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www.awe-communications.com

WinProp Multi Scenario Model

for Aircom Enterprise


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December 2008 (c) by AWE Communications 2

Outline

Motivation

Algorithm

Installation

Configuration and Features

Performance Evaluation

Enterprise Standard Models vs. Multi Scenario Model

Enhanced Features


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Motivation

Only simple wave propagation models available in AircomEnterprise

Important wave propagation effects are not considered by

simple wave propagation models One new wave propagation model for all scenarios

needed:

Vector building data

Clutter / landusage

Topography


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Typical Scenario

Vector building

data

Topographicaldata

Land usage data

Topographical data

Algorithm

Complete predictionarea

Transition



Multi Scenario Model

Algorithm

Combination of semi-deterministic and empirical wavepropagation models

Semi-deterministic model: 3D Urban Dominant Path Model

Empirical models: Hata-Okumura, Empirical Two-Ray, Deterministic Two-Ray

Automatic transition

Suitable for large scenariosSemi-

deterministicmodel

Empirical

model

Transition



3D Urban Dominant Path Model (1/ 3)

Algorithm

Only dominant path relevant

Calibration possible

Suitable for all scenarios

Short prediction times

High accuracy

S

E

S

E

S

EEmpirical Ray Optical Dominant Path

No preprocessing of

database in contrast toIRT



3D Urban Dominant Path Model (2/ 3)

Algorithm

Analysis of wedges in the scenario

Construction of a tree

Finding the best propagation path

convexwedges

T

Layer 1

Layer 3

Layer 4

Layer 2

4 52

24 25R5 4

5R 5 424 2R

RR

T

R

concave wedges convex wedges1

1

2

34

5

23 46 5

6


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Empirical Vertical Plane Models

Algorithm

Hata-Okumura Model

4 submodels (open/suburban/medium urban/dense urban)

Akeyama Extension

COST 207 for frequencies in the 2 GHz band

Two-Ray Models

Direct ray and ground reflected ray

Either deterministic (with check of visibility and check of reflection) orempirical (assuming always LOS)

Knife Edge Diffraction Extension

Consideration of topography in vertical plane between Tx and Rx

ll i



Installation

Copy WinProp plug-in package (*.zip) into the subfolderCommon of the Enterprise main directory and unzip thezip archive

Launch the batch file Install WinProp Multi ScenarioModel which is also located in the Common folder

Install the license (USB dongle / license file)

Start Aircom Enterprise and add the WinProp model toyour project

C fi ti


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Property Page: General

Configuration

Definition of frequency and prediction height


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Configuration


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Property Page: Model Settings

Configuration

Definition of settings for 3D Dominant Path Model

Definition of pathloss exponents andbreak point factor

Interaction lossesdue to diffractions or

transmissions

Adaptive resolutionfor acceleration

Empirical indoorprediction model

Configuration


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Property Page: Large Areas

Configuration

Definition of settings for large areas

Transition toempirical model after

certain distance

Selection ofempirical prediction

model and itsparameters

Knife edgediffraction algorithm


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Wave guiding effects in urban street canyons

Diffractions at corners

Computation time: less than 30 s

3D Urban Dominant Path Model: Tx in Street Canyon (2/ 2)



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Simulation settings

Prediction resolution 5 m

Prediction radius 500 m

Height of m obile station 1.5 m

Considered databases Vector buildings & Topo

TX frequency 1800 MHz

Max. TX power 43 dBm

TX antenna height 25 m, 30 m, 35 m

Azimuth of TX antenna 225

Downti lt of TX antenna 0

3D Urban Dominant Path Model: Tx above roof tops (1/ 2)

Scenario:Bern (Switzerland)



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Antenna height: 30 m Antenna height: 35 mAntenna height: 25 m

Shadows of buildings visible in prediction (depending on building heights)

The higher the antenna, the better the coverage (smaller shadows of buildings)

In-house prediction with Exponential Decrease Model

Prediction time: less than 30 s

3D Urban Dominant Path Model: Tx above roof tops (2/ 2)



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Scenario:Bern (Switzerland)

Simulation settings







TX antenna height 15 m, 40 m



3D Urban Dominant Path Model: Tx at open place (1/ 3)



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Antenna height: 40 mAntenna height: 15 m





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Antenna height: 40 mAntenna height: 15 m

Additional in-house prediction with Exponential Decrease Model



Enterprise standard models vs. Multi Scenario DPM


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Default parameters: Enterprise Macrocell Model 3

Model parameters

Earth radius 8493 km

k1 150.6 / 160.9

k2 44.9

k1 (near) 0.0

k2 (near) 0.0

k3 -2.55

d < 0.0

k4 0.0

k5 -13.82

k6 -6.55

k7 0.7 / 0.8

Effect iv e antenna hei gh t (Heff) algorit hm absolu te

Diffraction loss algorithm Epstein Peterson

Merge knife edges closer than Not used

clutters Not used

ASSET 3G User Reference GuideVersion 5.2.1 page 40

(values for 900 / 1800MHz)




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Default parameters: Enterprise M icrocell Model

Model parameters

Earth radius - 6370 km

Loss at one meter LOS area 41.2 / 41.5 dB

Antenna height gain LOS area 12.6 / 8.2

Near slope LOS area 8.7 / 16.3 dB/ dec

Far slope LOS area 41.3 / 49.0 dB/ dec

Breakpoint LOS area automatic

Forw ard scatterer near slope (NLOS area) NLOS area 17.9 / 18.7 dB/ dec

Forward scatterer far slope (NLOS area) NLOS area 17.9 / 18.7 dB/ dec

Back scatterer near slope (NLOS area) NLOS area 0

Back scatterer far slope (NLOS area) NLOS area 17.9 / 18.7 dB/ dec

Ignore buildings < meters tall NLOS area 0 m

Highest order virtual source NLOS area 2

Max. distance to diffracting edge NLOS area 6

Building penetration loss - 20 dB

In-building slope - 1

ASSET 3G User Reference GuideVersion 5.2.1 pages 50, 51

(values for 900 / 1800 MHz)



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Urban Street Canyon (1/ 4): Scenario

City of Istanbul (Turkey)

Simulation settings










p



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Urban Street Canyon (2/ 4): Enterprise Marcocell Model

No wave guiding effects

No consideration of buildings

Computation time: 1 s

Antenna height: 15 m Antenna height: 25 m

p



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Urban Street Canyon (3/ 4): Enterprise Mircocell Model

Waveguiding (mulitple reflections) in street canyons not visible

Diffractions at building corners not visible



p


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Shadowing effects due to topography (2/ 3):

Comparison of prediction results

Enterprise Macrocell

Enterprise Microcell

Multi Scenario DPM



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Shadowing effects due to topography (3/ 3):

Analysis of prediction results

Enterprise Marcocell Model

No shadowing due to topography visible

Computation time: 1s

Enterprise Mircocell Model

Influence of topography visible, but not as expected


3D Urban Dominant Path Model

Wave guiding due to topography in the valley

Shadowing effects due to higher elevations




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Shadow ing effects due to buildings (1/ 3): Scenario

Simulation settings








Azimuth of TX antenna omni directional antenna

Downtilt of TX antenna omni directional antenna

City of Bern (Switzerland)

Building height: 14 m



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Shadowing effects due to buildings (2/ 3):

Enterprise M ircocel l Model

Influence of building not obviously visible




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Enhanced Features


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Consideration of vegetation (1/ 2):

Arbitrary modeled vegetation blocks possible (woods, fields, etc.)

Antenna height: 10 m



Vegetation modeling in a city center

Enhanced Features


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Consideration of vegetation (2/ 2):

Higher path loss values inside the vegetation blocks


Enhanced Features


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Load predicted results w ith ProMan for detailed view :

Prediction of in-house transmitters

Penetration through huge glass doors and windows

Indoor walls can be considered (if data is available)

View propagation paths and detailed 3D view with ProMan

Enhanced Features


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Load predicted results w ith ProMan for detailed view :

Indoor prediction on multiple height levels

Hybrid propagation mode for predictions on multiple building floors


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AWE CommunicationsOtto-Lilienthal-Str. 36

71034 Boeblingen

Germany

Phone: +49 7031 71497 0Fax: +49 7031 71497 12

[email protected]

www.awe-communications.com

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