Bridging QoE and QoS for Mobile Broadband Networks

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





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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: [email protected] www.huawei.com

mailto:[email protected]





http://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


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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



• 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://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=6035803


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Outline

• Definitions

• Industry trends



• 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

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



• Case study



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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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• Definitions

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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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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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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.

Page 29

http://docbox.etsi.org/Workshop/2011/201109_FUTURENETWORKS/







Thank you www.huawei.com

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Bridging QoE and QoS for Mobile Broadband Networks