of PESQ and it is still under research (2009-2010)• P.CQO: new model based on P.561, P.563, P.564 and E-Model currently under study (2009-2012)
• PESQ: intrusive method that compares the degraded signal to the original signal• P.563: non-intrusive method and does not need the original signal• P.564: model for assessing voice over IP transmission quality• E-Model: non-intrusive method and its extensions in under study (2009-2012)• P.OLQA: evolution of PESQ and it is still under research (2009-2010)• P.CQO: new model based on P.561, P.563, P.564 and E-Model currently under study (2009-2012)
• E-Model is supported by Huawei SQM/QoE products• E-Model is supported by Huawei SQM/QoE products
E-ModelExtension
HUAWEI TECHNOLOGIES CO., LTD. Page 10
Video QoE: the state of art
Reduced Reference
Non ReferenceFull ReferenceSubjective
Estimation
Image resolution
ITU-T J.246
ITU-T J.147
ITU-T J.249
VQEG:
MM Project
VQEG:
RRNR-TV
HDTVITU-T SG12: P.NAMSP.NBAMS
G.OMVASITU-T P.910
ITU-T P.911
ITU-R BT.500
ITU-T J.140
ITU-T J.245
QCIF
CIF
VGA
HDTV
SDTV
ITU-T J.247
ITU-T J.144
ITU-R BT.1683
Completed Ongoing projects
• P.NAMS (from packet header) and P.NBAMS (from payload information): non-reference multimedia, audio and video quality estimation methods
• G.OMVAS defines a Quality Planning Tool (E-Model) for IPTV services (by 2011)• ITU-T also has several IPTV QoE projects, such as G.IPTV_MMRP, G.IPTV_PMP.
• P.NAMS (from packet header) and P.NBAMS (from payload information): non-reference multimedia, audio and video quality estimation methods
• G.OMVAS defines a Quality Planning Tool (E-Model) for IPTV services (by 2011)• ITU-T also has several IPTV QoE projects, such as G.IPTV_MMRP, G.IPTV_PMP.
• Huawei has a non-reference video quality estimation method, called MOS-V, it is a contribution to P.NAMS, and it is supported by Huawei SQM/QoE products
• Huawei has a non-reference video quality estimation method, called MOS-V, it is a contribution to P.NAMS, and it is supported by Huawei SQM/QoE products
HUAWEI TECHNOLOGIES CO., LTD. Page 11
IEEE special issue on QoE- March 2010 -
• IEEE Network – Special Issue on Improving Quality of
Experience for Network Services
Guest Editors Dr. Jahan A. Hassan
University of New South, Wales, Australia
Prof. Sajal K. DasUniversity of Texas at Arlington, USA
Prof. Mahbub Hassan,University of New South Wales, Australia
Dr. Chatschik BisdikianIBM T. J. Watson Research Center, USA
Dr. David SoldaniHuawei Technologies Co.,Ltd., Germany
http://dl.comsoc.org/livepubs/ni/public/2010/mar/index.html
Outline
• Definitions and industry trends
• Objectives of monitoring QoE indicators
• Solution layered architecture
• Bridging QoE and QoS
• Reference case
• Conclusions
HUAWEI TECHNOLOGIES CO., LTD. Page 13
Operators’ challenges• Very little work available on end user perception of the
services, especially from Internet, that are being offered
• Gaps between network measured quality and user perceived experience
• Mechanisms, procedures and tools to continuously monitor, operate and report QoE indicators
Ban
dw
idth
End to End
Effects!
1
Cause!
User plane
Control plane
2
HUAWEI TECHNOLOGIES CO., LTD. Page 14
Main objectives
1. QoE monitoring as support for strategic company decisions
2. QoE monitoring for network optimization, supervision and operation
3. Support for business and customer intelligence processes
Outline
• Definitions and industry trends
• Objectives of monitoring QoE indicators
• Solution layered architecture
• Bridging QoE and QoS
• Reference case
• Conclusions
HUAWEI TECHNOLOGIES CO., LTD. Page 16
Functional architecture
Accessnode
Accessnode
Core Network node
Core Network node
Aggregationnode
Aggregationnode
Terminal device
Terminal device
Embedded Agents
Network Elements and Interfaces Probes
Network Elements PM and FM Data
Corenode Corenode
Service corenode
Service corenode
Data Acquisition Data Acquisition LayerLayer
Data Analysis Data Analysis LayerLayer
Data Presentation Data Presentation LayerLayer
Data Query, Filtering, Refinement,Correlation and Processing
System QoS, Alarms and Events
Network Model, Configuration and Topology
E2E Service QoS and Events Data CollectionData Collection
LayerLayer
MBB QoE Indicator reports
MBB QoE Network Optimization, Supervision
and Operation
Customer and Business Intelligence
Functional Functional Objectives/Use CasesObjectives/Use Cases
Data Visualization and Report Generation
Mediation layer
Mediation layer (Optional)
Network Based Network Based ApproachApproach
Terminal Based Terminal Based ApproachApproach
HUAWEI TECHNOLOGIES CO., LTD. Page 17
Functional elements (layers)
• Data acquisition layer All relevant information related to QoE monitoring and measuring
Network and Terminal based approaches
• Data collection layer Storage for vertical solutions with continuous monitoring
Real time (seldom) and periodic monitoring
Scale of samples across network and customers
• Data analysis layer Format and data conversion required for different data sources
Data query, filtering, refinement, correlation and processing
Data aggregation, correlating and processing layer
Storage for horizontal solution
• Presentation layer Tools for visualization and report generation
Continuous tracking of mobile broadband experience
Customer experience as a combination of network indicators
HUAWEI TECHNOLOGIES CO., LTD. Page 18
Solution segmentation
ServicesServices
• Web surfing• Streaming• File DL/UL• E-mail• …
Network ScopeNetwork Scope
• Whole Network
• Per region
• Per NE/Cell
• Per RAN Vendor
•…
DeviceDevice
• All devices
• Device class
• Device type
• Device group
• …
TechnologyTechnology
• All technologies
• 2G
• 3G
• …
CustomerCustomer
• All customers
• Segment
• Tariff
• …
• Filtering based on all possible combinations
HUAWEI TECHNOLOGIES CO., LTD. Page 19
Layered approach
………Throughput of service C of user X,Packet drop ratio,…
Throughput of service B of user X,Packet drop ratio,…
…
Streaming
…
etc
…
VoIP
Email SessionSetup Success RatioEmail SessionSetup time…
Session Setup Success RatioActive Session Throughput…
FTP download
Web Page Loading Time
Active Session Throughput
…
SDU Throughput, SDU Error Ratio, SDU Transfer Delay …
Per User,QoS class, etc.
Look at the pipe(a PDP context)
Monitored ParametersSegmentation / Granularity
Gross and net throughput at each interface (cell, Iub, …),Wide band received and transmitted power (cell), etc.
Per Cell, Itf,NE, etc.
Look at theinfrastructure
Throughput of service A for user X,Packet drop ratio,…
Per service,User, etc.
Look shallowlyinto the pipe
Web Browsing
Service Quality
Look deeplyinto the pipe
“Pipe” = Bearer service
Mobile Broadband Network
HUAWEI TECHNOLOGIES CO., LTD. Page 20
Huawei Solution for 3GPP Packet Switched Networks
Backhaul
MSBTS
NodeB RNCSGSN
Internet/Intranet
HLR
Iub Iu-PSGn
GiGrGb
Datacard
eNB
eNB
X2S1-MME
S1-U
S4
S5 S6a
S7
S11
S3
SGi
LTE UE
Uu
Data acquisition from NE & OSS
FM / PM and 3GPP NE
embedded probes
Data acquisition from Interface
Data acquisition from transport NE
Transport NE embedded
and interface probes
Data acquisition from Terminal
Device
manager
Service Quality Manager
3r party
Backbone
GGSN
MME
Serving GW PDNGW HSS
PCU
PCRF
Abis
Outline
• Definitions and industry trends
• Objectives of monitoring QoE indicators
• Solution layered architecture
• Bridging QoE and QoS
• Reference case
• Conclusions
HUAWEI TECHNOLOGIES CO., LTD. Page 22
User and service satisfaction criteria
Gold, Silver and Bronze usersG, S, B• User active throughput > User_BW AND
• Session success rate > User_Target_SSR
User bandwidth
8
7
6
5
4
3
2
1
QoS class* (i)
• Air interface (IP) packet error loss rate < User_PELR(i) AND
• 98-percentile delay < User_PDB(i) – 20 ms AND
• Active throughput > User_target_rate(i) AND Video (Buffered Streaming), TCP-based
(e.g., www, e-mail, chat, ftp, p2p file sharing, progressive video, etc.)
Voice, Video (Live Streaming), Interactive Gaming
Non-GBRVideo (Buffered Streaming), TCP-based (e.g., www, e-mail, chat, ftp, p2p file sharing, progressive video, etc.)
IMS Signalling
Non-Conversational Video (Buffered Streaming)
Real Time Gaming
Conversational Video (Live Streaming)GBR
Conversational Voice• Air interface (IP) packet loss error rate < User_PELR(i) AND
• 98-percentile delay < User_PDB(i) – 20 ms AND
Example Services and UsersSatisfaction criterionResource Type
10.0Mb/s
*) Unique combination of QoS parameters identifying the bearer or service data flows, e.g. DSCP
HUAWEI TECHNOLOGIES CO., LTD. Page 23
Target performance
8
7
6
4
3
2
5
1
QoS class* (i)
< 384 kb/s, < 64 kb/s
4-13 kb/s, < 384 kb/s, < 60 kb/s
< 384 kb/s, < 128 kb/s
4-13 kb/s
20-384 kb/s
60 kb/s, 30 kb/s
32-384 kb/s
4-25 kb/s
Data Rate (DR)
Video (Buffered Streaming),TCP-based (e.g., www, e-mail, chat, ftp, p2p file sharing, progressive video, etc.)10-6300 ms
Voice,Video (Live Streaming),Interactive Gaming10-3100 ms
Non-GBR
Video (Buffered Streaming),TCP-based (e.g., www, e-mail, chat, ftp, p2p file sharing, progressive video, etc.)
10-6300 ms
IMS Signalling10-6100 ms
Non-Conversational Video (Buffered Streaming)
10-6300 ms
Real Time Gaming, Telemetry10-350 ms, 250 ms
Conversational Video (Live Streaming)
10-3150 msGBR
Conversational Voice10-2100 ms
Example ServicesPacket Error Loss Rate (PERL)b
Packet DelayBudget (PDB)a
Resource Type
a) PDB (radio) = PDB (BS-PCEF) - 20 ms (Delay Correction BS-PCEF)b) PERL (non congested BS-PCEF) = 0*) Unique combination of QoS parameters identifying the bearer or service data flows, e.g. DSCP
Reference [3GPP TS 23.203, TS 22.105]
HUAWEI TECHNOLOGIES CO., LTD. Page 24
Relationship between QoE and QoS1. Constant optimal QoEE.g. x1 (sharp threshold) is the boundary below which a user
feels the system reacting instantaneously
2. Sinking QoEThe higher the QoE the higher the impact of a certain additional QoS
disturbance on QoE
3. Unacceptable QoEE.g. Reached x2 (user-
dependent threshold) the transmission might become unacceptably bad in quality
QoSeQoE
QoEQoS
QoE
QoSfQoE
)(
)(
HUAWEI TECHNOLOGIES CO., LTD. Page 25
VoIP: Internet low bit rate codec as used by Skype
• Voice quality affected by loss, jitter and reordering
• Type-p reordered ratio is used to quantify the jitter
98th percentile delay < 100 msPERL < 10-2
HUAWEI TECHNOLOGIES CO., LTD. Page 26
Web Browsing: perceived quality
• QoS in terms of response and download times
• Web session: (a) requesting a search page; (b) typing and submitting a query; and (c) retrieving the results
Web page loading time < 4s
User throughput > 64 kb/s
HUAWEI TECHNOLOGIES CO., LTD. Page 27
Example of Video clips: quality affected by packet loss
• QoE scores of a video clip repaired with two loss concealment schemes at various packet loss rates
PELR < 10-6PELR < 10-6
HUAWEI TECHNOLOGIES CO., LTD. Page 28
• Encoder H.264 with one IP packet = 7 × 188 Bytes
• With 100 kb/s and PERL 10-6 PLF = 1.2x10-4
Example of video quality of IPTV Services: quality affected by packet loss
HUAWEI TECHNOLOGIES CO., LTD. Page 29
Example of service satisfaction criteria
Web Service Web Paging Loading Time AND
Active Session Throughput
Video Streaming Streaming Mean Active Throughput AND
Streaming Media Active Transport Jitter AND
Streaming Media Loss
Video via HTTP Active Session Throughput
VoIP Call Setup Success Ratio AND
Call Setup Time AND
Call Cut-off Ratio AND
Speech Quality
HUAWEI TECHNOLOGIES CO., LTD. Page 30
Satisfaction estimation using Fuzzy Logic
0
1
a ba KPI
Truth (KPI)
0
1
Truth (WPLT)
0
1
Truth (WPLT)
Air Interface Packet Error Rate (%) 98th-Percentile of Delay (ms)
Truth (PD)Truth (PELR)
1 100
Satisfaction = min [Truth (Air Interface Packet Loss Error Rate), Truth (98th-Percentile of Delay )]
Truth Value of a KPI (denoted by
weight) is given by
• Maximum of truth values, if logical OR is used
• Minimum of truth values, if logical AND is used
Example for VoIP:
HUAWEI TECHNOLOGIES CO., LTD. Page 31
Bridging QoE and QoS
① Generic Truth function of
a QoS parameter:
② Ex. Truth value (weight) of QoE for Web Browsing:
0.9384Active Session Throughput (kb/s)
0.30.33Web Page Loading Time (s)
Weight (Satisfaction)TruthValueKPI
QoE = Exp(- QoS) +
Satisfaction = min [Truth (Web Paging Loading Time), Truth (Active Session Throughput)]
Configurable parameters: , , , x1 and x2
Needs to be normalized
Outline
• Definitions and industry trends
• Objectives of monitoring QoE indicators
• Solution layered architecture
• Bridging QoE and QoS
• Reference case
• Conclusions
HUAWEI TECHNOLOGIES CO., LTD. Page 33
Service quality differentiated G/S/B portfolio
33
Service Quality Differentiation in Mobile Broadband portfolioService Quality Differentiation in Mobile Broadband portfolio
Bronze – Tariff A
Silver – Tariff B
Gold – Tariff C
„Ultimate“(e.g. HD Video)
„Best for Social Media“(e.g. facebook, youtube etc.)
„Best for Surf & Chat“
Service Quality Differentiation
Max Mbps DL/Mbps UL
Avg. Mbps DL/ Mbps UL
FUP / SSD
Montly fee
HUAWEI TECHNOLOGIES CO., LTD. Page 34
Bandwidth levels
(In loaded networks, e.g., throttling of Streaming and/or HD Video services for Bronze will make it possible to allocate the freed capacity to Gold, or Silver, so that a higher priority will enable a better user experience.)
Empty network
Bronze Silver GoldBronze Silver Gold
Streaming SurfingHD videoAllocated capacity:
Tariff
Speed
Tariff
Speed
Loaded networkEmpty network
Bronze Silver GoldBronze Silver Gold
Streaming SurfingHD videoAllocated capacity:
Tariff
Speed
Tariff
Speed
Loaded network
(1) Surfing
(2) http Streaming
(3) RTP Streaming
(4) E-Mail
(5) File DL
(6) Other
Example of Mapping for Gold:
HUAWEI TECHNOLOGIES CO., LTD. Page 35
QoS benefits
Dissatisfied Users (%)
Traffic (variable)
10%
With QoS on (at cost X)
All on BE (no QoS, with Resources R1)
QoS Gains = T2-T1 (at cost X, for paying the QoS features,
with resources R1)
Traffic = T2
Traffic mix = Tm(held constant)
0%
Traffic = T1
Worst performing
service Satisfied Users (%)
Resource (variable)
90%Over provisioning
Additional Resources R2, at cost Y, for accommodating
the same traffic as with QoS on, satisfactorily
Traffic = T2(both held constant)
Traffic mix = Tm
0%
Profit = Y-X > 0
Over provisioning = R2-R1Worst performing
service
Total profitTotal profit
1) Benefit of radio, transport and gateway QoS functions for HSPA and LTE/SAE
2) Corresponding cost savings with respect to over provisioning
+ additional revenues!
RNC
SGSN&GGSN
Web/Streaming/E-mail/FTP/MMS server
Traffic Generator
Downlink traffic
Node B
HUAWEI TECHNOLOGIES CO., LTD. Page 36
Traffic Mix
70%30%Without QoS
60%30%10%With QoS
BronzeSilverGoldUser Mix
35%5%3%7%15%35%
OtherFile
downloadse-mailRTP
streaminghttp
streamingSurfing
Service Mix
HUAWEI TECHNOLOGIES CO., LTD. Page 37
User satisfaction criteria for HSPA
NANANAWeb page delay < 10s
128 kb/s
Bronze
Throughput GBR
Throughput 90 kb/sPDL < 300 msPERL < 10-3
Throughput 192 kb/s
Web page delay < 8s
256 kb/s
Silver
Throughput GBR
Throughput 90 kb/sPDL < 300 msPERL < 10-6
Throughput 384 kb/s
Web page delay < 4s
512 kb/s
Gold
File downloads
RTP streaming
http streaming
Web Surfing
Av. Speed (GBR*)
User Type
*) Minimum target rate
HUAWEI TECHNOLOGIES CO., LTD. Page 38
Without QoS - RTP Streaming
RTP streaming: % of Satisfied users
Number of users
Threshold = 90%
A = 3300
0
20
40
60
80
100
1000 1500 2000 2500 3000 3500 4000 4500 5000 5500 6000 6500
G
S
HUAWEI TECHNOLOGIES CO., LTD. Page 39
With QoS - RTP Streaming
G = (B-A)/A = 30%
0
1000 2000 3000 4000 5000 6000 7000
RTP streaming: % of Satisfied users
Number of users
Threshold = 90%
20
40
60
80
100
G
S
B = 4300
HUAWEI TECHNOLOGIES CO., LTD. Page 40
Gains in terms of % of satisfied users• The more users that can be satisfied, at a given offered load, the more
efficiently the spectrum is utilized by the operator
Limit = 90%
BS1 BS2
BS3
Traffic volume(kb/s)
Offered traffic(“Held constant”)
% Satisfied users BS = Bearer Service
Fitness
Fitness = |QoE Actual - QoE Target|
HUAWEI TECHNOLOGIES CO., LTD. Page 41
Example: QoS optimization for 5 traffic mixes
Mix 1 Mix 2 Mix 3 Mix 4 Mix 5
-10
0
10
20
30
40
50
60
1 10 100Iteration
Best
fitn
ess
Too much traffic
Too low traffic
Target
Traffic volume: optimisation
really effective!
Outline
• Definitions and industry trends
• Objectives of monitoring QoE indicators
• Solution layered architecture
• Bridging QoE and QoS
• Reference case
• Conclusions
HUAWEI TECHNOLOGIES CO., LTD. Page 43
What could be standardized?
QoE as a combination of QoS parameters (e.g. ETSI TS 102
250-2) and truth functions (fuzzy logic)
NGBR and GBR bearer satisfaction criteria and user
satisfaction criteria as a function of them
Call Detail Records (CDR) for service data flows and relevant
interfaces / elements, which shall support those
Requirements for embedded probes and terminal agents for
multi-vendor support
HUAWEI TECHNOLOGIES CO., LTD. Page 44
References
1. D. Soldani, M. Li and R. Cuny, QoS and QoE Management in UMTS Cellular Networks, John Wiley & Sons (2006)
2. ITU-T Recommendation P.10/G.100 (incl. Amendment 2), “Vocabulary for performance and quality of service,” July 2006 (2008)
3. A. Takahashi, K. Yamagishi, G. Kawaguti, “Recent Activities of QoS/QoE Standardization in ITU-T SG12,” NTT white paper, 2008.
4. ETSI TS 102 250-2 V1.7.1 “QoS aspects for popular services in GSM and 3G networks; Part 2:Definition of Quality of Service parameters and their computation,” October 2009
5. ETSI EG 202 670 V1.1.1 “Human factors (HF); user experience guidelines for real-time communication services expressed in quality of service terms,” March 2010
6. P. Brooks, B. Hestnes, “Being objective and quantitative about user measurements of QoE,” IEEE Network Comm. Magazine, March 2010
7. M. Fiedler, T. Hossfeld and Phuoc Tran-Gia, “A generic quantitative relationship between quality of experience and quality of service,” IEEE Network Comm. Magazine, March 2010.
8. Kuan-Ta Chen, et al., “Quadrant of Euphoria: a crowd sourcing platform for QoE assessment,”IEEE Network Comm. Magazine, March 2010
9. K. Yamagishi, T. Hayashi, “Parametric packet-layer model for monitoring video quality of IPTV services,” IEEE, ICC, 2008
10. D. Soldani, Hou Xiao Jun, B. Lück, “Strategies for mobile broadband growth: traffic segmentation for better customer experience,” IEEE VTC Spring 2011 (submitted)
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