Lecture 3: Propagation Modelling

1. Lecture 3:Propagation Modelling Anders Västberg 08-790 44 55 vastberg@kth.se

2. Ionospheric propagation [Slimane]

3. Refraction in an ionospheric layer [Slimane]

4. Electron density profile [Slimane]

5. Ray paths

6. Cellular Networks • Network organised in cells • Each access point has a set of channels to service the users within the cell • The set of channels can be reused when the signal to interference ratio is low enough.

7. Macrocells • Give services in urban, suburban and rural areas. The cell radii varies from about 1 km to many tens of km. • Few users per area unit. • Base stations antennas are mounted on high buildings or on masts to get better coverage.

8. Microcells • In urban or suburban areas • Cell radii is approximately 500 m • Very high traffic density (many users per area unit). • Antennas mounted lower than the buildings around it to decrease the cell coverage are • More cells/unit area can services more users.

9. Indoor Cells (Picocells) • High data rates and high traffic densities for both mobile and fixed users • Coverage area influenced by • Layout of the building • Construction material (wood transparent to radio waves, well reinforced concrete is not). • Shape of rooms

10. Propagation modelling • To predict coverage areas in mobile cellular telephone systems, simple propagation models are needed. • Empirical methods • Physical models • Hybrid methods

11. Measurements [Saunders, 1999]

12. Emperical methods • Models are usually based on actual path loss measurements. • Curve fitting is used to obtain an analytical function for the model. • Parameters are given by: distance, frequency, antenna heights, distance to nearest building. • Validity of the model may be limited (dependent on the environment) • Models are practical and easy to use but not very accurate.

13. Physical Models • A physical model needs a very detailed description of the terrain and other clutter. • Large amount of data needed. • Excessive computational effort needed. • The important parameter for the macrocell designer is the area covered, not the field strength at particular locations.

14. Computerised Planning Tools • The enormous increase in the need to plan cellular systems accurately and quickly • The development of fast, affordable computing resources • The development of geographical information systems • Example: • TEMS CellPlanner, Ericsson AB

15. Empircal Models for Macro Cells • Power Law models • Clutter factor models • Okumura-Hata model • Cost 231-Hata Model

16. Plane Earth Loss [Saunders, 1999]

17. Physical Models for Macro Cells • Ikegami Model • Rooftop diffraction • Flat Edge model • Walfisch-Bertoni model • COST 231/Walfisch-Ikegami model

18. Models for Micro Cells • Dual Slope model (empirical model) • Physical Models • Two-ray model • Street canyon models • Non-line-of-sight models

19. Picocells • Wall and floor factor models • COST231 Multi-wall model • Ericsson model • COST 231 Line-of-sight model • Floor Gain Models • COST 231 Non-Line-of Sight model

20. Physical Model: Two Ray Model [Saunders, 1999]

21. Two-Ray Model R is the Fresnel reflection coefficient

22. Raytrace [Saunders, 1999]

23. Indoor models