Date post: | 07-Apr-2018 |
Category: |
Documents |
Upload: | makhful-adhim |
View: | 222 times |
Download: | 0 times |
of 40
8/6/2019 Air Comp Lug In
1/40
www.awe-communications.com
WinProp Multi Scenario Model
for Aircom Enterprise
8/6/2019 Air Comp Lug In
2/40
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
8/6/2019 Air Comp Lug In
3/40
December 2008 (c) by AWE Communications 3
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
8/6/2019 Air Comp Lug In
4/40December 2008 (c) by AWE Communications 4
Typical Scenario
Vector building
data
Topographicaldata
Land usage data
Topographical data
Algorithm
Complete predictionarea
Transition
8/6/2019 Air Comp Lug In
5/40December 2008 (c) by AWE Communications 5
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
8/6/2019 Air Comp Lug In
6/40December 2008 (c) by AWE Communications 6
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
8/6/2019 Air Comp Lug In
7/40December 2008 (c) by AWE Communications 7
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
8/6/2019 Air Comp Lug In
8/40
8/6/2019 Air Comp Lug In
9/40December 2008 (c) by AWE Communications 9
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
8/6/2019 Air Comp Lug In
10/40December 2008 (c) by AWE Communications 10
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
8/6/2019 Air Comp Lug In
11/40
December 2008 (c) by AWE Communications 11
Property Page: General
Configuration
Definition of frequency and prediction height
8/6/2019 Air Comp Lug In
12/40
8/6/2019 Air Comp Lug In
13/40
Configuration
8/6/2019 Air Comp Lug In
14/40
December 2008 (c) by AWE Communications 14
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
8/6/2019 Air Comp Lug In
15/40
December 2008 (c) by AWE Communications 15
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
8/6/2019 Air Comp Lug In
16/40
Performance Evaluation
8/6/2019 Air Comp Lug In
17/40
December 2008 (c) by AWE Communications 17
Performance Evaluation
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)
Performance Evaluation
8/6/2019 Air Comp Lug In
18/40
December 2008 (c) by AWE Communications 18
Performance Evaluation
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)
Performance Evaluation
8/6/2019 Air Comp Lug In
19/40
December 2008 (c) by AWE Communications 19
Performance Evaluation
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)
Performance Evaluation
8/6/2019 Air Comp Lug In
20/40
December 2008 (c) by AWE Communications 20
Performance Evaluation
Scenario:Bern (Switzerland)
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 15 m, 40 m
Azimuth of TX antenna 15
Downti lt of TX antenna 3
3D Urban Dominant Path Model: Tx at open place (1/ 3)
Performance Evaluation
8/6/2019 Air Comp Lug In
21/40
December 2008 (c) by AWE Communications 21
Performance Evaluation
Antenna height: 40 mAntenna height: 15 m
3D Urban Dominant Path Model: Tx at open place (2/ 3)
Computation time: less than 10 s
Performance Evaluation
8/6/2019 Air Comp Lug In
22/40
December 2008 (c) by AWE Communications 22
Performance Evaluation
Antenna height: 40 mAntenna height: 15 m
Additional in-house prediction with Exponential Decrease Model
Computation time: less than 20 s
3D Urban Dominant Path Model: Tx at open place (3/ 3)
Enterprise standard models vs. Multi Scenario DPM
8/6/2019 Air Comp Lug In
23/40
December 2008 (c) by AWE Communications 23
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)
Enterprise standard models vs. Multi Scenario DPM
Enterprise standard models vs. Multi Scenario DPM
8/6/2019 Air Comp Lug In
24/40
December 2008 (c) by AWE Communications 24
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)
Enterprise standard models vs. Multi Scenario DPM
8/6/2019 Air Comp Lug In
25/40
Enterprise standard models vs. Multi Scenario DPM
8/6/2019 Air Comp Lug In
26/40
December 2008 (c) by AWE Communications 26
Urban Street Canyon (1/ 4): Scenario
City of Istanbul (Turkey)
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 900 MHz
Max. TX power 43 dBm
TX antenna height 15 m, 25 m
Azimuth of TX antenna 40
Downti lt of TX antenna 2
p
Enterprise standard models vs. Multi Scenario DPM
8/6/2019 Air Comp Lug In
27/40
December 2008 (c) by AWE Communications 27
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
Enterprise standard models vs. Multi Scenario DPM
8/6/2019 Air Comp Lug In
28/40
December 2008 (c) by AWE Communications 28
Urban Street Canyon (3/ 4): Enterprise Mircocell Model
Waveguiding (mulitple reflections) in street canyons not visible
Diffractions at building corners not visible
Computation time: 214 s
Antenna height: 15 m Antenna height: 25 m
p
8/6/2019 Air Comp Lug In
29/40
8/6/2019 Air Comp Lug In
30/40
Enterprise standard models vs. Multi Scenario DPM
8/6/2019 Air Comp Lug In
31/40
December 2008 (c) by AWE Communications 31
Shadowing effects due to topography (2/ 3):
Comparison of prediction results
Enterprise Macrocell
Enterprise Microcell
Multi Scenario DPM
Enterprise standard models vs. Multi Scenario DPM
8/6/2019 Air Comp Lug In
32/40
December 2008 (c) by AWE Communications 32
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
Computation time: 85 s
3D Urban Dominant Path Model
Wave guiding due to topography in the valley
Shadowing effects due to higher elevations
Computation time: 7 s
Enterprise standard models vs. Multi Scenario DPM
8/6/2019 Air Comp Lug In
33/40
December 2008 (c) by AWE Communications 33
Shadow ing effects due to buildings (1/ 3): Scenario
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 900 MHz
Max. TX power 43 dBm
TX antenna height 10 m, 20 m
Azimuth of TX antenna omni directional antenna
Downtilt of TX antenna omni directional antenna
City of Bern (Switzerland)
Building height: 14 m
Enterprise standard models vs. Multi Scenario DPM
8/6/2019 Air Comp Lug In
34/40
December 2008 (c) by AWE Communications 34
Shadowing effects due to buildings (2/ 3):
Enterprise M ircocel l Model
Influence of building not obviously visible
Computation time: 63 s
Antenna height: 10 m Antenna height: 20 m
8/6/2019 Air Comp Lug In
35/40
Enhanced Features
8/6/2019 Air Comp Lug In
36/40
December 2008 (c) by AWE Communications 36
Consideration of vegetation (1/ 2):
Arbitrary modeled vegetation blocks possible (woods, fields, etc.)
Antenna height: 10 m
Antenna height: 20 m
Antenna height: 30 m
Vegetation modeling in a city center
Enhanced Features
8/6/2019 Air Comp Lug In
37/40
December 2008 (c) by AWE Communications 37
Consideration of vegetation (2/ 2):
Higher path loss values inside the vegetation blocks
Antenna height: 30 m
Enhanced Features
8/6/2019 Air Comp Lug In
38/40
December 2008 (c) by AWE Communications 38
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
8/6/2019 Air Comp Lug In
39/40
December 2008 (c) by AWE Communications 39
Load predicted results w ith ProMan for detailed view :
Indoor prediction on multiple height levels
Hybrid propagation mode for predictions on multiple building floors
8/6/2019 Air Comp Lug In
40/40
December 2008 (c) by AWE Communications 40
AWE CommunicationsOtto-Lilienthal-Str. 36
71034 Boeblingen
Germany
Phone: +49 7031 71497 0Fax: +49 7031 71497 12
www.awe-communications.com