radio resource management approach in everestwwi-mocca workshop - yokosuka, march 30th 2006 everest...

WWI-MOCCA Workshop - Yokosuka, March 30th 2006EVERESTEVEREST

1EVERESTEVEREST

Radio Resource Management Radio Resource Management approach in EVERESTapproach in EVEREST

Presented byPresented by

OriolOriol SallentSallentUniversitatUniversitat PolitPolitèècnicacnica de de CatalunyaCatalunya


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Outline

EVEREST consortium

EVEREST

ObjectivesReference architectureScenariosRRM studies (UTRAN, GERAN, WLAN)CRRM approach and some solutionsTestbed


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EVEREST Project

The Strategic Objective 'Mobile and Wireless Systems and PlatformsBeyond 3G' is included within IST priorities in 6th FrameworkProgramme

Project duration: January 2004-December 2005

Project cost: 2.75 M€

Project funding: 1.6 M€


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EVEREST Consortium

• TeliaSonera AB (Sweden)

• Telefónica I+D (Spain)

• Telecom Italia Lab (Italy)

• Portugal Telecom Inovação (Portugal)

• King’s College London (UK)

• Universitat Politécnica de Catalunya(Spain)


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EVEREST Objectives

• To devise and assess a set of specific strategies and algorithms for access and core networks, leading to an optimized utilization ofscarcely available radio resources for the support of mixed services within heterogeneous networks beyond 3G.

• To achieve the above objectives two parallel methodologies have been followed:

• Algorithm development, evaluation and validation via simulation

• Technology demonstration via a real time Testbed


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EVEREST - RRM Objectives

• To develop advanced RRM strategies and algorithms in the context of 3G and Beyond systems, ensuring the QoS requirements of the proposed services, providing the planned coverage and increasing capacity. In particular, algorithms will target:

Individual RRM for different RANs

CRRM for heterogeneous RANs

• To assess and evaluate the proposed algorithms in a number of relevant scenarios, technological functionalities, network layout structures, services mix, etc. with the idea to cover medium- and long-term foreseen evolutions


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WQB BB

MPDF

Policy-based QoS Management

Policy Repository

ExternalDomains SLS NegotiationSession

Establishment

ServiceSupportDomain

(e.g. IMS)

UE

ResourceActivation(ie. PDP Contextsignalling)

End-to-End Session Establishment Signalling (e.g. SIP/SDP)

RNCRAN (UTRAN)

RAN(GERAN)

RAN (TightCoupled WLAN)

Diffserv IP CoreNetwork

IuGTP Micromobility

Iu or GbBSC

APC

SGSN

SGSN

GGSN

Iu or Gb

ExternalQoS Domain

EVEREST – QoS architecture


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• Five selected target scenarios• Two theoretical: Hot Spot within urban area & along suburban main road

• Three realistic: urban/suburban, dense urban area & multifloor

• Scenario description items• Network architecture and entities • Services mix and traffic load• Environment; suburban, urban and indoor• Radio access technologies and capabilities

Scenarios

GSM / GPRSUMTS UMTS UMTS

WLAN


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Business

53%

11%

5%

9%

12%

4% 6%

VoiceVideotelephonyVideo streamingWeb browsingEmailMMSFTP

Consumer

55%

9%

7%

11%

6%

8% 4%

Service UL kbytes/user/BH DL kbytes/user/BH Voice 75 75 Video Streaming 5 113 Video Telephony 53 53 Web Browsing 60 312 Email 88 328

The scenario vision encompasses the heterogeneous network supporting users with multimode mobile terminals in the time frame of 2009-2010

Scenarios


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When an asymmetric service like the RAB 64/384 kb/s is considered, it is found that:• For p=0 (i.e. all users are outdoor) system capacity is clearly downlink limited due to the high service asymmetry. • However, for p=0.5 the system becomes uplink limited.

25.0%15.3%88.4%P=0.5

18.8%11.6%37.7%P=0.2

12.5%9.3%19.2%P=0.1

DL384 Kb/s

DL64 Kb/s

UL 64 Kb/s

Capacity loss (%) relative to the case with no indoor traffic (p=0) for 64/64 kb/s and 64/384 kb/s radio bearer:

This finding has inspirede.g. CRRM algorithms

UTRAN - Indoor traffic

RRM strategies between outdoor macrocells and indoor microcellshave also been tested


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• Indoor hotspot scenario• A three sector site for frequency f2

is used together with a macro layer of cells of frequency f1.

UTRAN - Multiple RF carriers

Objective: Find strategies that• Reduce

– blocking – dropping

• Increase – throughput

Compared to the Reference strategy: 50% of Voice and HTTP load on f1, 50% of Voice and HTTP load on f2.

Reference strategy

Load on f1Load on f2

Frequency f2 simulated cells

Frequency f1 simulated cells

Frequency f1 interferencegeneratingneighbour cells


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The study aims to analyze the system behavior with different settings of the Qoffset threshold that applies to the ranking of neighbour cells when the terminal is performing cell-reselection, taking into account its high/low mobility status.

Rn = Qmeas,n - Qoffsets,n - TOn * (1 – Ln)

R criterion for ranking:

High/low mobility status evaluation:

Micro Micro Micro

Macro layer Macro layer

Micro Micro

During TCRmaxNumber of Cell-reselections <= NCR

TCRmax = 60 secNCR = 21 Cell-relesection

in 60 sec

Micro Micro Micro

Macro layer Macro layer

Micro Micro

During TCRmaxNumber of Cell-reselections > NCR

TCRmax = 60 secNCR = 23 Cell-relesections

in 60 sec

High-mobility state

Qoffset RQoffset R

UTRAN - HCS & Mobility issues


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• The Transport Channel Type Switching (TCTS) procedure is a RRC procedure• When the traffic is high a dedicated channel is to be used, whereas for small traffic values a shared channel is adopted

UTRAN - TCTS

3.82%

0

0.00%

1.00%

2.00%

3.00%

4.00%

DCH-only TCTS

Percentage of RAB setup requests blocked due to lack of DL codes

• UTRAN capacity is higher when TCTS is active

•


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DiffServ aware RRM

Goal: Support DiffServ traffic in an efficient way over the air-interface

Main idea: To be consistent with DiffServ traffic marking according to traffic conformity

Queuing (prioritise according to color, green>yellow>red)SchedullingRRInterference-based Queue

The conforming traffic in DiffServ is given higher priority in the resource allocation over the air interface


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Three priority algorithms compared with Max CI

• Priority1=F(PacketTime-out, reliability requirements, #attempTx)

• Priority2=F(QueueAvrgTime-out, reliability requirements, #attempTx)

• Priority3=F(QueueLength, reliability requirements, #attempTx)

))(#)()(,(Priority 3211 attempTxWOutpacketTimeWSIRCQIW +=

))(#)()(,(Priority 3212 attempTxWimeOutqueueAvrgTWSIRCQIW +=

))(#)()(,(Priority 3213 attempTxWqueueSizeWSIRCQIW +=

HSDPA – Advanced schedulers

"Examples of RRM strategies for HSDPA (CR to 25.922)”, tdoc: R2-060302, Source: Telecom Italia, TeliaSonera, 3GPP RAN WG2 meeting 51, Denver (USA), 13-17 February 2006

’QoS-aware’ HSDPA packed scheduling algorithms for real-time services proposed as reference of algos exploiting QoS parameters


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• To identify main radio resource management mechanisms offered byGPRS/EGPRS to support the video streaming service:– procedures related to QoS handling and channel administration for the

services belonging to the STREAMING CLASS;– standard features and parameters affecting QoS of video streaming

• Performances investigation of some specific mechanisms able to maximize the quality perceived by the video streaming end-user (client-side pre-bufferization, header compression)

Video streaming over GPRS

e.g.5 second of buffering time is a safe value for codec bitratesless than 32 kbps


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WLAN – Admission control

Admission Control algorithm for WLAN 802.11b/a/g BSS based on a “Capacity Region” derived from an analytical model

Offered throughput per user doesn’tfulfil QoS constraint in UL or DL for at least one class of user

Offered throughput per user fulfils the QoS constraint in UL and DL for all classes of user

WLAN exploited to offer :- Video telephony (CONVERSATIONAL, UL:64/DL:64 kbps)- Video streaming Business users (STREAMING, UL:16/DL:128 kbps)- Video streaming Consumer users (STREAMING, UL:16/DL:64 kbps)

• Validation of the analytical model by means of simulations • Evaluation of the effect of the different factors not considered or only approximated in the analytical model (e.g. AckTimeout, the EIFS interval, etc.)


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CRRM – Functional model

The functional model assumed in 3GPP for CRRM operation:

The interactions between RRM and CRRM entities involve two types of functions:a) Information reporting function- Dynamic (e.g. cell load, transmitted carrier power, interference measurements, etc.)-Static (e.g. cell relations in HCS layers, cell capabilities and configuration)

b) RRM decision support functionCRRM simply advises the RRM entity (i.e. RRM remains as the master of the decisions) or CRRM is the master, so that its decisions are binding for the RRM entity.

CRRM entity

CRRM entity

RRM entity

RRM entity

RRM entity

RRM entity

- Information reporting

- Information reporting - RRM decision support

- Information reporting - RRM decision support


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RRM functionalities in a single-RAT context:• Admission control• Congestion control• Horizontal (intra-system) handover• Packet scheduling• Power control

When these functionalities are coordinated between different RATs in a heterogeneous scenario, they can be denoted as “common”

In an heterogeneous scenario a new functionality arises: RAT selection

CRRM – Functionalities & split

There exist a range of possibilities for the set of functionalities that the CRRM entity may undertake

The CRRM entity may be implemented either into existing nodes (i.e. RNC, BSC and APC) or in a separate node


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RAT selection

Some possible guiding principles for RAT selection are:

Sevice-based RAT selection. A service-based RAT selection policy is based on a direct mapping between services and a prioritised list of preferred RATs.

Load-balancing RAT selection. This policy will distribute the load among all resources as evenly as possible.

Interference-based RAT selection. This principle intends to anticipate the effects that the allocation of a certain connection request to a certain cell and RAT will cause in terms of interference. Then, different criteria could be used for the RAT selection so that the interference tends to be minimised.

An advanced RAT selection algorithm may integrate several of the above principles.

It is prime important to devise the role of the above principles, which of them has a predominant effect, which are the aspects related to the scenario, services, service mix and RATs characteristics influencing the relative importance, etc.


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0

1

2

3

4

5

6

7

8

9

10

0 200 400 600 800 1000

Voice users

Dro

ppin

g pr

obab

ility

(%)

Random policy

Indoor policy

High path loss traffic is allocated to GERAN

Better utilisation of the radioresources

RAT selection – Interference considerations


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UTRAN GERAN WLAN

Conversational – Business

Conversational – ConsumerInteractive – Business

Interactive – Consumer

Extension to: Indoor/outdoor, Pedestrian/car, etc.

RAT selection – Load balancing


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RAT selection – Examplen-complex policy

VHO PROCEDURE

LUTRAN>Lth+∆ for Mup consecutive

samples

Y

N

User in UTRAN

Y

N

VHO to GERAN

Do NOTHING

Y

Y

VHO to UTRAN

N

Voice

Y

N

Y

N

Interactive

RAT SELECTION

Start of session

LUTRAN>LthY N

Capacity available in

UTRAN

N

Y Y

N N

N

YY

ACCEPT IN GERAN

ACCEPT IN UTRAN

Service

Voice

Interactive

BLOCK CALL

INITIAL RAT SELECTION

Y N


GERAN


GERAN


UTRANCapacity

available in GERAN


UTRAN

Service

LUTRAN<Lth-∆ for Mdown consecutive

samples

User in UTRAN


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The proposed algorithm combines:

• Service principle (preference of UTRAN for interactive traffic)• Interference principle (tends to avoid at the possible extent to assign high path

loss users to WCDMA RAT)• Load balancing principle (setting of the path loss threshold Lth as a certain

percentile of the statistical path loss distribution)


0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

90 95 100 105 110 115 120 125 130 135 140

L (dB)

CD

F

PLth=125 dB(80-th perc)

PLth=120 dB(60-th perc)PLth=115 dB

(40-th perc)

Key single parameter: Lth


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Throughput gain up to 25%are observed with theproposed algorithm

1.5

2

2.5

3

3.5

4

4.5

5

400 500 600 700 800 900 1000 1100 1200

Voice Users

DL

Thro

ughp

ut (M

b/s)

EVEREST

Load Balancing

Optimisation throughsuitable Lth setting

With different dominant principles

Downlink throughputVoice-only scenario Lth=120 dB


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CRRM allocation

Connection establishment

Transport channel setup

Data transmission (TCP)

CRRM re-allocation

RAT specific simulations

CRRM – Perceived TCP throughput

CRRM throughput with and without HSDPA

0,00

0,20

0,40

0,60

0,80

1,00

1,20

1,40

1,60

1,80

alg 1w.o.

HSDPA

alg 1 w.HSDPA

alg 2w.o

HSDPA

alg 2 w.HSDPA

alg 3w.o

HSDPA

alg 3 w.HSDPA

alg 4w.o

HSDPA

alg 4 w.HSDPA

Rel

ativ

e C

RRM

thro

ughp

ut

WLAN throughput 3G throughput 2G throughput

The relative CRRM throughput gain usingsome proposed algorithms is 30-40%.

With HSDPA, the gain compared to RAT selection in a non HSDPA case is more than 60%.

27WWI-MOCCA Workshop - Yokosuka, March 30th 2006EVERESTEVEREST

27EVERESTEVEREST

0

5

10

15

20

25

30

35

100 75 50 25Multi-mode Terminal Availability (%)

Thro

ughp

ut D

egra

datio

n (%

)

VU=600;WU=600

VU=400;WU=400

VU=200;WU=200

UL Throughput degradation

• Increases degradation with

decrease of multi-mode availability

• Impact on the interactive users

exhibiting higher delays

CRRM – Multimode terminals

Proposed solution: Average Packet Delay improvement with dedicated slots(i.e. some reserved resources for single-mode terminals)

Study provides insight into evolutionary paths (e.g. suitability to subsidizemulti-mode terminals to exploit CRRM gain depending on load levels)


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EVEREST TestbedFlexible HW/SW platform functionalities:

• To test E2E QoS mechanism• To evaluate the associated signalling mechanisms • To assume different scenarios • To evaluate the user perceived QoS

Testbed configuration including: • Realistic scenarios for Heterogeneous Radio Access Network environment.

Three different RATs (UTRA, GERAN, WLAN).• Diffserv enabled Core Network.• Definition of new QoS Policies. • UUT running standard IP applications: Conversational services (VIC and RAT); Streaming (Darwin,

Mpeg4ip); Interactive (Mozilla, Apache Web server) and Background (Mozilla/Qmail)

Integrated Testbed Managers and Tools• Communications Manager Abstraction Layer: Software Integration and synchronisation.• Advanced Graphical Management Tool (AGMT): Centralised control of the complete testbed• Remote Testbed management: Test remotely located applications.


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Testbed - Architecture


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Configuration Files

•Scenario Layout•Propagation matrixes•BLER Tables

EVEREST Testbed

AGMT •Configuration Parameters(users, services, algorithms)

Testbed - Configuration


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AGMTStatisticsTool(real-timeand off-line processing)

Execution oflegacy applications

EVEREST Testbed

Testbed - Results


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A wide range of studies in the field of RRM/CRRM strategies have been developed in EVEREST

Special emphasis has been placed on RRM for UMTSFurther focus has been placed on CRRM

A QoS architecture has been proposed and developed

Novel and advanced algorithms, guidelines on key parameter setting and identification of major drivers and radio resource management principles are some relevant outputs

Obtained results are claimed to provide valuable inputs for B3G deployment, operation and optimisation

A real time testbed has been developed

Openness of all these RRM/CRRM studies provide public references on strategies, approaches, expected performance gains, etc.

EVEREST - Summary


33EVERESTEVEREST

AROMA – Follow-up project

To propose simulate, assess and validate innovative end-to-end QoS strategiesconsidering both radio and core network aspects under a variety of conditions.

To identify, propose, simulate, assess and validate advanced CRRM/RRM algorithms, covering among other:

RRM solutions for both HSUPA and HSDPA as well as the suitability of MBMS on dedicated channels and broadcast channels CRRM algorithms exploiting the non-homogeneous system conditions as well as CRRM algorithms and Cross layer RRM algorithms based in IP-RAN.

To develop mechanisms allowing an automated tuning of the CRRM/RRM algorithms and corresponding parameters via network management software

To carry out economic evaluation on the impacts of the novel solutions considered by the project.

Potential economic advantages of using specific RRM/CRRM algorithms addressed by AROMA Potential economic advantages to migrate and converge towards the all-IP architecture


34EVERESTEVEREST

More information: http://www.everest-ist.upc.es/

More information: http://www.aroma-ist.upc.edu/

Thank you !EVERESTEVEREST

AROMA

AROMA

radio resource management approach in everestwwi-mocca workshop - yokosuka, march 30th 2006 everest...

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