a functional end-to-end qos architecture enabling radio ... · - iub interface fully supported over...

S&RM Cluster Meeting, October 3rd, 2006, Brussels

AROMAAdvanced Resource Management Solutions for Future All IP Heterogeneous

Mobile Radio Environments

AROMAAROMAAdvanced Resource Management Solutions for Future All IP Heterogeneous

Mobile Radio Environments

Dr. Ramon FERRÚS Universitat Politècnica de Catalunya (UPC)

January 2006-December 2007

IST-4-027567

A Functional End-to-End QoS Architecture Enabling Radio and IP

Transport Coordination

2


Academia• Universitat Politécnica de Catalunya (UPC) – Spain• King’s College London (KCL) – U.K.• Instituto Tecnico Superior- Technical University of

Lisboa (IST-TUL) - Portugal

Mobile Operators• Portugal Telecom Inovação (PTIN) – Portugal • Telecom Italia (TI)- Italy• Telefónica I+D (TID)- Spain• Telia–Sonera (TEL) - Sweden

Mobile Operator driven STREP project

Project AROMAConsortium

Project AROMAConsortium

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The AROMA project aims to devise and assess a set of specific strategies and algorithms for both the access and the core network parts that can guarantee the end-to-end QoS in the context of an all-IP heterogeneous radio access network

AROMA addresses in an integral way the end-to-end QoS provision in Mobile networks. In particular, AROMA focuses in both a Heterogeneous Access Networks and an IP-based core and access transport network.

AROMA contributes to the development of an efficient wireless access assuming IP based services.

The results coming from the AROMA project will provide a manufacturer-independent analysis of the End-to-end QoS strategies, which allow the mobile operators to evaluate and compare solutions coming from the market with an available reference of the system performance.

AROMA is the natural continuation of two legacy project ARROWS and EVEREST

Project AROMAMain ObjectivesProject AROMAMain Objectives

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S&RM ClusterProject AROMAS&RM ClusterProject AROMA

Scope and Approaches followed in Project AROMA

Techniques:

RRM (Radio Resource Management)CRRM (Common Radio Resource Management)CARM (Common Access Resource Management)Automatic Tuning

Framework:

Current RATs (UMTS, GERAN, WLAN..)Current spectrum allocationCurrent regulatory framework

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S&RM ClusterProject AROMAS&RM ClusterProject AROMA

Space ResolutionU

ser

Cel

lR

egio

nal

Time Resolutionµs ms s mn 10s mn ½ day day month

Short term Middle term Long term

Short

space

Middle

space

Large

space

Automatic tuning

RRMCRRMCARM

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AROMA reference architecture –Medium term scenario

RNC SGSNBSCMSC ServerGANC

PSTN/ISDN

CS-MGW GGSN

IMS ServicesExternal PDN

WLAN AP

Node-B BTS

IP-based transport backhaul IP-based transport core network

3GPP R6 network architectureMulti-mode terminals

Rad

io N

etw

ork

Laye

r (R

NL)

Tran

spot

Net

wor

k La

yer (

TNL)

Radio Access Network (IP-RAN) UMTS-based Core Network

Medium term scenario assumptions:- Backhaul already migrated to IP transport- Iub interface fully supported over IP transport

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AROMA reference architecture –Medium term key drivers

RNC SGSNBSCMSC ServerGANC

PSTN/ISDN

CS-MGW GGSN


WLAN APNode-B BTS

IP backhaul IP transport network

radi

o

IP transportIP transport IP transport

Access network e2e QoS

Key Drivers CRRMRadio and IP transport coordination

(GERAN and WLAN may share backhaul resources or not)

RRM RRM RRM

CRRM

RRM

Over-provisioning in the backhaul may not be economically feasible

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AROMA reference architecture –Long term scenario

aGW

PSTN/ISDN

MGW


eNB


MMEUPE

RRCBorder GW

Inter ASanchor

Aligned to 3GPP SAE/LTE

Long term scenario assumptions:- Aligned to TR 25.912- Iub interface no longer needed- High capillarity needs efficient resource management

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AROMA reference architecture – Long term key drivers

PSTN/ISDN

MGW


eNB


RRCBorder GW

radio

IP nativeIP transport/native?

Access network e2e QoS

RRM

Key DriversMulti-cell RRMIETF IP solutions for mobility and QoSRadio and IP transport coordination

aGW

MMEUPE

Inter ASanchor

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Proposed AROMA E2E QoS Framework

Proposed AROMA E2E QoS Framework

QoS Framework approach:⇒Functional Description in terms of required functions:

Admission, Congestion, etc

Other possible approaches:⇒Bearer Services and QoS Management functions in the

control and user plane (23.107 and 23.207 approach): BS Managers, Resource Managers, etc.. Structured approach but some QoS functions don’t fit in this model

⇒Protocols and protocol stack: Too implementation dependent

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RRM RAT n

MC

RPSLC

AC CC

BS

Radio Controller(RNC, BSC, GANC)

Base Station(NodeB, BTS, AP)

SGSN GGSNMobile Terminal

Radio Resources IP Transport Resources IP Transport Resources IP Transport Resources

TRM

R5/R6

CC

PSRC

BS

AC

RRM RAT2

MC

RPSLC

AC CC

BS

RRM RAT1

MC

RPSLC

AC CC

BS

CRRM RS

AROMA reference architecture –RRM and TRM QoS functions

CRRM:- RAT Selection (RS)

RRM and TRM:- Admission Control (AC)- Congestion Control (CC)- Bearer Selection (BS)

RRM:- Mobility Control (MC)- Radio Link Control (LC)- Radio Packet Scheduling (RPS)

TRM:- TNL Route Control (RC)- TNL Packet Scheduling (PS)

Refs.:- Everest White Paper - TEQUILA project- TR 25.912- TS 23.107- TS 23.207

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AROMA reference architecture –CARM QoS functions

RRM RAT n

RPSLC

RRM RAT 2

RPSLC

Radio Controller(RNC, BSC, GANC)

Base Station(NodeB, BTS, AP) SGSN GGSN

Mobile Terminal

Radio Resources IP Transport Resources IP Transport Resources IP Transport Resources

TRM

PS

RRM RAT 1

RPSLC RCMC

CC

AC

BS

CRRM RS

Coordinated Access Resource Management

(CARM) functions

The 3GPP approach is to separate the QoS management at RNL from the QoS management at TNLNo standard mechanisms for QoS management at TNL will be defined

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BearerSelection

Radio PacketScheduling

Congestion Control

Link Control

RRM functions TRM functions

TNL PacketScheduling

RouteControl

AdmissionControl

MobilityControl

CARM functions

RAT Selection

AROMA ref. architecture –Proposed CARM QoS functions

Goals:⇒ Resource optimisation (RNL and TNL)⇒ Business strategies (e.g. business users vs. consumer users)

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aGWeNBMobile Terminal

Radio Resources IP Transport Resources

TRM

LTE

PSRC

RRM RAT n

RPSLC

RRM RAT 2

RPSLC

RRM RAT 1

RPSLC

CRRM

CARM

MC

CC

AC

BS

RS

Coordinated Access Resource Management

(CARM) functions

AROMA reference architecture –CARM QoS functions in LTE

In a LTE scenario the core IP transport network and the access IP transport network are expected to mergeThen QoS management entities at the core and access network could also merge together

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Degree of couplingDegree of couplingWe can envisage the definition of a standard interface between the RNL and TNL QoS management entities. It should be flexible enough to allow different degrees of coupling between RNL and TNL management

Radio AdmissionControl

TNL AdmissionControl

Radio Bearer Admission Request

Success/Reject

TNL Bearer Admission Request

Radio AdmissionControl

TNL AdmissionControl

Radio Bearer Admission Request

Prioritization of the proposed cells in which the connection can be admitted according to TNL status

TNL Bearer Admission Request (List of potential cells)

RNL TNLInterface

Basic Coordinated Admission Control

Coordinated Admission Control with cell prioritization

Degree of coupling

+

-

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Work in progress & Future work

QoS architecture implementation aspects⇒Analyse potential implementation approaches of the CARM

framework (e.g. centralised approaches based on the BB concept for the Diffserv IP transport network, MPLS, etc.)

Definition and evaluation of CARM algorithms⇒Work is in progress for the definition and evaluation of

coordinated admission and congestion control algorithms based on:

• Metrics definition for the estimation of resource occupancy on the transport layer.

• These metrics are incorporated in the admission and congestion functions of the radio layer (e.g. DCH rate selectionfor PS services)

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Transport Congestion ResolutionMechanisms based on RRM within the RNL:

•Bit rate reduction for non-guarateed PS services•Redistribute traffic via HO and network controlledcell reselection (intra/inter RAT)•Reduce soft HO connections•Flow control for High Speed channels•Increase admission blocking•Drop active sessions

Tranport Network CongestionResolution Mechanisms within the TNL itself:

•Packet Discarding policies (blind/selective)•Path re-calculation (routing control)

How TNL congestioncan be preventedand/orsolved?

Where TNL congestion oroverloadsituations can be detected?

Transport Congestion/Overload DetectionMechanisms in the radio layer

Transport Congestion/Overload DetectionMechanisms in the transport layer

Coordinated Congestion Control approachpure RNLapproach

pure TNL approach

Transport Congestion ResolutionMechanisms based on RRM within the RNL:

•Bit rate reduction for non-guarateed PS services•Redistribute traffic via HO and network controlledcell reselection (intra/inter RAT)•Reduce soft HO connections•Flow control for High Speed channels•Increase admission blocking•Drop active sessions

Tranport Network CongestionResolution Mechanisms within the TNL itself:

•Packet Discarding policies (blind/selective)•Path re-calculation (routing control)

How TNL congestioncan be preventedand/orsolved?

Where TNL congestion oroverloadsituations can be detected?

Transport Congestion/Overload DetectionMechanisms in the radio layer

Transport Congestion/Overload DetectionMechanisms in the transport layer

Coordinated Congestion Control approachpure RNLapproach

pure TNL approach

Cover those situations where: (1) pure-TNL mechanisms do not suffice to alleviate a given congestion situation and consequently the RNL

should be involved in congestion handling, and (2) useful metrics to characterise overload/congestion situations are computed in the TNL itself and notified to the

RNL, instead of letting the RNL layer to detect congestion by itself, so that the reaction of the RNL can be better directed to the location and adjusted to the severity of the overload situation.

Exemple: Coordinated Congestion Control

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IP Transport Network

RNCn

RNCm

NodeBi

NodeBj

NodeBk

TNL Monitoring

Measurements

Congestion metrics

CoordinatedCongestionResolutionmechanims

li

lj


A bottleneck link in the transportnetwork is considered

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a) Mean LU (%)

50

55

60

65

70

75

80

85

90

95

0.4 0.5 0.6 0.7

Normalised Goodput

DCH64DCH128DCH256

b) Prob (LU>0.95) (%)

0

10

20

30

40

50

60

70

0.4 0.5 0.6 0.7Normalised Goodput

DCH64DCH128DCH256

c) FP PDU Loss Ratio (%)

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5


DCH64DCH128DCH256

Potential Congestion Control Gain


Effect of the DCH bit rate selection in the LU indicator and potential coordinated congestion control gain.

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a) Mean LU (%)

50

5560

6570

75

8085

9095

100


Rep_Range=10dBRep_Range=0dB

b) FP PDU Loss Ratio (%)

00.5

11.5

22.5

33.5

4

4.55

0.4 0.45 0.5 0.55 0.6Normalised Goodput

Rep_Range=10dBRep_Range=0dB

Potential Congestion Control Gain

Effect of the reporting range value in the LU indicator and potential coordinated congestion control gain.


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Coordinator contact detailsDr. Fernando Casadevall Universitat Politècnica de CatalunyaCampus Nord UPC-Edifici D4Jordi Girona 1-308034-Barcelona (Spain)e-mail: [email protected]

AROMA WEB sitehttp://www.aroma-ist.upc.edu

Thanks for your attention….

AROMA Contact

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