ATOLL MEASUREMENT MODULE Training Programme 1. SPM Calibration Concepts . u e nes or easurement urveys 3. Working with CW Measurements 4. Automatic Calibration Method 5. Analysing the Calibrated Model 6. Calibration Process Summary © Forsk 2010 Confidential – Do not share without prior permission Slide 2 of 54 1. SPM Calibration Concepts Goal equ rements Quality target © Forsk 2010 Confidential – Do not share without prior permission Slide 3 of 54 Goal SPM Macrocell statistical propagation model Based on empirical formulas + set of parameters Propagation depends on Frequency Area type (urban, suburban, rural, etc.) Geography (relief, vegetation, climate, etc.) Calibration is essential to accurately estimate Coverage predictions Interferences © Forsk 2010 Confidential – Do not share without prior permission Slide 4 of 54 Requirements (1) Accurate and recent geo data DTM and clutter resolution <= 25m for urban areas DTM and clutter resolution <= 50m for rural areas Vector map with major roads CW measurement surveys Selection of representative areas for different area types Site selection for each (area type – frequency band) 8 recommended (minimum 6) sites for calibration, 2 sites for verification Survey route study Perform CW surveys by fully following guidelines © Forsk 2010 Confidential – Do not share without prior permission Slide 5 of 54 Requirements (2) Drive Test data Possible but not recommended Conversion to CW measurements is needed Downside Real network is measured interferences Directional antennas: accuracy of pattern, only a few points are relevant Several frequencies are measured Low sampling rate for each measured station (lee criterion can’t be met) Signal measured over a short distance from the transmitter (model will not be calibrated for interference evaluation) © Forsk 2010 It is not recommended to use Drive Test data to calibrate a model Confidential – Do not share without prior permission Slide 6 of 54 Quality Target Calibration sites Global mean error on calibration sites < 1 dB Global standard deviation on calibration sites < 8 dB Mean error on each calibration site < 2.5 dB Standard deviation on each calibration site < 8.5 dB Verification sites Global mean error on verification sites < 2 dB Global standard deviation on verification sites < 8.5 dB © Forsk 2010 Confidential – Do not share without prior permission Slide 7 of 54 Training Programme 1. SPM Calibration Concepts . u e nes or easurement urveys 3. Working with CW Measurements 4. Automatic Calibration Method 5. Analysing the Calibrated Model 6. Calibration Process Summary © Forsk 2010 Confidential – Do not share without prior permission Slide 8 of 54 2. Guidelines for CW Measurement Surveys Site Preselection criteria urvey route cr ter a Radio criteria © Forsk 2010 Confidential – Do not share without prior permission Slide 9 of 54 Site Preselection Criteria Surrounding Very representative of area type Major clutter classes equally represented No major obstruction within a radius of 150 to 200m from the CW sites Low diffraction within a 10km radius (rural zones) Enough roads all around the site nspec on on s e Possibility to rig omnidirectional antenna (no obstacle on any side) Panoramic photographs Report site details: precise height, coordinates © Forsk 2010 Confidential – Do not share without prior permission Slide 10 of 54 Survey Route Criteria Distance Up to noise floor of the receiver Equal number of samples near and far in all directions Clutter Routes through major clutter classes Avoid forests and lakes between transmitter and receiver Maps Supply vector maps of survey routes to import in Atoll Check that survey routes match roads (vector data or scanned maps) © Forsk 2010 Confidential – Do not share without prior permission Slide 11 of 54 Radio Criteria (1) Frequency 3 contiguous unused channels for GSM 1 unused carrier for UMTS Only one channel must be measured Interferences must be checked before each drive Equipment data ntenna patterns + ownt t + az mut not per ect y omn rect ona Antenna height + transmit power + transmission gain and losses Receiver height + sensitivity + reception gain and losses © Forsk 2010 Confidential – Do not share without prior permission Slide 12 of 54 Radio Criteria (2) Signal measurement Lee criterion: at least 36 samples over 40 λ (for f ≥ 900 MHz) Maximum vehicle speed depends on equipment’s sampling rate Sampling Rate at 900 MHz Sampling Rate at 2100 MHz (samples per second) (samples per second) 45 100 60 68 150 90 90 200 120 113 250 150 Max. Speed (km/h) Measurements after averaging At least 5000 points per site Typical number: between 10000 and 20000 points © Forsk 2010 Confidential – Do not share without prior permission Slide 13 of 54 Training Programme 1. SPM Calibration Concepts . u e nes or easurement urveys 3. Working with CW Measurements 4. Automatic Calibration Method 5. Analysing the Calibrated Model 6. Calibration Process Summary © Forsk 2010 Confidential – Do not share without prior permission Slide 14 of 54 3. Working with CW Measurements Creating a CW measurement path B co in – astin X Y measurement By importing any ASCII format file • • Standard import as in excel Option of importing any additional information related to CW measurement points • configurations © Forsk 2010 Confidential – Do not share without prior permission Slide 15 of 54 3. Working With CW Measurements CW Measurements: Table List of all measurement points with their attributes and additional information Coordinates of points Altitude, Clutter classes and heights, Distance, etc. read from the Geo data Signal Measured values Standard content management and tools (filters, copy-paste, etc...) © Forsk 2010 Confidential – Do not share without prior permission Slide 16 of 54 3. Working With CW Measurements CW Measurements: Properties For predictions along the CW measurement path, you can either use Existing path loss matrices or recalculate them by choosing a specific Propagation model © Forsk 2010 The points can be displayed according to any data contained in the measurement Table Confidential – Do not share without prior permission Slide 17 of 54 3. Working With CW Measurements CW Measurements: Calculations and Statistics To calculate the predicted signal level of the reference an any o er op ona y added) transmitter along the considered path. Note: This can also be run from top folders. To compare statistics between measured and predicted signal levels. Note: This can also be run from top folders. © Forsk 2010 Confidential – Do not share without prior permission Slide 18 of 54 3. Working With CW Measurements CW Measurements: Filter (at the Folder level) Distance, Measurements Advanced filter on additional survey data © Forsk 2010 Confidential – Do not share without prior permission Clutter Classes filtering Slide 19 of 54 3. Working With CW Measurements CW Measurements: Filtering Assistant and Filtering Zones Tool to filter the data path in an more advanced way than in the Filter dialogue available at the folder level (previous slide) Tool to exclude some points from the measurement path according to a drawn polygon (all points within the polygon will be filtered out) © Forsk 2010 Confidential – Do not share without prior permission Slide 20 of 54 3. Working With CW Measurements CW Measurements: Smoothing BEFORE Create a sliding window to smooth the measured signal strength AFTER Smoothing can be used to limit fading effect Smoothing keeps the number of measurement points unchanged Smoothing cannot be used to average gross CW measurements © Forsk 2010 Confidential – Do not share without prior permission Slide 21 of 54 3. Working With CW Measurements CW Measurements: Synchronise the Table, the Map and the CW Measurements Tool Synchronisation: - Map - Table - CW Measurements Tool Predicted signal level Analysis of a specific CW measurement path © Forsk 2010 Display of any attribute related to a given path Confidential – Do not share without prior permission Slide 22 of 54 Training Programme 1. SPM Calibration Concepts . u e nes or easurement urveys 3. Working with CW Measurements 4. Automatic Calibration Method 5. Analysing the Calibrated Model 6. Calibration Process Summary © Forsk 2010 Confidential – Do not share without prior permission Slide 23 of 54 4. Automatic Calibration Method CW measurements pre-processing Initial model Calibration wizard Final model © Forsk 2010 Confidential – Do not share without prior permission Slide 24 of 54 CW Measurements Pre-processing Correspondence between Measurements and Geo data Projection checking Check that CW measurements match roads Routes checking Check that CW measurements respect planned survey routes Surrounding checking © Forsk 2010 Check with panoramic photographs that there is no obstacle Option of setting an angle filter to avoid attenuation due to obstacles Confidential – Do not share without prior permission Slide 25 of 54 CW Measurements Pre-processing Filtering Available at the Folder level for each site Will be applied to all the measurement paths in that folder Distance, Measurements values and Azimuth filtering Advanced filter on additional survey data © Forsk 2010 Confidential – Do not share without prior permission Will permanently remove the points outside the filter Slide 26 of 54 CW Measurements Pre-processing Distance filtering (Min Distance / Max Distance) Typical min value: 200 m (not representative of mean propagation) Typical max value: 10 km (rural area) Signal filtering (Min Measurement / Max Measurement) Filtering out the measurements above the receiver overload: typical value -40 dBm Filtering out the measurements below the “receiver sensitivity + target standard deviation” typical value: -120 + 8 = -112 dBm In order to avoid noise saturation effect in statistical results Azimuth filtering To remove points in a certain angle Filtering assistant In addition to the Filter located at the Folder level, you can define more precise filtering depending on the CW measurement file © Forsk 2010 Confidential – Do not share without prior permission Slide 27 of 54 CW Measurements Pre-processing Filtering assistant (1/2) Display of M = f ( 10log(D) ) Selection rectangle simultaneous Signal/Distance filtering Possibility to keep the selected points or to exclude them Signal/Distance filtering according to the selection rectangle Azimuth filtering on the measurement points © Forsk 2010 Selection ec ang e Confidential – Do not share without prior permission Slide 28 of 54 CW Measurements Pre-processing Filtering assistant (2/2) Remaining points after the Distance, Signal level, Azimuth and Clutter classes filtering Remove all previous filters applied © Forsk 2010 Confidential – Do not share without prior permission Slide 29 of 54 CW Measurements Pre-processing Final filtering (1/2) Display each CW measurement according to their Measured signal level Check that propagation loss is spatially homogeneous © Forsk 2010 Confidential – Do not share without prior permission Slide 30 of 54 CW Measurements Pre-processing Final filtering (1/2) Removing which points? Sudden drop of signal level How? Delete from the CW measurement table Draw Filtering zones © Forsk 2010 Confidential – Do not share without prior permission Slide 31 of 54 Calibration / Verification Stations Display measurement routes after pre-processing Calibration stations a ons so a measuremen s cover e w o e area Avoid keeping stations with a lot of common points Verification stations Stations so that measurements are inside covered area (not at edges) Major part of their covered areas are also covered by calibration stations How many © Forsk 2010 If 8 measured stations If < 8 measured stations 6 for calibration; 2 for verification all stations used for calibration verification performed with same stations Confidential – Do not share without prior permission Slide 32 of 54 Initial Model General SPM formula Lmodel = K1 + K 2 .log (d ) + K 3 .log (HTxeff ) + K 4 .Diffraction Loss + K 5 .log (d ).log (HTxeff ) + K 6 .(H Rxeff ) + K7 .log (H Rxeff ) + K clutter .f (clutter ) + K hill, LOS Let K6 = 0 Others will be calibrated Effective antenna height Choose method according to terrain relief Modify height from transmitter properties Can be selected by the calibration process Recommendation if terrain is hilly “Enhanced slope at receiver” method Hilly terrain correction “1-YES” Recommendation if terrain is flat “Height above average profile” method Hilly terrain correction “0-NO” © Forsk 2010 Confidential – Do not share without prior permission Slide 33 of 54 Initial Model Max distance Forced to 0 during calibration If >0 no continuity ensured Kclutter = 1 is recommended Multiplying factor of clutter losses Minimum loss = Free space loss Avoid unrealistic values Profiles Radial optimisation quicker © Forsk 2010 Confidential – Do not share without prior permission Slide 34 of 54 Initial Model Heights of Clutter taken or not into account in Diffraction Then put “1-YES” in the box If you only have a Clutter classes File 2 approaches: If Clutter Classes file has a very fine resolution • • You can put “1-YES” and the tool will take into account the average heights defined in your clutter classes file you should keep all the losses per clutter class to Zero If Clutter Classes file resolution is low • Do not take into account the average heights defined in your clutter classes file (“0-NO”), but instead add a Loss per Clutter class type Receiver on top of clutter By default “No” Only useful for fixed receivers © Forsk 2010 Confidential – Do not share without prior permission Slide 35 of 54 Initial Model Clutter Classes Losses can be calibrated You need to define the max distance from the Receiver (towards the Transmitter) for which the different clutter classes will be considered Choice between 4 t es of Wei htin functions Uniform Trian ular Lo arithmic Exponential) n f (clutter ) = ∑ Li w i i =1 wi=f(d'i) Uniform Triangular Logarithmic Exponential wi d'i © Forsk 2010 Confidential – Do not share without prior permission Slide 36 of 54 Initial Model Reference model Create a Reference model containing all the previous settings , When duplicated, choose an appropriate name and pay specific attention to: • • • • • Methods used for Diffraction and Effective Antenna Height calculation value of Kclutter Hilly terrain correction Heights of Clutter considered or not in Diffraction Clutter Range and associated Weighting function Start from the Reference model for each calibration trial © Forsk 2010 Confidential – Do not share without prior permission Slide 37 of 54 Calibration Wizard Automatic calibration overview Algorithm based on solving a least-squares problem Calculation of the best solution in terms of root mean square : , RMS = δ 2 M 2 + First Step Selection of calibration stations © Forsk 2010 Confidential – Do not share without prior permission Slide 38 of 54 Calibration Wizard Second step (1/2) Selection of the Parameters to calibrate Possibility to modify their ranges © Forsk 2010 Confidential – Do not share without prior permission Slide 39 of 54 Calibration Wizard Second step (2/2) Recommended ranges Constant Min Max K1 0 100 K2 20 70 K3 -20 20 K4 0 1 K5 -10 0 K7 -1 It is recommended to leave K6 to 0 © Forsk 2010 Confidential – Do not share without prior permission Slide 40 of 54 Calibration Wizard Final step Display of Before and After Parameters values and Statistics Commit will update the model you are calibrating with the new values of Ki, height and diffraction methods as well as the Clutter Losses © Forsk 2010 Confidential – Do not share without prior permission Slide 41 of 54 Final Model Extrapolate non-calibrated clutter losses (1/2) Non-calibrated clutter classes must not have their clutter losses left to 0 Could lead to high error where these classes are present Must be extrapolated from: Calibrated clutter losses (from other propagation model) Typical losses (here centred on the Urban class) © Forsk 2010 Clutter class Typical loss Dense Urban from 4 to 5 Woodland from 2 to 3 Suburban from -5 to -3 Industrial from -5 to -3 Open in urban from -6 to -4 Open from -12 to -10 Water from -14 to -12 Confidential – Do not share without prior permission Slide 42 of 54 Final Model Extrapolate non-calibrated clutter losses (2/2) Centre clutter losses Relative difference between clutters kept unchanged Example: After calibration, model centred on suburban: K1=17.4 Losses: Dense Urban = 6.5 Wood = 5.7 Urban = 3.5 Suburban = 0 Apply scaling factor apt typ ca osses or ca -12 Open -8 Extrapolated © Forsk 2010 After centring, new values: K1=20.9 Losses: Dense Urban = 3 Wood = 2.2 Urban = 0 Suburban = -3.5 rate ones com ng rom ot er mo e to t e ca C 0 e n t Urban r e d 0 calibrated rate mo e 4.5 Typical Losses Dense Urban “MyModel” Losses 3 calibrated Confidential – Do not share without prior permission Define Scaling Factor Slide 43 of 54 Training Programme 1. SPM Calibration Concepts . u e nes or easurement urveys 3. Working with CW Measurements 4. Automatic Calibration Method 5. Analysing the Calibrated Model 6. Calibration Process Summary © Forsk 2010 Confidential – Do not share without prior permission Slide 44 of 54 5. Analysing The Calibrated Model Statistics (1/2) Apply the new calibrated propagation model to your CW sites © Forsk 2010 Confidential – Do not share without prior permission Slide 45 of 54 5. Analysing The Calibrated Model Statistics (2/2) Check the Quality Targets (Std Deviation and Mean Error values) on the Calibration and Verification sites Statistics available Globall per Clutter class, per Transmitter and per Measurement path Possibility to run the Statistics on all the Measurement paths, or on specific ones © Forsk 2010 Confidential – Do not share without prior permission Slide 46 of 54 5. Analysing The Calibrated Model Correlation (to be checked on the Calibration sites) Through the Assisted Calibration Wizard Displays, for each parameters to be calibrated (K1, K2, K3, etc.), the correlation of the variables lo D lo Heff Diff etc. with the lobal Error Check if the Correlation values are between -0,1 and +0,1 The calibration wizard will attempt to bring the correlation as close to zero as possible. The results will be a correction value that will be added or subtracted to the initial Ki value in the model Commit will apply the Correction values to the corresponding Ki values Notes: This will not take into account the Ki Ranges © Forsk 2010 Confidential – Do not share without prior permission Slide 47 of 54 5. Analysing The Calibrated Model Display Error Recalculate the Predicted signal values (P) according to the calibrated propagation model Display the Error (P – M) between the CW Measurements values (M) and the Predicted values P © Forsk 2010 Confidential – Do not share without prior permission Slide 48 of 54 5. Analysing The Calibrated Model Display CW Measurements & associated Signal Level study Use the same shading on both displays to be able to compare them For each site, one by one Check the global behaviour of calibrated model © Forsk 2010 Confidential – Do not share without prior permission Slide 49 of 54 5. Analysing The Calibrated Model CW measurement and Profile windows Analysis along the path © Forsk 2010 Confidential – Do not share without prior permission Slide 50 of 54 Training Programme 1. SPM Calibration Concepts . u e nes or easurement urveys 3. Working with CW Measurements 4. Automatic Calibration Method 5. Analysing the Calibrated Model 6. Calibration Process Summary © Forsk 2010 Confidential – Do not share without prior permission Slide 51 of 54 Calibration Process Summary Before starting... Check Geographical Database quality & accuracy (DTM, clutter, vectors...) Define environments (hilly, flat / urban, rural...) to specify the required number of propagation models to be calibrated Measurements preparation Sites selection Survey roads Fulfil radio criteria Make & Average measurements Create Transmitters used for measurements in the Atoll document With exact configuration (coordinates, antenna type & height, EIRP, losses) Analyse & Filter measurements ( Pre-processing) Keep representative points and remove suspicious ones Choice of calibration / verification sites © Forsk 2010 Confidential – Do not share without prior permission Slide 52 of 54 Calibration Process Summary Run the automatic calibration Display statistics and compare results with target values (Std deviation and Mean for calibration sites: Global and Individual checking for verification sites: Global checking Extrapolate non-calibrated clutter losses Analyse calibrated model Display statistics h k rr la i n Maps displaying Error(P-M), Measurements & Signal Level Study, etc. Apply the calibrated model Apply resulting standard deviation per clutter in the clutter class description Apply the calibrated model to network’s transmitters (Transmitter Properties\Propagation tab) © Forsk 2010 Confidential – Do not share without prior permission Slide 53 of 54 THANK YOU!
