Propagation indoor

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<ul><li> 1. IndoorScenarios 2012 by AWE Communications GmbH</li></ul><p> 2. Contents Building DatabasesPixel or vector databases Wave Propagation Model Principles- Multipath propagation- Reflection- Diffraction- Scattering- Antenna pattern Propagation ModelingPropagation models and prediction of path loss (ProMan) Network PlanningPlanning of indoor wireless networks (ProMan) Comparison to MeasurementsComparison to measurements in different types of buildings by AWE Communications GmbH 2 3. Building DatabasesDatabases: Pixel or Vector?Pixel Databases 3D Vector Databases Formats: jpg, bmp, gif, tiff, Formats: dxf, dwg, stl, nas, 2D approach (propagation in Rigorous 3D approach horizontal plane only) Single or multiple floors Colors represent materials Different materials Multiple floors (bitmaps) possible Subdivisions (doors, windows) Powerful graphical editor for building databases: WallMan by AWE Communications GmbH3 4. Building DatabasesDatabases: 3D Vector Building Databases 3D vector oriented database Walls as planar objects with _ polygonal shape Arbitrary location and orientation in space Individual material properties Subdivisions with different material properties to model doors and windows by AWE Communications GmbH 4 5. Building DatabasesDatabases: 3D Vector Building DatabasesSpecial featuresWall material properties to modelMaterial: Concrete (e.g. Glass). Subdivision 2 Subdivision defined as Hole to Subdivision 3 Material:model openings in wallsGlass Material: NoneSubdivision 1 Arbitrary number of subdivisions Material: per wall Wood Subdivisions cannot intersecteach other by AWE Communications GmbH 5 6. Building DatabasesDatabases: Material Properties Global material catalogue for different frequency bands(In WallMan via menu Edit Materials used in Database Import) User can select and add materials by AWE Communications GmbH6 7. Building DatabasesDatabases: Material Properties Local material database (in building database) only relevant for objects in this database independent of global material catalogue (modification of global catalogue does not affect material properties of objects in database) can be updated with materials from global material catalogue Settings of local material database individual material properties for different frequency bands (always the properties of the frequency band closest to TX frequency is used) Material (incl. all properties) is assigned to objects (walls/buildings) Always all material properties must be defined even if they are not required for the selected propagation model Individual colors can be assigned to the materials for better visualization by AWE Communications GmbH7 8. Building DatabasesDatabases: Material Properties Properties of a material for individual frequency bands Properties affecting all propagation models (except One Slope and Motley)Transmission Loss (in dB) Properties affecting Dominant Path ModelReflection Loss (in dB) Properties affecting Ray Tracing GTD/UTD related properties Relative Dielectricity Relative Permeability Conductance (in S/m) Empirical reflection/diffraction model Reflection Loss (in dB) Diffraction Loss Incident Min (in dB) Diffraction Loss Incident Max (in dB) Diffraction Loss Diffracted (in dB) by AWE Communications GmbH8 9. Building DatabasesDatabases: Non-deterministic Objects/Furniture Possibility to define areas with non-deterministic objects (polygonal cylinders) Propagation paths inside these areas get higher attenuation depending on the length of the path inside the object Mobile stations located inside these objects will also get a higher path loss assignedWithout furniture and personsDeterministic modeling Non-deterministic modeling by AWE Communications GmbH 9 10. Building DatabasesDefinition of (multiple) Floors in WallMan Definition of floors in WallMan by user (heights of each floor and ceiling) For each floor different bitmap (i.e. floor layout) can be used Fast access to floors by mouse Drawing of (vertical) objects can be optionally restricted to floor height by AWE Communications GmbH 10 11. Building DatabasesSelection of Floor in ProMan Floors read from database (as defined in WallMan) Fast access to floors by selection from drop-down list Predictions either on all floors or on selected floor only (prediction height is defined relative to floor/s) Antennas can be hidden on display if not mounted on the selected floor Display of prediction results either in 2D or 3D by AWE Communications GmbH 11 12. Propagation ModelingPropagation Models One Slope Model Only distance dependency Path loss exponent is dominant parameter Motley Keenan ModelCOST 231 Multi Wall All walls have identical attenuation COST 231 Multi-Wall-Model Only direct ray between Tx and Rx Individual attenuation of each wall(transmission loss of wall) Ray Tracing Ray Tracing 3D Ray Tracing (IRT, with preprocessing) 3D Ray Tracing (SRT, without preprocessing) Dominant Path Model 3D (Multiple floors)Dominant Path by AWE Communications GmbH 25 13. Propagation ModelingPropagation Models: COST 231 Multi Wall Model Principle of model: Based on direct ray between transmitter and receiver Free space loss (one slope) with additional loss due to transmission of walls Individual material properties of each wall consideredComputation of field strength: L T3Receiver r3L T2 21L T1Transmitter by AWE Communications GmbH26 14. Propagation ModelingPropagation Models: Ray Tracing Multipath propagation considered Dominant effects: diffraction, reflectionand transmission (penetration) Ray with up to 6 reflections and2 diffractions (and arbitrary number oftransmissions / penetrations) aredetermined in different combinations Full 3D approach Uncorrelated or correlatedsuperposition of contributions (rays) Supports only vector databases Two sub-modes: 3D IRT: Incl. single pre-processing of building data andaccelerated predictions 3D SRT: Without any pre-processing by AWE Communications GmbH27 15. Propagation ModelingPropagation Models: Intelligent Ray Tracing (IRT) Considerations to accelerate the time consuming process of path finding: Deterministic modelling generates a large number of rays, but only few of them deliver most of the energy Visibility relations between walls andedges are independent of transmitterlocation Adjacent receiver pixels are reached by rays with only slightly different paths Single pre-processing of the building database with determination of the visibility relations between buildings reduces computation time by AWE Communications GmbH28 16. Propagation ModelingPropagation Models: Intelligent Ray Tracing (IRT) Pre-processing of the Building Database Subdivision of the walls into tiles Subdivision of the vertical andhorizontal edges into segments min Subdivision of the prediction areainto receiving points (grid) max min stored information for each visibility relation:max angle between the elements distance between centres example: visibility between a tile and areceiver pixel Tile Prediction Pixel projection of connecting straight linesSegmentCenter of Tileinto xy-plane and perpendicular plane Center of horiz. Segm.Center of vert. Segm. 4 angles for each visibility relation by AWE Communications GmbH29 17. Propagation ModelingPropagation Models: Intelligent Ray Tracing (IRT) Prediction with Pre-processed Data Determination of all tiles, segments and receiving points, which are visible from the transmitter Computation of the angles of incidence belonging to these visibility relations PREDICTION Recursively processing of Direct ray all visible elements incl. consideration of the1.interaction PREPRO- angular conditionsCESSING Tree structure is very fast and efficient2.interaction 3.interactiontransmitterreceiving pointtile / segment by AWE Communications GmbH 30 18. Propagation ModelingPropagation Models: Dominant Path Model Dominant Path (single path or group of Typical Indoor Channel Impulse Responsepaths) Unlimited number of interactions (changesOne pathof orientation) along the pathdominates Parameters of path determined (e.glength, number of interactions, angles,.)and used to compute path loss with semi-deterministic equations Optional consideration of wave guidingpossible (wave guiding factor, based onreflection loss of walls) No pre-processing required Accurate and fast Auto-calibration available TT T Robust against errors in vector buildingRR Rdatabase empiricalray-opticaldominantmodel model path model by AWE Communications GmbH 31 19. Propagation ModelingPropagation Models: Dominant Path ModelDetermination of Paths Analysis of types of walls in scenario0I J4Generation of tree with walls 23D B F L5 M O0 A Searching best path through walls S 0 T G N1 dP Computation of path lossa X U Q9 8 7 6 b Y V R Tc Z W S0 Transmitter1ABC D H I J K L Layer 1 2 2 33 5 6 7 8 9 B AD F E C F E............ Layer 2 1 11 4 5 1 4 5C D H I J K L............ Layer 3 3 3 5 6 7 8 9 ............ by AWE Communications GmbH32 20. Propagation ModelingPropagation Models: Dominant Path ModelComputation of Path Loss Path length l Wavelength Path loss exponent p Individual interaction losses f(,i) for each interaction i of all n interactions Penetration loss tj for all m transmissions through walls Gain due to waveguiding 4 L 20 log 10 p log l f , i t j nm i1j 1 by AWE Communications GmbH33 21. Propagation ModelingPropagation Models: Dominant Path ModelParameters for prediction (2/2) Different LOS states Definition of different path loss exponents p for LOS (line of sight) NLOS OLOS (obstructed line of sight =&gt; no transmission through a wall) NLOS (non line of sight =&gt; at least oneOLOSTX LOS transmission through a wall) Interaction losses (effective attenuationdepends on angle of incident and diffracted ray)Waveguiding Wave guiding effectTX by AWE Communications GmbH34 22. Propagation ModelingPropagation Models: ComparisonCOST 231Ray Tracing (3D IRT) Dominant Path (3D) Computation time: &lt; 1 min Computation time: &lt; 1 min Computation time:&lt; 1 min Preprocessing time: nonePreprocessing time: 10 minPreprocessing time: none Not very accurate High accuracy in region of Tx High accuracy also far Limited accuracy far away away from Tx by AWE Communications GmbH 35 23. Propagation Modeling Leaky Feeder CablesLeaky Feeder Models: ComparisonShortest Distance Model Smallest Transmission Loss Smallest Path Loss Model Shortest distance between Based on transmission loss Based on path loss cable and receiver evaluation for discrete Tx evaluation for discrete Txpoints along the cable points along the cable Loss due to transmission of(definable discretization) (definable discretization) intersected walls (optional with angle of incidence)Selection of path with Selection of path withsmallest transmission loss smallest path loss Additional distance loss due to propagation (path loss Loss due to transmission of Loss due to transmission of exponents) intersected walls (optionalintersected walls (optionalwith angle of incidence) and with angle of incidence) anddistance depending lossdistance depending loss by AWE Communications GmbH 36 24. Indoor: Sample PredictionsPropagation Models: Multi Layer Predictions 3D Dominant Path Multi Layer PredictionPrediction on multiple floors are possiblewith all indoor prediction models in WinProp. by AWE Communications GmbH37 25. Indoor: Sample PredictionsBuildings: Arbitrary Prediction PlanesPrediction planes not only horizontal, but arbitrarily locatedExample: Prediction in staircases inside a building by AWE Communications GmbH38 26. Indoor: Sample PredictionsBuildings: Prediction on SurfacesCoverage computed on the surfaces of buildings in an urban scenario by AWE Communications GmbH39 27. Indoor: Sample PredictionsTunnels: Prediction inside Tunnel Scenarios Separate tool for defining tunnel databases based on cross sections and track Tunnel database can be modified in WallMan Coverage prediction and networkplanning in ProManCoverage predictions inside tunnel scenarios by AWE Communications GmbH40 28. Indoor: Sample PredictionsStadium: Computed with Indoor Ray TracingPrediction of thecoverage on upper and lower tiersinside a stadium by AWE Communications GmbH 41 29. Indoor: Sample PredictionsAirport: Computed with Indoor Ray TracingPrediction of theradio link between anairplane and the tower by AWE Communications GmbH 42 30. Indoor: Sample PredictionsMetro Station: Computed with Dominant Path Model Prediction of the W-LAN coverage in a METRO station (two trains arriving) by AWE Communications GmbH 43 31. Indoor: Sample PredictionsMetro Station: Computed with Dominant Path Model Prediction of the W-LAN coverage in a METRO station (two trains arriving) by AWE Communications GmbH 44 32. Indoor: Sample PredictionsHighway (VANET): Computed with Ray TracingCar2Car communications:Prediction of the mobile radiochannel for VANETs by AWE Communications GmbH 45 33. Indoor: Sample PredictionsVehicles: Computed with Ray TracingRadio links to transmit sensors dataCoverage of a wireless sensor insideinside vehicles a vehicle by AWE Communications GmbH 46 34. Indoor: Sample PredictionsKeyless Entry: Computed with Ray TracingAnalysis of the radio channel forkeyless go systems by AWE Communications GmbH 47 35. Indoor: Sample PredictionsKeyless Entry: Computed with Ray TracingNumber of received sub-carriers Analysis of the coverage areain an UWB radio system for for keyless go systems keyless go by AWE Communications GmbH 48 36. Indoor EvaluationEvaluation with Measurements Investigated Scenarios:I. Institute for Radio Frequency Technology, University of StuttgartII.University of Vienna, Vienna, AustriaIII. Institute of Telecommunications, LisbonIV.Institute of Radio Frequency Engineering, University of Vienna, AustriaV. Whittemore Hall of the Virginia State UniversityVI.Villa of Guglielmo Marconi, Bologna by AWE Communications GmbH 49 37. Indoor Evaluation Scenario I: Institute for Radio Frequency Technology, University of Stuttgart, Germany Typical modern office building !Scenario InformationMaterial concrete and glass Total number of objects353Number of walls 170 Resolution0.50 m0.90 m, 20 dBm,Transmitter 1800 MHz3D view of the modern office buildingPrediction height0.90 m by AWE Communications GmbH 50 38. Indoor Evaluation Scenario I: Institute of Radio Frequency Technology, University of Stuttgart, GermanyTransmitter location 1Transmitter location 2 Transmitter location 6Transmitter location 12 by AWE Communications GmbH51 39. Indoor Evaluation Scenario I: Institute of Radio Frequency Technology, University of Stuttgart, GermanyPrediction with Multi- Prediction with 3D Ray Prediction with Indoor Wall Model forTracing Model forDominant Path Modeltransmitter 1 transmitter 1for transmitter 1 by AWE Communications GmbH52 40. Indoor Evaluation Scenario I: Institute of Radio Frequency Te...</p>


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