Propagation cnp
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Propagation cnp Presentation Transcript

  • 1. Propagation Models & Scenarios:Hybrid Urban  Indoor© 2012 by AWE Communications GmbH www.awe-com.com
  • 2. Contents • Overview: Propagation Scenarios • Scenario: Rural and Suburban Pixel Databases (Topography and Clutter) • Scenario: Urban Vector databases (Buildings) and pixel databases (Topography) • Scenario: Indoor Vector databases (Walls, Buildings) • Combined Network Planning Hybrid Rural  Urban  Indoor Scenarios Pixel and Vector Databases2012 © by AWE Communications GmbH 2
  • 3. Propagation Models Propagation Scenarios (1/2) Different types of cells in a cellular network • Macrocells • Cell radius > 2 km • Coverage • Microcells • Cell radius < 2 km • Capacity (hot spots) • Picocells • Cell radius < 500 m • Capacity (hot spots)2012 © by AWE Communications GmbH 3
  • 4. Propagation Models Propagation Scenarios (2/2) Macrocell Microcell Picocell Vector data Database type Raster data Vector data Raster data Topography 2.5D building (vector) 3D building Database Clutter Topography (pixel) 3D indoor objects Hata-Okumura Knife Edge Diffraction Motley Keenan Path Loss Two Ray COST 231 WI COST 231 MW Prediction Models Knife Edge Diffraction Ray Tracing Ray Tracing Dominant Path Dominant Path Dominant Path r < 30 km r < 2000 m Radius r < 200 m r > 2 km r > 200 m2012 © by AWE Communications GmbH 4
  • 5. Propagation Models Propagation Models • Different types of environments require different propagation models • Different databases for each propagation model • Projects based on clutter/topographical data or vector/topographical data • Empirical and deterministic propagation models available • CNP used to combine different propagation environments Types of databases • Pixel databases (raster data) • Topography, DEM (Digital Elevation Model) • Clutter (land usage) • Vector databases • Urban Building databases (2.5D databases  polygonal cylinders) • Urban 3D databases (arbitrary roofs) • Indoor 3D databases2012 © by AWE Communications GmbH 5
  • 6. Combined Scenarios (Urban  Indoor) Combined Network Planning (CNP): urban  indoor Motivation (1/2) • Penetration into buildings with complex structure inside • Transmitters located inside buildings (micro BTS, Repeater, WLAN, …) interfering with outdoor network Modeling whole scenario in indoor mode? Computational demand too high for large scenarios!2012 © by AWE Communications GmbH 6
  • 7. Combined Scenarios (Urban  Indoor) Combined Network Planning (CNP): urban  indoor Motivation (2/2) • Indoor penetration If transmitter located outdoor indoor walls should be considered  but two environments involved (urban & indoor)  which propagation environment should be used? • Radiation from indoor transmitters and interference with outdoor environment If transmitter located indoor (e.g. repeater) the interference with the outdoor environment of interest  but two environments involved (urban & indoor)  which propagation environment should be used?2012 © by AWE Communications GmbH 7
  • 8. Combined Scenarios (Urban  Indoor) CNP Prediction: urban  indoor • Combination of urban and indoor prediction • Dynamic resolution of results: Indoor higher resolution than urban • Automatic adaptation of parameter settings (path loss exponents, interaction losses,..) if a transition between urban and indoor environment occurs • Multiple transition from indoor  outdoor  indoor are possible to include e.g. the indoor penetration 3D Mode into a different building from an  Multiple prediction layers analyzed indoor transmitter  Path finding in 3D  Highly accurate2012 © by AWE Communications GmbH 8
  • 9. Combined Scenarios (Urban  Indoor) CNP Database: urban  indoor • Shape around indoor database (polygonal cylinder) • Indoor database (with indoor walls and objects) is imported into urban building database • Shape of indoor database represents the building when using the urban propagation model • Rays are handled by using the Angular Power Delay Profile (APDP) for the transition between the models (includes field strength, delay time, angles of incidence)  Allows the prediction of delay spread and impulse response2012 © by AWE Communications GmbH 9
  • 10. Combined Scenarios (Urban  Indoor) CNP Database: urban  indoor • Urban database (polygonal cylinders) of the surrounding environment can be saved in indoor data format (i.e. as polygonal planar objects) for CNP database • Indoor databases (with walls inside buildings) can be imported into the urban database to substitute selected shapes of buildings by their indoor structure • The resulting database is saved as urban database and the project is also handled as urban propagation project (incl. the (indoor walls of selected buildings)2012 © by AWE Communications GmbH 10
  • 11. Combined Scenarios (Urban  Indoor) CNP Prediction: urban  indoor • Rays in urban scenario reaching the shape of the indoor database are followed in the other environment with the corresponding propagation model • Multiple transition from indoor  outdoor  indoor are possible to include e.g. the indoor penetration into a different building from an indoor transmitter • Transition COST 231 WI  COST 231 MW is possible • Transition Urban Dominant Path  Indoor Dominant Path is possible • Transition IRT Urban  COST 231 MW is possible • Transition IRT Indoor  IRT Urban is possible • Handled in urban project • If indoor walls at a building are detected the indoor coverage is computed with consideration of the indoor walls • If transmitter is located inside building and if indoor walls of this building are available the CNP module is automatically activated2012 © by AWE Communications GmbH 11
  • 12. Combined Scenarios (Urban  Indoor) Examples CNP urban  indoor Indoor coverage for outdoor transmitter2012 © by AWE Communications GmbH 12
  • 13. Combined Scenarios (Urban  Indoor) Examples CNP indoor  urban Outdoor coverage for indoor transmitter2012 © by AWE Communications GmbH 13
  • 14. Combined Scenarios (Urban  Indoor) Example urban  indoor: Base Station on Top of Building Indoor coverage for outdoor transmitter2012 © by AWE Communications GmbH 14
  • 15. Combined Scenarios (Urban  Indoor) Example indoor  urban: WLAN AP inside Building Outdoor coverage for indoor transmitter2012 © by AWE Communications GmbH 15
  • 16. Combined Scenarios (Urban  Indoor) Example: Indoor  Urban Omni-directional antenna in the highest floor of an office building Computed with the Dominant Path Model2012 © by AWE Communications GmbH 16
  • 17. Combined Scenarios (Urban  Indoor) Example: Indoor  Urban Omni-directional antenna in the highest floor of an office building Computed with the Dominant Path Model2012 © by AWE Communications GmbH 17
  • 18. Combined Scenarios (Rural  Urban  Indoor) Example: Rural (Topo) / Urban (Buildings) / Indoor (Walls) Omni-directional antenna on a hill in the Hong Kong area2012 © by AWE Communications GmbH 18
  • 19. Combined Scenarios (Rural  Urban  Indoor) Example: Rural (Topo) / Urban (Buildings) / Indoor (Walls) Coverage inside a building (multiple floors) due to an omni-directional antenna on a hill in the Hong Kong area2012 © by AWE Communications GmbH 19
  • 20. Combined Scenarios (Urban  Indoor) Evaluation with Measurements Investigated Scenario: I. Campus of University of Stuttgart, Germany2012 © by AWE Communications GmbH 20
  • 21. Combined Scenarios: Evaluation Scenario I: Campus of University of Stuttgart, Germany Penetration Scenario! Scenario Information Material concrete and glass Total number of objects 1893 Number of walls 1004 Resolution 1.0 m Transmitter height 40.0 m 3D view of database Prediction height 17.0 m2012 © by AWE Communications GmbH 21
  • 22. Combined Scenarios: Evaluation Scenario I: Campus of University of Stuttgart, Germany Prediction with 3D Prediction with 3D Dominant Path Model Dominant Path Model for transmitter 3 for transmitter 42012 © by AWE Communications GmbH 22
  • 23. Combined Scenarios: Evaluation Scenario I: Campus of University of Stuttgart, Germany Difference of prediction with DPM and Difference of prediction with DPM and measurement for transmitter 3 measurement for transmitter 4 Statistical Results for Dominant Path Model Site Mean Value [dB] Std. Dev. [dB] Comp. Time [s] 3 0.90 5.43 154 4 4.26 7.48 156 Remark: Standard PC with an AMD Athlon64 2800+ processor and 1024 MB of RAM2012 © by AWE Communications GmbH 23
  • 24. Summary Features of WinProp Hybrid Urban  Indoor Module • Highly accurate propagation models Empirical: Multi Wall Deterministic (ray optical): 3D Ray Tracing, 3D Dominant Path Arbitrary number of transitions (from indoor to urban and vice versa) within one path Optionally calibration of 3D Dominant Path Model with measurements possible • Building data Models are based on 3D vector (CAD) data (indoor) and 2.5D vector building data (urban) Consideration of material properties (also subdivisions like windows or doors) • Antenna patterns Either 2x2D patterns or 3D patterns • Outputs Predictions on multiple heights simultaneously Signal level (path loss, power, field strength) Delays (delay window, delay spread,…) Channel impulse response Angular profile (direction of arrival)2012 © by AWE Communications GmbH 24
  • 25. Further InformationFurther information: www.awe-com.com2012 © by AWE Communications GmbH 25