umts ran dimensioning

8/10/2019 UMTS RAN Dimensioning

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Treffen/Workshop der ITG Fachgruppe 5.2.1

Radio Access Network Dimensioning

for 3G UMTS

Xi Li

[email protected]

November 13, 2009


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Outline

Introduction and Motivation

UMTS Network Dimensioning Framework

Developed Simulation Models

Developed Analytical Models

Dimensioning Models and Results

Conclusions and Outlook


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Outline








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Universal Mobile Telecommunication System (UMTS)

UE User Equipment

Node B Base Station

RNC Radio Network Controller

UTRAN UMTS Terrestr ial Radio Access Network

PSTN Public Switched Telephone Network

UE

PSTN ...

Core Network

Node B

UE

UE

UE

InternetX.25 ...

UTRAN External Networks

Iub

Node B

UE

UE

UE

UE

Iub

RNC

Circuit Switched

Domain

Packet Switched

Domain


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Motivation of UMTS Network Dimensioning

Dimensioning: determine appropriate bandwidths for transport links

maximizing utilization of transport resources

guarantee QoS (Quality of Service) requirements

The transport resource within the UTRAN is considerably costly

UTRAN Costly interface

Strict delay QoS

Costly interface

Strict delay QoS

Iub Interface

Dimensioning of Iubis important to design a high

cost- efficient UMTS network


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Goal of This Thesis

UMTS network is developing fast

Evolutions of UMTS

Radio Access Network (RAN) evolution: Rel99, HSDPA, HSUPA, HSPA+, LTE

Evolved UMTS terminals and emerging new services

Significant increase of the traffic volume

Remarkable changes in traffic pattern and characteristics

Transport Technologies for UTRAN, e.g. migration from ATM to IP

Quality of Service Schemes, e.g. QoS differentiation and prioritization

Goal of this Thesis

Investigate important aspects related to the Iub dimensioning

Develop dimensioning approaches for different UMTS Networks

simulation models

analytical models

Derive important dimensioning guidelines and rules

Goal of this Thesis

Investigate important aspects related to the Iub dimensioning

Develop dimensioning approaches for different UMTS Networks

simulation models

analytical models

Derive important dimensioning guidelines and rules


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Outline








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Objectives of UMTS Network Dimensioning

Network Costs: the costs correlated with the expenditures necessary forleasing transport link bandwidths

Quality of Service user-relevant QoS: refers to the QoS related to the individual users

Application delay or throughput, connection reject ratio due to admission

control function

network-relevant QoS: network-specific QoS to evaluate the quality of

a network, measured on the packet level

Packet delay, packet loss ratio

The goal of network dimensioning is to minimize costs while maximizing QoSThe goal of network dimensioning is to minimize costs while maximizing QoS


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Framework of UMTS Network Dimensioning

Bandwidth

QoS

AnalyticalApproach

Input

Traffic Demandtraffic classtraffic load

traffic distribution

QoS Targetsuser-relevant QoSnetwork-relevant QoS

Dimensioning

Process

Network

Configurations

network topology

traffic control functions

resource control functions

transport technology

QoS mechanisms

Output

Network Cost

minimum required linkcapacities (Mbit/s)

SimulationApproach


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Outline








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Simulation Models

Model a complete UMTS system following 3GPP specifications

Focused on a detailed modeling of the Iub interface (i.e. protocol stack,

transport network, resource and QoS management)

Modeling of air interface and core network are simplified

Reduce complexity and improve simulation efficiency

ATM TransportATM TransportIP Transport IP Transport


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Outline








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Services and QoS Measures

VoiceVideo

Conferencing Applications/Services

Circuit-Switched Traffic

Traffic Classes

Web FTP

Elastic Traffic

Real Time (RT)low delaylow loss

require Admission Control

Non Real Time (NRT)

carried by TCP/IPdelay tolerant

QoS Measures

at flow/call levelBlocking probability

(CAC reject ratio)

Application Throughput

(Application Delay)

Packet Delay

Packet Loss ratio

QoS Measures

at packet level

over the Iub

Packet Delay

Packet Loss ratio

Network-

relevant QoS

User-

relevant QoS


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Overview of Analytical Models

Queuing Models with non-

Markovian Arrival Process

Non-preemptive priority

queuing model

Modeling Packet Level

MMPP(2)/D/1

or BMAP/D/1

MMPP(2)/D/1 - Priority

or BMAP/D/1-Priority

Erlang Loss

Model

Processor

Sharing (PS)

Model

Processor

Sharing Model

+ Erlang ModelProposed

AnalyticalModels

Modeling Call or Flow Level

Erlang-B

MD Erlang-B

M/G/R-PS

queuing model

Traffic Policy

- BW sharing

- BW separation

Dimensioning Tool Analytical Models

User-Relevant QoS Network-Relevant QoS

Circuit-Switched

TrafficMixed TrafficElastic Traffic Elastic Traffic Mixed Traffic

Circuit-

switched traffic

blocking QoS application delay

or throughput

packet delay, packet loss ratio

over the Iub interface

both QoS need

to be met

Traffic

Scenario

QoS

Measure


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Outline





Dimensioning Models and Results Processor Sharing Model (Application Performance)

Packet level Queuing Model (Transport Network Performance)



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Processor Sharing (PS) Model for Elastic Traffic- for User-Relevant QoS (Application Performance)

Iub (C)

UE

UE

UE

UE

UE

NodeB RNC

R = C / rpeak

Radio Network Cont

Radio Access Bearer (RAB) rpeak

rpeak

rpeak

rpeak

rpeak

rpeak Iub (C)

UEUE

UEUE

UEUE

UEUE

UEUE

NodeB RNCRNC

R = C / rpeak

Radio Network Cont

Radio Access Bearer (RAB) rpeak

rpeak

rpeak

rpeak

rpeak

rpeak

Flow arrival follows

Poisson Process General file length

distribution

Assumptions

M/G/R-PS Model

K. Lindberger (1999)

Peak data rate

File length

{ } Rpeakpeak

RGM frx

RRRE

rxxTE =

+=

)1(),(1)( 2//

Link utilization Delay factor

Number of servers

R = C / rpeak

Expected Sojourn Time (average transfer delay)


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Proposed Extensions on M/G/R-PS Model

Case Extensions Analytical Realizations

2. Single RAB

With CAC

3. Multiple RABs

No CAC

General M/G/R-PS model - R is bearer specific - consider total traffic

i

ir

CR = =

bearers

i

{ } Rii

i

i

ii

i

iiRGM f

r

x

R

RRE

r

xxTE =

+=

)1(

),(1)( 2//

4. Rate Adaptation

- BRA j

K

j

javgpeak qrr ==1

_ avgpeakavg rCR _/=

Reuse single rate M/G/R-PSCalculate an average ratefrom different r

peakto derive R

1. Single RABNo CAC

Radjust

fRTTRTT =

{ } { } adjustRTTratiorttULxTExTE )__2()(*)( ++=

New parameterUL_rtt_ratio

Seven Extensions are proposed in this thesis to incorporate UMTS networks

RAB Radio Access Bearer CAC Call Admission Control


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Proposed Extensions on M/G/R-PS Model (cont)

5. Mixing with

CS Traffic

CSelasticIub LCC +=

M/G/R-PS

CSelasticIub CCC +=

M/G/R-PS Erlang

(a)

(b)

Case Extensions Analytical Realizations

7. IP DiffServ { } k

kpeak

k

kk

kkk

kpeak

kkRGM f

r

x

R

RRE

r

xxTE

_

2

_

//)1(

),(1)( =

+=

6. Multi-Iub RANC

bb

Node B

Node B

Node B

IP Router

Cac_1

RNC

Cac_n

Cac_2

Backbone Link

Last mile links


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IP-based UTRAN with DiffServ QoS Structure

EF Expedited Forwarding

AF Assured Forwarding

PHB Per Hop Behavior

UMTS Core

Network

UMTS Core

NetworkNode B RNC

SP Strict Priority

WFQ Weighted Fair Queuing

DiffServ Differentiated Services

Per Hop Behavior (PHB)


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Validation of Application Delay Estimation

BE

AF41

AF31

AF21

AF11

EF

EF

PHB

10NRT HSPA 2Mbps

50NRT RAB 384kbps

40NRT RAB 256kbps

30NRT RAB 128kbps

20NRT RAB 64kbps

RT video

RT voice

WFQ

weightService class

Single Link Scenario

The relative errors of obtained analytical results are within

the agreed level for network dimensioning of industry

The relative errors of obtained analytical results are within

the agreed level for network dimensioning of industry

0.5 0.6 0.7 0.8 0.9 10

2

4

6

8

10

12

Iub link utilization

AF11

app.

delay(s)

AF11 PHB - NRT RAB 64kbps

M/G/R/N-PS

Simulations

0.5 0.6 0.7 0.8 0.9 10

2

4

6

8

10

12


AF

41app.

delay(s)


M/G/R/N-PS

Simulations

0.5 0.6 0.7 0.8 0.9 10

2

4

6

8

10

12


AF21app.

delay(s)


M/G/R/N-PS

Simulations

0.5 0.6 0.7 0.8 0.9 10

2

4

6

8

10

12


BEapp.

de

lay

(s)

BE PHB HSPA

M/G/R/N-PS

Simulations


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Queuing Models for Network-Relevant QoS

Arrival process model (shall capture bursty and self-similarity of the aggregatedarrival traffic and Bulk Arrival of packets)

2-state Markov Modulated Poisson Process (MMPP) model, where the inter-arrival time distribution is based on 2-Phase Hyper-exponential distr ibution

Batch Markovian Arrival Process (BMAP)

TTI

TTI

TTI

AAL2

Queue

ATM

Queue

Deterministic

service rate

Deterministic

service rate

Link

DCH 1

DCH 2

DCH n

Segmentation

FP PDUs

RT or NRTArrivals

Server process(deterministic service rate)

Depatures

(a) Single-service system

DepartureRT

NRT

H

L

Packet scheduling:

Non-preemptive priority

Server process(deterministic service rate)

DepaturesArrivals

(b) Priority system

Departure

queuing delay

Delay distribution

0.99

30ms


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MMPP Model for Estimation of the Iub delay

Capture of the Characteristic of the Arrival Traffic

Traffic demand

Mean traffic Variance Correlation

Add network / protocol overhead

Measure arrival traffic

MMPP arrival process

model parameters

Capture the arrival traffic characteristics

MMPPD/1 queuing

MMPP/D/1 priority queuing

Queuing delay

distribution


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Validation of the Iub Delay Estimation

0 1000 2000 3000 40000

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

voice traffic demand [kbps]

re

quiredIubbandwid

th[kbps]

voice only scenario - Rel99 ATM-based Iub

system simulation

M/D/1

H2/D/1

MMPP/D/1

0 1000 2000 3000 40000

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

voice traffic demand [kbps]

relativeerroroftheanaly

ticalmodel

voice only scenario - Rel99 ATM-based Iub

M/D/1

H2/D/1

MMPP/D/1

Scenario I: 100% voice traffic (single Iub)Traffic model: Adaptive Multi Rate (AMR) 12.2kbps

Speech/silence period: exponential distribution, mean = 3 seconds

Call duration: exponential distribution, mean = 120 seconds

Dimension QoS target: 99% of packets experience less than 10ms Iub delay


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Validation of the Iub Delay Estimation

1000 2000 3000 4000 50001000

2000

3000

4000

5000

6000

7000

8000

UTRAN traffic demand [kbps]

req

uiredIubbandwidth[kbps]

packet switched traffic (BRA) only

System simulation

Queueing simulation (Opnet)

Analytical calculation

0 1000 2000 3000 4000 50000

1000

2000

3000

4000

5000

6000

7000

8000

UTRAN traffic demand [kbps]

req

uiredIubbandwidth[kbps]

packet switched traffic (BRA) with 10% voice

System simulation

Queueing simulation (Opnet)

Analytical calculation

Dimension QoS target:99% of voice packets experience less than 10ms Iub delay

99% of data packets experience less than 30ms Iub delay

Scenario III: 90% web traffic (low priority)

& 10% voice traffic (high priority)Scenario II: 100% web traffic


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Outline





Dimensioning Models and Results Conclusions and Outlook


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Conclusions and Outlook (cont)

Dimensioning and Comparing ofATM- and IP-based UTRAN Single Iub link scenario

Multi-Iub RAN scenario

Dimensioning HSPA traffic in ATM-based UTRAN

HSDPA

HSUPA

HSPA+Rel99 (Traffic Separation)

Further Work: Long Term Evolution (LTE)

Expect a much higher demand on transport bandwidth in access networks

Dimensioning for LTE transport access network

Investigating applicability of current dimensioning models

Extensions of analytical models are desired


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Thank for your Attention

umts ran dimensioning

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