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HUAWEI TECHNOLOGIES CO., LTD.
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www.huawei.com
Driving the Digital Future – What
Innovation in Services for
Telecom Operators
Dr. David Soldani
EU-NSD/European Research Centre
Trento Innovation Workshop, 24th June 2011
http://intranet.etno.be/mailroot/trento/default.html
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HUAWEI TECHNOLOGIES CO., LTD.
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Curriculum Vitae – Dr. David Soldani
• 15 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
- 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: [email protected] www.huawei.com
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Outline
• Definitions
• Industry trends
• Key technology issues
• User aware Customer Service Assurance
• Bridging QoE and QoS
• Case study
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Quality of Experience (QoE)
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• 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 occurs 5. 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
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Quality of Service (QoS)
“The ability of a network to provide such a service
application with an assured service level.” by 3GPP
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• Functions (mechanisms)
and parameters in the
network and handset
that ensure the
provision of the
negotiated service
quality between peer
entities
• Provide packet transfer
in a better-than-best-
effort way (IETF)
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QoS and QoE parameters – Mapping Model
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Subjective
Measurements
Objective
Measurements
QoS QoE
SQoS
(Network based) e.g. Packet Error Loss Ratio
ESQoS
(Service based) e.g. Web Page Loading Time
MOS (Mean Opinion Score)
Objective
evaluation
Subjective
evaluation
Viable solution SQoS = System QoS
ESQoS = E2E Service QoS
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Customer Experience Management
- The four pillars
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Source TM Forum
Customer Service
Assurance
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Outline
• Definitions
• Industry trends
• Key technology issues
• User aware Customer Service Assurance
• Bridging QoE and QoS
• Case study
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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://dl.comsoc.org/livepubs/ci1/info/call.html
http://dl.comsoc.org/livepubs/ni/public/2010/mar/index.html
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Outline
• Definitions
• Industry trends
• Key technology issues
• User aware Customer Service Assurance
• Bridging QoE and QoS
• Case study
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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
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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
• E-mail
• …
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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Intelligent Traffic Management
Backhaul
MS BTS
NodeB RNC SGSN
Internet/
Intranet
HLR
Iu
b 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
Abi
s
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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What are the main issues in the
current approaches?
• Open questions:
How does accessibility, retainability and integrity relate to the 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
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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
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RTT
(empty
NW)
Bearer
setup delay
(empty
NW)
PDP context
setup delay DNS setup
delay
Application
setup delay
Radio
load
Packet
core
load
App.
Server
load
End user
device
load
Nw
element/
int. failure
QoS profile
(PDP
context)
Device
screen
resolution
Content
encoding
rate
TCP
parameters
(device
and server)
Transport
load
Application
throughput
1st packet
delay App.
packet
jitter
Application
cutoff ratio
HTTP Video
Streaming Quality
PDP context
setup
success rate
DNS
success
rate
Application setup
success rate
App.
packet
loss rate
Origin variable (within a data service session)
Variable dependent on other variable(s)
PDP context
cuttoff ratio
Load
next
packet
delay
App.
device
buffer
size
Rebuffering
(number and
duration)
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What do we propose to close this
gap?
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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
Intelligent
Traffic
Management
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Proposed solution User centric Service Model (USM)
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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-aware Customer Service Assurance (uCSA)
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Probes Network
Elements
Data
Collection
Mediation
Probes
Data
Collection
Network
Elements
USM
Mapping to R-
KPIs
Data Consolidation & Storage Layer
User-centric
Service
Modelling
(USM)
Correlation Correlation
Correlation
Aggregation Aggregation
Aggregation Storage
Business
Intelligence
QoS/QoE
Level
Management
Trouble
Shooting
& user tracing
Network
Planning,
Design &
Configuration
QoS/QoE
Assessment
Network
Optimization
Intelligent
Traffic
Management
Infrastructure Layer: To Enable Network Visualization
Functional Objectives: Enable Customer Business
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Outline
• Definitions
• Industry trends
• Key technology issues
• User aware Customer Service Assurance
• Bridging QoE and QoS
• Case study
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Bridging QoE and QoS: possible approaches
uCSA
TB NB
TA
P P P
P
1
SON
2
4
3
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Outline
• Definitions
• Industry trends
• Key technology issues
• User aware Customer Service Assurance
• Bridging QoE and QoS
• Case study
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Service quality differentiated G/S/B portfolio
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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
See:
D. Soldani, Hou Xiao Jun, B. Lück, “Strategies for mobile broadband growth: traffic segmentation for better
customer experience,” IEEE VTC Spring 2011
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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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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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Thank you www.huawei.com