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HUAWEI TECHNOLOGIES CO., LTD.
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www.huawei.com
Bridging QoE and QoS for
Mobile Broadband Networks
Dr. David Soldani
Huawei European Research Centre, Munich, Germany
Capacity Sharing Workshop, 13th Oct 2011
Institute of Communication Networks and Computer
Engineering (IKR) – University of Stuttgart, Germany
http://www.ikr.uni-stuttgart.de/Content/CapacitySharingWS/program.html
HUAWEI TECHNOLOGIES CO., LTD.
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Curriculum Vitae – Dr. David Soldani
• 16 years in ICT industry
• 2009 – present: Huawei Technology Düsseldorf
- VP European Research Centre
- Head of European Network Solutions R&D
• 2007 – 2009: Nokia Siemens Networks (NSN)
- Head of Solutions & Services Innovation (SSI)
- 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 Soldani VP European Research Centre
HUAWEI TECHNOLOGIES CO., LTD. Huawei Technologies Duesseldorf GmbH
Riesstr. 25, C – 3., 80992 Munich, Germany
Tel: +49-89-1588344095
Fax: +49-89-1588344447
Mobile: +49-1622047695
E-mail: david.soldani@huawei.com www.huawei.com
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Outline
• Definitions
• Industry trends
• Key technology issues
• User aware Customer Service Assurance
• Case study
• Bridging QoE and QoS
HUAWEI TECHNOLOGIES CO., LTD.
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Customer Experience Management
- The four pillars
Page 4
Source TM Forum
Customer Service
Assurance
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Outline
• Definitions
• Industry trends
• Key technology issues
• User aware Customer Service Assurance
• Case study
• Bridging QoE and QoS
HUAWEI TECHNOLOGIES CO., LTD.
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Managing customer experience becomes
operator core business
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Source: TMF – Exploiting Analytics, 2010
Budget • Customer retention
• Word of mouth
• Occasional buys
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IEEE Special Issues
http://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=6035803
http://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=5634431
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Outline
• Definitions
• Industry trends
• Key technology issues
• User aware Customer Service Assurance
• Case study
• Bridging QoE and QoS
HUAWEI TECHNOLOGIES CO., LTD.
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QoE challenges
3GPP QoS
(3GPP bearer)
IP QoS*
(Transport)
*) Includes data link layer (DLL)
Service KQI
QoE
3GPP UP KPI
3GPP CP KPI
IP/DLL KPI
QoE as a function of QoS
parameters (for Internet
Services) in near RT
Cross-layer, inter-domain
and intra-domain influence
(Problem localization)
NAS QoS
(Media component)
S1
S1,1
S1,1,1C1
C2
CN
5. Excellent
4. Good
3. Fair
2. Poor
1. Bad
5. Excellent
4. Good
3. Fair
2. Poor
1. Bad
S = Symptom
C = Cause
Identify causes from observed
symptoms (Alarms/KPIs)
(Cause identification)
MOS
HUAWEI TECHNOLOGIES CO., LTD.
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Solution segmentation
• Filtering and enforcement based on all possible combinations
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Services
• Web surfing
• Streaming
• File DL/UL
• …
Network Scope
• Whole Network
• Per region
• Per NE/Cell
• Per RAN Vendor
•…
Device
• All devices
• Device class
• Device type
• Device group
• …
Technology
• All technologies
• 2G
• 3G
• …
Customer
• All customers
• Segment
• Tariff
• …
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Page 11
Intelligent Traffic Management
Backhaul
MS BTS
NodeB RNC SGSN
Internet/
Intranet
HLR
Iub Iu-PS Gn
Gi Gr Gb
Datacard
eNB
eNB X2
S1-MME
S1-U
S4
S5 S6a
S7
S11
S3
SGi
LTE UE
Uu
Backbone
GGSN
MME
Serving GW PDNGW HSS
PCU
PCRF
Abis
Main Server
Site Servers
Client (MKT) Client (NPO)
Client (CFO)
Client (CTO)
Terminal
Agents
Embedded
Probes
Interface
Probes
QoE as a
function of QoS
parameters (for
Internet
Services) in
near RT
Adaptive
policy control
in near RT
Root causes
and drill down
into lower level
indicators in
near RT
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Outline
• Definitions
• Industry trends
• Key technology issues
• User aware Customer Service Assurance
• Case study
• Bridging QoE and QoS
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End-to-end view
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User Perspective
Business
Opportunities
Operations
Efficiency
Netw
ork
Pers
pective
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How to assess user’s perception?
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Subjective
evaluation
Data collection
(KPIs)
Co
rrela
tion
s
Estimated
QoE
Data collection
(KPIs)
Service
Modeling
Estimated
QoE Validation
• Narrow scope of application
and validity: expensive and
hardly ever reusable
• Wider scope of application
and high reusability
• Enough room for
customization
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User-Centric Service Modelling
Integrity KQI Retainability
KQI
Accessibility
KQI
Business KQI Business KQI Business KQI Business KQI
Application
KQI
Application
KQI
Applications
KQI
Application
KQI
Application
KQI
Network KPI Network KPI Network KPI Network KPI Network KPI Network KPI
Measured
Parameter
Measured
Parameter
Measured
Parameter
Measured
Parameter
Measured
Parameter
Measured
Parameter
Measured
Parameter
User-Centric Service Modeling (QoE)
Open questions:
• How does accessibility, retainability and integrity impact
user experience?
• What is the interdependency of the three KQIs on user
impact?
• Which KQI should be improved if the user is not satisfied?
• Why the user is not satisfied if all the three KQIs are OK?
• How to evaluate the QoE(t) within a session
• How to evaluate the QoE from session to session
• How to evaluate the QoE from sessions of different services
Composition rules
New functions
Computation models
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Terminal
Actions
Results Server
Service
User
Perception Interactions
User-centric Service Model (USM)
Begin
Session
Service
State 1
Result
Impact on user
Service
State 2
Result
Impact on user
End
Session
Result
Impact on user
Service session QoE(t) Session
QoE
User
Action
Network
event
User
Action
Network
event
User
Action
Network
event
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USM: Examples
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User-Centric
Service
Model
KQI_availability
KQI_retainability
KQI_accessibility
Web Download
Session =KPI1…..KPIz
One user
Over many
sessions
YouTube
• 1 session
• context known
• 1 session
• context known
• 1 session
• context known
Session =KPI1…..KPIy Session =KPI1…..KPIx
• idle period
• user active
KQI_availability
KQI_retainability
KQI_accessibility
KQI_availability
KQI_retainability
KQI_accessibility
Legacy
quality
assessment
On target troubleshooting
QoE(t)=f(KPI1,.....,KPIz) QoE(t)=f(KPI1,.....,KPIy) QoE(t)=f(KPI1,.....,KPIx)
Anomaly
Detection Trouble-
shooting
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User centric Troubleshooting (UTS)
User perception
KQIs Segment x
Statistical
measurement
of QoE
per
segment of
users
TDR
TDR
TDR
TDR
TDR
TDR
TDR
TDR
TDR
TDR
TDR
TDR
TDR
TDR
TDR
TDR
TDR
TDR
TDR
TDR
TDR
SDR
SDR
SDR
SDR
SDR
SDR
SDR
SDR
KPIs Interface 1
Protocol 1
KPIs Interface 1
Protocol 2
KPIs Interface 1
Protocol 3
KPIs Interface 2
Protocol 1
KPIs Interface 2
Protocol 2
KPIs Interface 3
Protocol 1
KPIs Interface 3
Protocol 2
CORRELATION
TDR = Transaction Data Record
SDR = Session Data Record
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uCSA: USM value added to CSA
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Service
Acceptability: satisfied?
Service Provider User
KPI_1
KPI_2
KPI_3
KPI_n
KQI_accessibility
KQI_retainability
KQI_integrity
Service Model
User-
Centric
Service
Modeling
Value Added KQI QoE
Value Added
Usage
Analysis &
Forecasting
QoE
Assessment
QoE
Monitoring &
Assurance
Business
Intelligence
Intelligent
Trouble-
shooting
QoE
Intelligence
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Network and technology agnostic
approach
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Messaging Services
Voice (telephony) Services
Streaming Services
Storage Services
Web Browsing Services
Cloud Services (SaaS, IaaS...)
M2M Services
Fixed Networks
MBB
User-
Aw
are
Custo
mer
Serv
ice A
ssura
nce
QoS/QoE
Assessment
QoS/QoE
Assurance
Trouble
shooting
Forecasting
Provisioning
Optimization
Control
SLM BPM CEM
M2M & Cloud
Infrastructure
(near) future
User-centric
Service
Modelling
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Outline
• Definitions
• Industry trends
• Key technology issues
• User aware Customer Service Assurance
• Case study
• Bridging QoE and QoS
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Page 22
Service quality differentiated G/S/B portfolio
22
Service 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
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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:
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Page 24
User satisfaction criteria for HSPA
User
Type
Av.
Speed
(GBR*)
Web
Surfing
http
streaming
RTP
streaming
File
downloads
Gold 512
kb/s
Web page
delay <
4s
Throughput
384 kb/s
Throughput
90 kb/s
PDL < 300 ms
PERL < 10-6
Throughput
GBR
Silver 256
kb/s
Web page
delay <
8s
Throughput
192 kb/s
Throughput
90 kb/s
PDL < 300 ms
PERL < 10-3
Throughput
GBR
Bronze 128
kb/s
Web page
delay <
10s
NA NA NA
*) Minimum target rate
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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
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With QoS - RTP Streaming
G = (B-A)/A = 30% or equivalently 22% of site savings!
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
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• Definitions
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• Key technology issues
• User aware Customer Service Assurance
• Case study
• Bridging QoE and QoS
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Bridging QoE and QoS: possible approaches
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Solutions • User Classification Fairness (UCF)
• Control of Flow Mobility
Network and terminal data
(M2, eRAN, CN, etc.)
TDR SDR
KPI KQI
USM UTS
UTM
(User centric Traffic Management)
PC
C
KFI
CBR
UCF
Targets • QoE at optimal QoS
• ARPU / Market Share
KFI = Key Financial Indicators
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References D. Soldani, S. Beker, R. Cuny, D. Jurca, “An Innovative Framework for Service
Assurance,” Huawei Communicate, November 2011.
D. Soldani, S.K. Das, J.A. Hassan, M. Hassan, G. D. Mandyam, “Traffic
Management for Mobile Broadband Networks,” IEEE Communications Magazine,
October 2011.
S. Beker, ETSI WS on Future Networks, Sept 2011.
http://docbox.etsi.org/Workshop/2011/201109_FUTURENETWORKS/
D. Soldani, ETNO WS on Innovation, June 2011.
http://intranet.etno.be/mailroot/trento-post/the-conference/index.html
D. Soldani, Hou Xiao Jun, B. Lück, “Strategies for mobile broadband growth:
traffic segmentation for better customer experience,” IEEE VTC Spring 2011
J.A. Hassan, S.K. Das, M. Hassan, C. Bisdikian, D. Soldani, “Improving quality of
experience for network services,” IEEE Network, Vol. 24, pp. 4 – 6, March 2010.
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Thank you www.huawei.com
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