Development of a Propagation Prediction Software Tool for VHF

1. Development of a Propagation Prediction Software Tool for VHF/UHF Terrestrial Wireless Communications Systems Phillip Maher IPS Radio and Space Services, Sydney NSW p-maher@ips.gov.au

2. Software Aims Development of a tool for modeling VHF/UHF radio propagation. Modeling the physical layer of Broadcast communications systems. Cellular mobile communications systems. Focus on the effect terrain has on signal strength estimates via Empirical pathloss models. Semi deterministic pathloss models. Reliance on Digital Elevation Models that provide topographical and morphology data input to the propagation models.

3. Digital Elevation Models and Raster Imagery Main input data source being DEM (Digital Elevation Models) derived from Satellite and LIDAR sources. DEM’s measure the highest point below a nominal observer hovering the earth (data can include buildings and trees). Imported into software in square tile or irregular format. Variable resolution from 5m to 1km. Scaled colour raster image (bitmap) representation in the GUI. Project developed in C/C++ within Borland Builder.

4. Mapping and Coordinate Systems GIS requirements for use on Australian terrain data. Incorporating MGA94 (Map Grid of Australia) and the GDA94 (Geodetic Datum of Australia) which uses the Universal Transverse Mercator System for projections. Operations to perform conversions between Grid coordinates (Eastings/Northings) and Geographical (Latitude/Longitude) using Redfearn’s formulae. Distance and Height Scale factors for accurate distance calculations on the ellipsoid.

5. Bitmap Profiling Profiling tool for use on all raster images. Profiles created by line intersection algorithm between pixel values and simple linear interpolation for intermediate values. Height and distance values of terrain cross section passed through convex hull algorithm to produce diffracting radio path. Profiling performed on terrain for propagation models Fresnel zone clearance and LOS obstruction testing. Also applied to simulation results e.g. observing cell boundaries for cellular systems.

6. Empirical Propagation Models ITU recommended Empirical Pathloss models such as Okumura-Hata and Longely-Rice Okumura-Hata model variations for Large Cities, Medium Cities, Suburban Area and Open/Rural Areas. Valid for 150MHz < f < 1500MHz 30m < Htx <200m 1m < Hrx <10m 1km < d <20km COST 231 Hata model for 1500MHz-2000MHz.

7. Knife Edge Diffraction Semi Deterministic pathloss models employ knife edge diffraction for evaluating hilly terrain and finding losses in shadowed regions. A terrain cross section profile is produced between the Tx and Rx which is then passed through a convex hull function to find diffracting radio path. Decision calculations based on the knife edge model are performed to produce the Fresnel-Kirchoff diffraction parameter ?. Fresnel-Kirchoff parameter then substituted into Lee’s approximation of attenuation over single diffracting edge.

8. Semi Deterministic Propagation Models

9. Antenna modeling Vertical and Horizontal gain patterns loaded in from a manufacturers antenna data file. Pattern multiplication performed for a approximate 3D representation. Full gain pattern then incorporated into propagation model via a simple raytrace function and added to the pathloss equation. Mechanical rotation and tilting of the patterns.

10. Simulation Results. Each simulation is performed over an area where the transmitter is located in the middle of variable sized square region. Individual transmitters can be modeled using the variety of propagation models. Transmitters operating on similar frequencies over a network, or those that may interfere - can be modeled to produce a “least” pathloss result. Full range of attributes such as tx height, Rx heights, and antenna frequency/power/bandwidth.

11. Simulation Types Variable colour scale for results with selectable upper and lower limits and quantisation step. Calculations carried out for Pathloss Field Strength Signal-to-noise ratio (SNR) Signal to noise ratio – flat noise modeling via simple thermal noise model for No Comparisons available with data sheets from broadcast TV station field strength estimate.

12. Future Work Network analysis functions for 2G, 3G and future mobile communication systems and broadcasting systems. Smart antenna modeling. Incorporating vector data of buildings/structures for small cell modeling via semi deterministic propagation models : Walfish-Ikagami deterministic propagation models: Raytracing Modeling of mobile transmitter scenarios. Calibration mode for feeding in actual field data to fine tune propagation models. Incorporating RadCom database for interference and spectrum management.