__cellular network ion based on mobile location cello)

8/2/2019 __Cellular Network ion Based on Mobile Location Cello)

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8.3.2004 1

Cellular network optimisation

based on mobile locationIST-CELLO

Workshop - Location-based Technologies, Services andApplications,

Brussels, 8 March, 2004

Jaakko Lhteenmki

[email protected]

Technical Research Centre of Finland (VTT)

Information Technologywww.vtt.fi/tte

8.3.2004 2

OUTLINE

Overall project description

Trial on Location-aided planning and AdaptiveCoverage

Trial and simulations of Location-aided handover

Follow-on project plans

Conclusions


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Page 2

8.3.2004 3

Overall project description

8.3.2004 4

Project partners

Cosmote Mobile

Telecommunications S.A., Greece

Institute ofCommunications and

Computer Systems

(ICCS-NTUA), Greece

Elisa CommunicationsCorporation,

Finland

VTT Information

Technology, Finland

Project co-ordinator

Motorola S.p.A, ItalyMotorola Ltd., UK (sub.contr.)

Teleplan AS, Norway

Center forPersonKommunikation

(CPK), Denmark


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8.3.2004 5

Main objective

Enhance performance of

mobile systems by using

mobile location techniques

8.3.2004 6

Technical objectives

Improve network planning and monitoring

Increase capacity and quality of service by

intelligent base station antennas

Optimise handover performance

Enhance mobility management in multi-system

environment


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8.3.2004 7

OMC

Location

server

Basis: retrieving location-relatedinformation from user terminals

BS

BS

BS

BS

BS

BS

BS

x,yuser #1 x, y, RXLEV, ...

user #2 x, y, RXLEV, ...



.... .... ....

Mobile network

operator

MSC

Location-

capable

terminal

MGIS database

Flow of measurement reports from terminal to

database

BSC/RNC

8.3.2004 8

How MGIS data is used?

Adaptive Coverage System

Location-aided network

planning

Location-aided handover

Location-aided mobility

managementMobile Network

Geographic Information

System (MGIS)

Access to location-

related performance and

coverage data





.... .... ....

CELLO Applications

Location

serverOMC


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Page 5

8.3.2004 9

Location-aided network planning (LAP)

BS

MGIS

ASTRIX

Planningtool

Monitoring and planning of mobilenetwork based on location-relateddata:

Coverage verification with live data

Detecting problematic areas

Propagation model tuning

Adaptive coverage planning

terminal-

level data

OMC

cell-level

data

8.3.2004 10

Adaptive coverage system (ACS)

BS

BS

Adaptive coverage for

temporarily varying traffic

demand

Realised by switched or

steered antenna patterns

Application examples:

- sports events

- rush hours

- exhibitions

...

Intelligent basestation antennaswith variable antenna pattern


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8.3.2004 11

Location-aided handover (LAH)

Intelligent handoverdecisions based onmobile location anddirection of motion

Avoid ping-pongeffects and unneces-sary handovers

Optimum neighbourplanning

Pre-emptive handoverfor reserving resourcesfor wideband services

BS

BS

BS

optimumtarget cellserving cell

candidatetarget cell

8.3.2004 12

Location-aided mobility management(LAM)

Inter-system handover toother cellular networksand wireless LANs

Informing the user ofnearby access pointsoffering wideband service

Expected results:

Improvement of QoSoffered to the user

Improvement of differrentnetworks load

Signalling of differentnetworks decreased

BS

INDOOR

WLAN

ACCESSPOINT

potential

handover to

wideband

service


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8.3.2004 13

Time schedule

WP1: Management

WP2: System design

WP8: Standardisation

and support to policy

WP3: Location-aided

network planning

WP6: Integration and

trials

WP4: Adaptive

coverage system

WP5: Location-aided

handover and mobility

WP7: Dissemination

and exploitation

2001

1 2 3 4 5 6 7 8 9 10 11 12

2002

1 2 3 4 5 6 7 8 9 10 11 12

2003

phase I phase II phase III

pre-study & specifications technical development trials & simulations

Trial1

M8

Work-

shop

M4

M9

M7

M3

M6

M5

M2

M1

Work-

shop

Work-

shop

M12

M11

Trial2

prelim. std.

contrib.

M10

1 2 3 4 5 6 7 8 9 10 11 12

8.3.2004 14

Implementation of data collectionto MGIS


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8.3.2004 15

Three approaches for accessing terminal levelperformance data and location:

BSC

AMU L-MGIS

NMDI

Abis

BTS

RNC

IMU

NMDI

Iub

Node B

core network

L-MGIS

Iu

A,Gb

GSM-UMTS network

L-MGISOMC

LS

LS

AP L-MGIS

WLAN network

WMU

NMDI

LS

Abis/Iub -monitoring

- distributed monitoring units(IMU/AMU/WMU)

and location servers

- DCM algorithm for location

Terminal application- location, e.g. by GPS

- data transmitted by

GPRS to MGIS

Network query

- O&M protocols used for

phone measurement data- SMLC used for location

SMLC

SMLC = Serving Mobile Location

Center (standard network element)

LS = Location Server (dedicated)

AMU = Abis monitoring unit

IMU = Iub monitoring unit

WMU = WLAN monitoring unit

8.3.2004 16

Network query approach increases signalling andSMLC load

Terminal application requires specific transmissions(e.g. GPRS) and users terminal resources--> suitable approach for limited groups (e.g.operators own employees

Abis/Iub monitoring enables data extraction without

loading the network distributed functionality --> low-cost LS+monitoring unit needed

computationally efficient location algorithm needed

possibly a specific computer board for location computations

Terminal level data and locationaccess


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8.3.2004 17

Trial approach

8.3.2004 18

d1

d2

d3

Global Positioning System (GPS)

Benefon Esc! phone used

Signal Level Algorithm (SLA)

Location algorithm by Elisa

Database Correlation Method(DCM)

Location algorithm by VTT

Location techniques in trials


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8.3.2004 19

Trials for LAP & ACS

Measurement

reports by

SMS

BS

BS

BS

Trial 1: Linnanmki(amusement park, Helsinki)

DAM

algorithm

MGIS

ASTRIXMGIS

Trial 2: Linnanmki

Switched commercial antennas Pre-planned network plan schedule

GSM1800 network of Elisa

Communications

Phase steered Modular Antenna Array (MAA) DAM algorithm for automatic coverage control

GSM1800 network of Elisa Communications

DAM =

Data analyser module

8.3.2004 20

Simulators and trials for LAH&LAM

Trial 2:

IP-level LAH

InputData

Configuration

User

distribution

Location

Server

UMTSAdmission

Control

StatisticalAnalysis

GSM/GPRS

AdmissionControl

WLANAdmission

Control

MGISdata

MobilityModelTraffic Model

SlowFading

MMCF

RXLEV

distribution

LAH simulators (cellular handover)GSM/GPRS & UMTS

LAM simulator (inter-system handover:GSM/GPRS & UMTS & WLAN )

handover

algorithms


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8.3.2004 21

LAP & ACS Trials

8.3.2004 22

Trial objectives Development of the prototypes

MGIS (VTT)

ACS antennas (CPK, NTUA)

antenna control system (CPK, NTUA, VTT)

location-aided planning components (Teleplan)

Demonstrate and evaluate the concept feasibility

concept of collecting information from mobile terminals(probing)

antenna control planning & monitoring results accuracy


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8.3.2004 23

OMC

DB

(Oracle)

ASTRIX

planning tool

MGIS

- MGIS database

- Post-processing

- Location Server

- MGIS administration

- Adaptive coverage

control software

Measurement

reports by

SMS

BS

ACS Antenna

control by

GSM-data

DB

(Oracle)

- maps- ASTRIX database

CELLO control center hosted by Elisa Communications

BS

BS

Fieldmeasurements

Trial area

Measurement reports

BSC

Abis-

analyserMGIS

Trial set up

8.3.2004 24

Mobile Network GeographicalInformation System (MGIS)

INTERNET

DB

MGIS SERVER

LOCATION-AIDED

PLANNING TOOL

ASTRIX

MGIS

DB

LOCATION SERVERS

DCM ELISA

Location

file

OMC file

- TEMS

- NPSi

MEASUREMENT

TOOLS

Measure-

mentfile

TEST

APPL.

Direct

database

access

MGIS

VISUALISATION

TOOL (MVT)

(IND)

ADMIN. &

TOOLSAPPLICAT

IONS

HTTP

Direct

database

access

OPERATIONS AND

MAINTENANCE

CENTRE

(OMC)

GSM modem

ADAPTIVE

COVERAGE

ANTENNAS DAM & ECM

ALGORITHMS


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8.3.2004 25

Trial environment: Linnanmki amusement park

Sight from Case A base stationtowards Linnanmki

Three base station sites for testing

8.3.2004 26

Antenna systemcontrol

- ACS control

software

RF Switch

GSM data

Antenna

moduleAntenna switching

commands

according to network

plan schedule

Microcontroller

GSM modem

Antenna(s)

basestation

TX/RX RX

switch-box

network plan

scheduleMGIS

database


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8.3.2004 27

Trial results

8.3.2004 28

Assesment of location techniques

Method r.m.s.

GPS 7.6

DCM 73.9

SLA 366.2

Cell Id 461.0

0 5 10 15 20 25 30 35 40 45 500

100

200

300

400

500

600

700

800

900

1000

GPS

DCMSLA

Cell ID

Distance[m]

Points

0 200 400 600 800 1000 1200 1400 1600 18000

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

GPS

DCM

SLA

CellID

SLA

DCMCell Id

GPS

Location error [m]

Probability


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8.3.2004 29

Effect of location accuracy on tuning

- Good fit for TEMS, GPS, DCM data

- Unacceptable fit for SLA data

Data based on DCM location method feasible for tuning

Propagation model tuning results

Mean(dB)

StdDev(dB)

RMS(dB)

Judgement

>1 >~10 >~10 Poor


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8.3.2004 31

Measurement-based coverageprediction

Error Correction Method

Aim:

Improve propagation model predictions by insertingmeasured and interpolated signal level values inthe predicted coverage area matrices.

How:

Surface fitting techniques are used to interpolatesignal level values

Three different surface fitting techniques wereimplemented: MLS, Delaunay triangulation andAveraging.

Why:

Enable more reliable network planning.

Predict coverage areas even without an expensive

network-planning tool and digital map

coverage

grid measurement

samples

8.3.2004 32

Coverage estimate based oninterpolation of measurement data

0 20 40 60 80 100 120 140 160 180 20010

20

30

40

50

60

70Signal Strength with ECM

Sample number

RxLev

Predicted

Measured

Typical performance of Error CorrectionMethod (ECM)

- r.m.s. error 5.0 dB

Overall performance: 3-13 dB- large errors when ECM tuning points are

far away (>200 metres)


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8.3.2004 33

Automatic reallocation of capacity

DATA ANALYSER MODULE (DAM) Analyses network performance data to detectcapacity problems

OMC data

Measurement samples (directly from terminals)

Locates the problem area

At cell precision by using OMC data

Within the cell by using terminal level measurements

Defines changes to the network configuration

Selects the optimal network plan (cell&antennaconfigurations)

Checks the load of the cells ensuring sufficient servicequality in other areas

Result: A schedule of network plans to be used in antennapattern control

Example of optionalantenna lobes

8.3.2004 34

DAM: Tracking of moving hotspot

Example:

Samples from one measurementshown as white dots

Yellow circle shows the averagelocation of the samples during thelast 3 minutes = hot-spot

DAM has selected an optimalnetwork plan

The coverage area of one cell isshown

1/4


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8.3.2004 35

2/4


Example:





8.3.2004 36

3/4


Example:






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8.3.2004 37

4/4


Example:





8.3.2004 38

Data Analyser Module results

DAM is capable of carrying out the analysis of networkperformance data and creating a network plan schedule

ACS can be effectively used for running the schedule

Example of capacity enhancement with three MAA antennas


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8.3.2004 39

Roadmapfor

LAP&ACSEvaluation of predicted

coverage with MGIS data

Semi-automatic tuning of

models based on MGIS

Continuous, automatic

tuning of models

Measurement-based

coverage prediction

Automatic reallocation

of capacity

ECM interpolation ACS method

DAM algorithm

Object of further R&D

Evaluation of coverage and

tuning of propagation

models based on dedicated

field measurements

Current situation with

commercial tools

8.3.2004 40

Example of LAH simulation results


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8.3.2004 41

6,37

5,123

4,235

2,012

0

1

2

3

4

5

6

7

0 0,01 0,02 0,03 0,04 0,05 0,06 0,07

Erlangs per User

DCR(%)

No LAH

PPA

MDR

TTB

Simulation results for cellular LAH(Dropped Call Rate)

8.3.2004 42

IP level LAH trial


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8.3.2004 43

Trial objectives

Development of the prototypes

Mobile Node and Home Agent protocol stacks (VTT)

Control Application (VTT)

GPS functionality (VTT)

Mobility Management Coordination Function MMCF (NTUA)

MT - MMCF communication = CEPPHO protocol (VTT)

Handover algorithm (COST function) (NTUA)

Demonstrate and evaluate the concept feasibility

handover performance

usage of location information for automatic handover

informing the user about nearby hotspot testing of applications

8.3.2004 44

Trial Scenario

Context: residential area with GPRS coverageand WLAN hot-spots

User: moving around with a laptop/handheldwhile using IP-based applications

Routing and location updates based on Mobile IP


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8.3.2004 45

Trial environment

8.3.2004 46

Network environment


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8.3.2004 47

Handover signalling

Mobile

Terminal

MMCFServer

Location,

Field Strength

NetID

Handover commandPrediction Information

(MGIS)DB

DBupdates,

inquiries

CEPPHO protocol

Coverage map

Network load information

MMCF = mobility management coordination function

8.3.2004 48

Handover algorithm

Algorithm predicts the position of the user in thefuture based on current location and direction ofmotion

The handover is performedonly if the predicted timewithin the hot-spot is longenough

COST function based

approach Network load can be

taken into account


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8.3.2004 49

Trial results

8.3.2004 50

End-to-end delay during handover


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8.3.2004 51

Summary of results on IP-level LAH

Stabilisation period of several seconds appears in

the context of handover Location-aided algorithm was observed to

reduce ping-pong effects

The handover should not be based only onlocation information

GPS is the the preferred location solution due tohigh accuracy requirements

indoors, other methods are needed (e.g. WLAN, Bluetooth ..)

Applications must be able to adapt their bitratebeforehand

This is can be done based on location & velocity information

8.3.2004 52

Follow-on project plans


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8.3.2004 53

Possible continuation of CELLO:

Service usage monitoring

Enhance CELLO functionality for monitoringservice usage

DB Entry:

- service provider Id

- service Id

- terminal location

- terminal type and brand

- usage time

- problem Id

.

Monitoring:- service usage

- users location

- user type data- terminal type

- performance data- Rx-level

SUD

DB Service Provider (SudP)

Services:- location request

- traffic info

- video trailers

- voice book

.

Cellular network operator

Internet

Service Providers

Multimode

terminal

User

WLAN operator

WLAN

Network operator(s)

Teleservice data

Addedvalue

servicedata

8.3.2004 54

Conclusions


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8.3.2004 55

Conclusions (1)

MGIS/LAP concept shows clear improvement toexisting planning&monitoring technology

better precision for coverage estimation compared to prediction

probing is inherently economical method for data collection

suitable for automatic network planning and model tuning

GPS or network-based location methods (DCM) are feasible

ACS is a feasible alternative to expensive adaptiveantenna approach

intended coverage changes could be realised with a relativelysimple arrangement

allows manual or automatic reconfiguration of system

transparent solution at RF level

8.3.2004 56

Conclusions (2)

Location-aided IP-level handover (GPRS/WLAN)

network-independent solution

trial demonstrated feasibility of two main benefits:(1) informing the user of nearby hot-spots(2) automatic decision of handover based on the COST function

Location-aided cellular handovers

demonstrated by simulation

reduced overall number of handovers, clearly reduced droppedcall rate and blocking

__cellular network ion based on mobile location cello)

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