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WaveSight WaveSight TM TM -- see your see your net work!net work!
Technical PresentationTechnical Presentation
Slide 2Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Table of Contents I
I. Network Planning Concerns1. Calculating coverage and reducing interference
2. Rising numbers of subscribers in GSM networks
3. Additional Needs for GPRS
4. Set-up of UMTS networks
II. Propagation History1. Empirical models
2. Semi-empirical models
3. Deterministic models (Ray-Tracing)
III. Deterministic models: WaveSight1. Physical basics of WaveSight
2. Implemented Parameters and algorithms
3. Data Input
4. Simulation
5. Prediction Outcome (Accuracy and Speed)
Slide 3Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Table of Contents II
IV. The added value of WaveSight for network planning
1. Reduced need for measurement and drive tests
2. Better knowledge of Coverage
3. Better Input / better results for frequency planning
4. Rising network quality / better opportunities for fine/tuning
5. Increased speed of network set-up
6. Reduction in the number of needed sites
V. Integration of WaveSight into Planning Tools1. Integrated Planning Tools2. Integration on Windows Systems3. Integration on Unix Systems4. License Protection
Slide 4Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
I. Network Planning Concerns
1. Calculating coverage and reducing interference
2. Rising numbers of subscribers in GSM networks
3. Set-up of UMTS networks
Slide 5Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
1. Calculating coverage
• In the early 90’s, the initial concern in term of planning was to ensure a coverage for all areas as fast as possible.
• After rolling-out their network, the operators had to face one problem : in Urban areas you can easily have shadow areas because of the characteristics of buildings.
• Finally these last years, the most important challenge became to face the important increase of subscribers, which caused problems of saturation in congested areas.
Slide 6Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
2. Rising numbers of subscribers in GSM networks
• The number of subscribers has continuously raised with an explosion in the year 2000, seeing more than 210,000,000 subscribers in Western Europe and an increase of more than 30%.
• Now as the amount of users has grown, it came close to the point that network capacities are saturated in some congested areas.
• Simultaneously, users have rising quality expectations and don´t accept dropped calls and bad connections.
• As the bandwidth allocated to operators is not infinite, the only way to raise network capacity is to add new microcells to increase the maximal amount of users in such areas.
• The important problem that is caused by adding microcells is that the frequency planning became more complex (a good one allows good frequency re-use)
Slide 7Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
3. Additional Needs for GPRS
• On GPRS (General Packet Radio Service) users use remaining free slots of Base Station for data transmission.
• The number of available slots for GRPS is scalable. It depends on the circuit load of the cell (number of voice channels)
The loading of GSM networks will raise seriously !! And so interference will raise as well.
• The received data throughput is directly related to the ratio receivedsignal/interference.
Bad coverage will result in poor data transmission and unacceptable Quality of Service
Badly planned GSM networks will have trouble with GPRS and may also experienceproblems with voice users.
Slide 8Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
4. Set-up of UMTS networks
• Planning of UMTS is a new challenge, as the technology is completely new, the problems in planning will be different
• Infrastructure costs will be a significant burden for all operators
• No frequency planning (frequency reuse = 1)
• Soft handover will be a feature
• There is a great uncertainty about the availability and attractivity of killer applications
Slide 9Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
4.1 Set-up of UMTS networks
• UMTS-Planning is done through network simulations.
• This simulation typically consists of spreading users, engaging different services like voice or data transmission, in the environment.
• The simulating software will then predict the behavior of the simulated network –e.g. uplink, downlink, power
• These characteristics are directly related to interference and so capacity
• Simulation is based on propagation (power path-loss prediction)
• Doing simulations on the basis of bad predictions of the coverage will give nonsense results
Slide 10Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Simulation – User distribution
Cost-Hata WaveSight
Green: OK ; Black: inactive; Red: mobile power outage; Pink: BS power outage; Purple: overload (load factor)
Slide 11Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
II. Propagation History
1. Empirical models
2. Semi-empirical models
3. Deterministic models (ray-tracing)
Slide 12Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
1. Empirical Models
Okumura-Hata
This model has been developed from measurements made by Okumura inTokyoand published [1] in 1968. Then the formula was given by Hata [2] in 1980.
• Advantage :
- Needs no building data
• Disadvantages :
- Needs expensive and time consuming calibration
- Rough prediction (circular shaped)
- the model is not appropriate for planning a sophisticated network
Slide 13Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
1.1 Empirical Models
• Shortcomings :
Despite this model has been developed especially for urban areas, the approach needs heavily calibration which is based on measurements and in some complex terrain like very dense cities it is very difficult to carry out.
[1] Y. Okumura, E. Ohmori, T. Kawano, K.Fukura: " Field strength and its variability in VHF and UHF land-mobile radio service", Review of the Electrical Communication Laboratory, Vol. 16 N°9-10, Sept. 68, pp 825-873.
[2] M. Hata: "Empirical formula for propagation loss in land mobile radio services", IEEE Transaction on Vehicular Technology, Vol.29 N°3, Aug. 80, pp 317-325.
Slide 14Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Empirical Models
Expression given by Hata :L = 69.85 + 6.16 log10 (f) + 13.82 log10 (h) - (44.9 - 6.55 log10 (h)) log10
(d) - A - B - C – D
Where :f = frequency,d = distance transmitter-receiver, h = Base station heightA, B, C & D = relief loss, near obstacles loss, correction for mobile height (1.5m) other (rivers, wood, building density)
Slide 15Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
2. Semi-Empirical Models
Walfish-Ikegami
This model has been published for the first time by Bertoni and Walfish [4,5]. Then only the attenuation caused by buildings was implemented. Several ameliorations were added by different authors to improve the calculation formula. Ikegami has added the last reflection on the opposite wall.
• Advantage :
Takes into account terrain and building data
• Disadvantage :
Still needs expensive and time consuming calibrations
Slide 16Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
2.1 Semi-Empirical Models
• Shortcomings :
Despite this model takes the environment into account, it is still needed to calibrate it so the accuracy of the predictions is still not satisfying enough.
[4] J. Walfish, H.L. Bertoni: "A theoretical model of UHF propagation in urban area", IEEE Trans. on Ant. and Prop., Dec. 1988, pp1788-1796.
[5] H. L. Bertoni, J. Walfish: "A diffraction based theoretical model for predicting UHF path loss", IEEE Trans. on Veh. Tech., Vol. 37, 1988.
Slide 17Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Semi-Empirical Models
Mobile
the reality
Base station
from terrain data base
w1 w2h
α
b
What can be computed by theory1 2 3 4 n-1 n
W
Reflected term(Ikegami)
Classical Fresnel diffraction
multi-screen effect frombase station to last diffraction =
Bertoni-Walfish formula :Pr = C * Pt / d
44
Slide 18Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
3. Deterministic Models
Since the early eighties, a lot of work has been carried out on physical models, which take into account all the three-dimensional environment. All of these models are only based on physical laws and use different techniques like ray-tracing or ray-launching.
• Advantages :- Does not need calibration (frequency, antennas, environment…)- More accurate- One model for all uses (macro small and micro cells).- Allows full channel information (Received power, direction of arrival, impulse
response, short term fading)
• Disadvantages :- Long computation time
• Shortcomings :Few: As the telecom industry is now looking for better accuracy in prediction results to improve the fine tuning of the network, the physical models look at this time the better alternative.
Slide 19Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Deterministic Models
Problems involved
Reflector
Source
Virtual source
Receiver
Virtual source for each reflector
Source
Ray 2
Ray 1
Reflector
Construction imprecision
Reflector
Source
Virtual source
Receiver
Ray tracing method
Reflector
Source
Receiver
Ray launching method
Beam
Ray
Ray construction principle
Slide 20Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Deterministic Models
Base station
Mobile
Slide 21Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Deterministic models : WaveSightTM
1. Physical basics of WaveSight
2. Implemented parameters and algorithms
3. Data input
4. Simulation
5. Prediction outcome (accuracy and speed)
Slide 22Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
1. Physical basics of WaveSight
The propagation of waves is following different modes in the three-dimensional environment.
These propagation modes are :
• Free space
• Diffraction
• Transmission
• Reflection
• Scattering
Slide 23Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
1.1 Physical basics of WaveSight
a. Propagation in free space
Antenna gainPr = P * G / 4pd2
Energyconcentration
on a sector by antenna
Free spacePr = C * Pt / 4pd2
Slide 24Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
1.2 Physical basics of WaveSight
b. Diffraction phenomenon
Obs
tacl
eSource
Wave roundsthe obstacle
Attenuation near
shadowboundary
Obs
tacl
e
Source
Mobile
Diffraction phenomenon Ray representation of diffraction(GTD, UTD)
In shadow area, the received power is proportional to wavelength
Slide 25Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
1.3 Physical basics of WaveSight
Reflection, scattering and transmission phenomenon
Source
Reflection
Scattering
Transmission
Building
Transmission and scattering have no significant impact. So they are not taken into account by WaveSight.
Slide 26Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Approach: Horizontal Plane Propagation
ray0
Receiver
Antenna
Slide 28Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Conclusion
WaveSight is an enhanced ray tracing algorithm
close to ray launching (block ray construction with
image source).
It is 2,5 D (separate quasi horizontal propagation of
vertical propagation) Takes into account :- 2 reflections (Fresnel formula)
- 2 diffractions by vertical wedges (building corners) : UTD
- 15 diffractions by horizontal wedges (roofs) : UTD
- penetration in buildings (constant path loss)
Slide 29Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
2. Implemented Parameters and Algorithms
• Terrain File
• Building Vector Data
• Frequency
• Receiver Height
• Transmitter Coordinates (x, y, z)
• Transmitter power
• Antenna Tilt
• Antenna Azimuth
• Antenna Radiation Pattern (horizontal and vertical)
Slide 30Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
3. Data Input
• Data needed is vector data.
WaveSight is taking ASCII files as input for geographical data in MSI Planet format (supported by almost all planning tools)
• Which resolution/accuracy is needed ?
Common Terrain resolution is 5m, but 25m is sufficient (given that the terrain is not too hilly)
Building accuracy +/- 2m
Slide 31Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Actual terrain data of Paris
Actual terrain data :
(Paris, about 1km x 2km)
Slide 32Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
4. Simulation
• WaveSight’s interface is intuitive and easy-to-use. Running a prediction can be done in 5 steps :
• Zooming in to see the area you are looking for
• Defining the antenna position
• Setting-up the antenna and base-station parameters
• Start the prediction
• Analysing results on the map
Slide 33Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
WaveSight of ArcView
Building and Terrain Data of a part of the City of Bern in Switzerland
(Vector Format)
Slide 36Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
WaveSight of ArcView
Defining an Antenna Position
Slide 37Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
WaveSight of ArcView
Setting AntennaAnd Prediction
Parameter
Slide 38Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
WaveSight of ArcView
Antenna Height,Power, Azimuth,
Tilt, Antenna-Type,Prediction-Radius
Slide 39Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
WaveSight of ArcView
Start of thePrediction
Slide 40Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
WaveSight of ArcView
PredictionRunning
Slide 41Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
WaveSight of ArcView
Prediction with Radius of 300m
(prediction time lessthan a minute on a PII
400 machine)
Slide 42Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
WaveSight of ArcView
Shadow Area Shadow
Area
Shadow Area
Slide 43Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
WaveSight of ArcView
Canyon-Effect of Streets
Canyon-Effect of Streets
Canyon-Effect of Streets
Slide 44Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Prediction Outcome (Accuracy and Speed)
• After the simplicity of WaveSight – needing no calibration and being extremely easy to use – has been shown before, the two main questions to prove WaveSights value are directed towards accuracy and speed.
• The accuracy determines wether WaveSight can improve the input for planning and therefore allows higher quality in network setup and fine-tuning.
• The speed determines wether WaveSight has a practical use at all. So far the big obstacle to the practical use of ray-tracing were computation times up to 12 hours for a microcell.
• The following slides show, how WaveSight typically performs regarding on these critical decision parameters and prove that WaveSight delivers a unique combination of simplicity, accuracy and speed!
Slide 45Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
…tested In The Real World
• Over 80 sites and 1000 km of routes validated:
10 cities / 7 countries
8 operators
• World class high-tech reference:
Bell Labs
EPFL
KPN
• 7 years of development
• Different city types:
• Paris• Munich• Bern• Fribourg• Tampa• Manhattan• Rotterdam• The Hague• Brussels• Torino
Continually growing verification pool!
Slide 46Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Macrocell in Bern
Transmitter: Omni directional antenna, 632 m height, Frequency 1800 MHz
Building layout: Average building heights 614 m
Receivers: located within 1500 m from transmitter on a 20 km route
Computing time: 6 minutes on a Pentium II 266
Error with Measurements: Mean and standard deviation are 0 and 7.5 dB
-140
-120
-100
-80
-60
-40
-20
0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000Rx num ber
Pow
er [d
Bm
]
Measurements
WaveSight Predic tions
Measurements and buildings courtesy Swisscom and Istar respectively
Slide 47Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Small Cell In Bern
Transmitter: Omni directional antenna, 625 m height, Frequency 1800 MHz
Building layout: Average building heights 614 m
Receivers: located within 1500 m from transmitter on a 4 km route
Computing time: 6 minutes on a Pentium II 266
Error with Measurements: Mean and standard deviation are .5 and 5.4 dB
-110
-90
-70
-50
-30
0 500 1000 1500 2000 2500 3000 3500 4000Rx number
Pow
er [d
Bm
]
Measurements
WaveSight Predictions
Measurements and buildings courtesy Swisscom and Istar respectively
Slide 48Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Microcell in Bern
Transmitter: Omni directional antenna, 613 m height, Frequency 1800 MHz
Building layout: Average building heights 614 m
Receivers: located within 1000 m from transmitter on a 2.5 km route
Computing time: 2 minutes on a Pentium II 266
Error with Measurements: Mean and standard deviation are -1.5 and 8.2 dB
-110
-100
-90
-80
-70
-60
-50
-40
-30
0 500 1000 1500 2000 2500Receiver number
- Pat
h Lo
ss [d
B]
MeasurementsWaveSight Predictions
Measurements and buildings courtesy Swisscom and Istar respectively
Slide 49Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Small Cell in Munich
Transmitter: Omni directional antenna, 13 m height, Frequency 900 MHz
Building layout: Average building heights 16m
Receivers: located within 2500 m from transmitter on a 10 km route
Computing time: 7 minutes on a Pentium II 266
Error with Measurements: Mean and standard deviation are -0.2 and 6.4 dB
-160
-150
-140
-130
-120
-110
-100
-90
-80
-70
0 100 200 300 400 500 600 700 800 900 1000Receiver number
- Pat
h Lo
ss [d
B]
MeasurementsWaveSight Predictions
Measurements and buildings courtesy Mannesmann
Slide 50Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Microcell in The Hague
Transmitter: Omni directional antenna, 8 m height, Frequency 900 MHz
Building layout: Average building heights 11 m
Receivers: located within 3000 m from transmitter on a 25 km route
Computing time: 8 minutes on a Pentium II 266
Error with Measurements: Mean and standard deviation are 3.5 and 6.8 dB
-170
-160
-150
-140
-130
-120
-110
-100
-90
-80
-70
0 500 1000 1500 2000 2500Receiver number
- Pat
h Lo
ss [d
B]
MeasurementsWaveSight Predictions
Measurements and buildings courtesy KPN
Slide 51Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Small Cell in The Hague
Transmitter: Omni directional antenna, 11 m height, Frequency 900 MHz
Building layout: Average building heights 11 m
Receivers: located within 3000 m from transmitter on a 25 km route
Computing time: 8 minutes on a Pentium II 266
Error with Measurements: Mean and standard deviation are 4.1 and 6.8 dB
-160
-150
-140
-130
-120
-110
-100
-90
-80
-70
0 500 1000 1500 2000 2500Receiver number
- Pat
h Lo
ss [d
B]
MeasurementsWaveSight Predictions
Measurements and buildings courtesy KPN
Slide 52Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Macrocell in The Hague
Transmitter: Omni directional antenna, 15 m height, Frequency 900 MHz
Building layout: Average building heights 11 m
Receivers: located within 3000 m from transmitter on a 25 km route
Computing time: 8 minutes on a Pentium II 266
Error with Measurements: Mean and standard deviation are 2.5 and 8.3 dB
-160
-150
-140
-130
-120
-110
-100
-90
-80
-70
0 500 1000 1500 2000 2500Receiver number
- Pat
h Lo
ss [d
B]
MeasurementsWaveSight Prediction
Measurements and buildings courtesy KPN
Slide 53Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Summarm of Accuracy
8.36.86.85.86.48.25.47.5
Standard Deviation (db)
2.54.13.5-1.5-0.2-1.50.50
Meanerror (db)
+40-3-3-3-11118
AntennaHeight (abovebuilding)
MacroSmallMicroSmallSmallMicroSmallMacroCell Size
The HagueTheHague
TheHague
MunichMunich
BernBernBern
Slide 54Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Microcell in Paris
1099 sec. / 18,32 min.36 km2 (6000m x 6000m)
554 sec. / 9,23 min.16 km2 (4000m x 4000m)
153 sec. / 2,55 min.4 km2 (2000m x 2000m)
57 sec. / 0,95 min.1 km2 (1000m x 1000m)
29 sec. / 0,48 min.0,16 km2 (400m x 400m)
Calculation TimeArea
The calculations were performed with a 650 Mhz Pentium III PC with 192 MB RAM.
Slide 55Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Macrocell in Torino
5802 sec. / 96,70 min64 km2 (8000m x 8999m)
951 sec. / 15,85 min.36 km2 (6000m x 6000m)
412 sec. / 6,87 min.16 km2 (4000m x 4000m)
246 sec. / 4,10 min.4 km2 (2000m x 2000m)
54 sec. / 0,90 min.1 km2 (1000m x 1000m)
25 sec. / 0,42 min.0,16 km2 (400m x 400m)
Calculation Time Area
The calculations were performed with a 650Mhz Pentium III PC with 192 MB RAM.
Slide 56Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Microcell in Amsterdam
960 sec. / 16,0 min.16 km2 (4000m x 4000m)
315 sec. / 5,25 min.4 km2 (2000m x 2000m)
95 sec. / 1,58 min.1 km2 (1000m x 1000m)
17 sec. / 0,28 min.0,16 km2 (400m x 400m)
Calculation TimeArea
The calculations were performed with a 650 Mhz Pentium III PC with 192 MB RAM.
Slide 57Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Microcell in Bern
196 sec. / 3,27 min.16 km2 (4000m x 4000m)
74 sec. / 1,23 min.4 km2 (2000m x 2000m)
34 sec. / 0,57 min.1 km2 (1000m x 1000m)
15 sec. / 0,25 min.0,16 km2 (400m x 400m)
Calculation TimeArea
The calculations were performed with a 650Mhz Pentium III PC with 192 MB RAM.
Slide 58Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Macrocell in Paris
915 sec. / 15,25 min.36 km2 (6000m x 6000m)
492 sec. / 8,20 min.16 km2 (4000m x 4000m)
201 sec. / 3,35 min.4 km2 (2000m x 2000m)
73 sec. / 1,22 min.1 km2 (1000m x 1000m)
27 sec. / 0,45 min.0,16 km2 (400m x 400m)
Calculation TimeArea
The calculations were performed with a 650 Mhz Pentium III PC with 192 MB RAM.
Slide 59Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Macrocell in Paris
990 sec. / 16,50 min.36 km2 (6000m x 6000m)
750 sec. / 12,50 min.16 km2 (4000m x 4000m)
355 sec. / 5,92 min.4 km2 (2000m x 2000m)
105 sec. / 1,75 min.1 km2 (1000m x 1000m)
30 sec. / 0,50 min.0,16 km2 (400m x 400m)
Calculation TimeArea
The calculations were performed with a 650 Mhz Pentium III PC with 192 MB RAM.
Slide 60Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Summary of Speed
--96.70-64 km2
--15.85 min18.32 min36 km2
3.27 min16.0 min6.87 min9.23 min16 km2
1.23 min5.25 min4.10 min2.55 min4 km2
0.57 min1.58 min0.90 min0.95 min1 km2
0.25 min0.28 min0.42 min0.48 min0.16 km2
Microcell in Bern
Microcell in Amsterdam
Macrocell in Torino
Microcell in Paris
Area of Calculation
Slide 61Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
IV. The added value of WaveSight for network planning
1. Reduced need for measurement and drive tests
2. Better knowledge of Coverage
3. Better Input / better results for frequency planning
4. Rising network quality / better opportunities for fine/tuning
5. Increased speed of network set-up
6. Reduction in the number of needed sites
Slide 62Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Reduced need for measurement and drive tests
• WaveSight is a deterministic model. The input consists of a rough picture of the physical environment and the calculation process is based on a picture of the physical behavior of the rays (UTD, Ray-Tracing, Maxwells-Theory of Rays).
• Because all signficant geographic information is taken into account in the calculation process, the model needs NO TUNING.
• Therefore a lot of money, time and energy which is going into drive testing can be saved by using WaveSight.
Slide 63Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Better knowledge of Coverage
It is clearly visible that the coverage in the empirical prediction is only very crudely estimated (red area), whereas the WaveSight prediction takes the physical characteristics of the city into account (buildings, streets, terrain) to compute a precise map. The canyon effect of streets is visible.
Okumura-Hata Model (macro)+ Pseudo-Ray Tracer (micro)
WaveSight Model
Slide 64Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Coverage by signal level
Cost-Hata WaveSight
Coverage by signal >=-75 dBm
>=-81 dBm
>=-85 dBm
>=-93 dBm
>=-96 dBm
>=-102 dBm
Measurements
Slide 65Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Better Input / better results for frequency planning
• To show the impact of WaveSights predictions on frequency planning the Wavecall team has performed a study – based on the GSM-technology (download: www.wavecall.com/papers).
• The main objective of this case study was to show that using a sophisticated prediction model reduces cost and time in frequency planning.
• ILSA, a frequency-planning tool from Aircom, was used to compare frequency planning obtained by using classical propagation models and the ray-tracing model WaveSight.
• The tests presented were performed on a 4.5 km2 area comprising 17 sites (36 cells) actually used in the Bouygues Telecom network of Paris.
• This study demonstrates that using WaveSight can reduce the number of carriers needed to provide the same network quality from 47 carriers to 40. This is significant not only because it can reduce the cost of fine-tuning the network, but also because extra carriers can be used to increase traffic capacity.
• By using, WaveSight, the network interference area can be reduced by 80%.
Slide 66Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Rising network quality / better opportunities for fine/tuning
Changing a minor parameter can have astonishing impact on the coverage.
The single change made is the antenna’s height.
Initial coverage (left), Antenna 2m higher (above)
Slide 67Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Best Server (-102dBm)
Cost-Hata WaveSight
Slide 68Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Overlapping (- 80dBm)
Cost-Hata WaveSight
Intercell interference => noise increase => reduced capacity
Slide 69Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Soft Handover – No handoff area
Cost-Hata WaveSight
Slide 70Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Simulation – User distribution
Cost-Hata WaveSight
Green: OK ; Black: inactive; Red: mobile power outage; Pink: BS power outage; Purple: overload (load factor)
Slide 71Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Simulation
• 232 active users
• Simulation with empirical prediction: 4 rejections (1.7 %) , due to load factor
• Simulation with deterministic prediction: 47 rejections (20.3%), 5.2 % due to power, 4.3 % due to pilot problem, 10.8% due to load factor. 18% of speech users, 22% of 64kbps users, 28% of 144kbps users.
Slide 72Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Effective service area - Speech
Cost-Hata WaveSight
100% of area 90.3% of area
Slide 73Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Effective service area - 64kbps
Cost-Hata WaveSight
100% of area 87.1 % of area
Slide 74Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Service area - 144 kbps
Cost-Hata WaveSight
99.3 % of area 83.1 % of area
Slide 75Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
DL Service area 64kbps – different Eb/N0 threshold
Cost-Hata WaveSight
64kbps Service area (Eb/Nt maxi >= 10 dB
Eb/Nt maxi >= 8 dB
Eb/Nt maxi >= 5 dB
Eb/Nt maxi >= 1 dB
Slide 76Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Conclusion & future
• UMTS simulations and planning are based on the path loss prediction => if it’s wrong the results are nonsense.
• Ray tracing models are also able to deliver other interesting feature for UMTS: impulse response, delay spread, direction of arrivals.
Slide 77Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Increased speed of network set-up
• In the actual situation at the UMTS-frontier speed is desperately needed.
• For acquiring their licenses operators had to invest tremendous amounts of money, raising their debts to almost intolerable limits.
• Every day of delaying the start of their new networks and making money with their licenses can be said to cost millions of € in interest rates.
• Because WaveSight is easy to use, calculates accurate predictions extremely fast and needs no calibration to (non-existing) measurements it can significantly speed-up the planning phase and help to shorten the time to start the technical and commercial operation of the network –saving millions of € in interest rates.
Slide 78Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Reduction in the number of needed sites
• In the planning phase, a propagation fading margin istaken in the link budget in order to raise the probability of good coverage.
• This margin is directly related to the standard deviationerror of the propagation prediction model.
• The more accurate the propagation model is, the lowerthe standard deviation is and the lower the needed margin is.
• A gain in the link budget results in a lower needed basestation density.
• An improvement of 1dB in the link budget corresponds to 12% reduction in the number of needed sites. 2dB corresponds to a 23 % reduction and 3dB to 32%. (based on a propagation path loss exponent of 3.52) 1
1 (ref WCDMA for UMTS, H.Holma A.Toskala)
Slide 79Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Integration of WaveSight into Planning Tools
1. Integrated Planning Tools
2. Integration on Windows Systems
3. Integration on Unix Systems
4. License Protection
Slide 80Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Integrated Planning Tools
Integration Completed :
• Enterprise – Aircom (Partnership with one-stop-shop and support)
• Totem – Nokia (Partnership with one-stop-shop and support in negotiation)
• Atoll – Forsk (Partnership with one-stop-shop and support)
• Odyssey – Logica (Partnership with one-stop-shop and support)
• Ellipse – CRIL
• Planet – MSI
Integration work in progress:
• Astrix – Teleplan (Partnership with one-stop-shop and support)
• Celplanner Suite – Celplan (Partnership with one-stop-shop and support in negotiation)
• Wizard – Safco/Agilent (Partnership with one-stop-shop and support in negotiation)
Companies with a positive stance towards integration• Quantum – Quotient
• Decibel Planner – Northwood
Slide 81Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Integration on Windows Systems
Planning Tool
WaveSight Interface
Calc Array()
Create input files for WaveSight
Files.txt
1 2
Call
Winsight.exeDLL Library
w2c_wsal.dll
Read
Generates Results
Slide 82Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
Integration on Unix Systems
Planning Tool
WaveSight Interface
Calc Array()
Create input files for WaveSight
Files.txt
1 2
Call
WS.exeRead
Generates Results
Slide 83Prof. Dr. Volker Amelung / Dr. Karim Rizk Wavecall SA
License Protection
The licensing is made in 2 different ways :
1. Completely integrated into the planning tools, with whom we have a partnership agreement (protection with the dongle solution)
2. In the other case, with a node-locked license where a serial key is generated in link with the D-drive serial number (NT Workstation) or the Host-ID (Unix Workstation)