Table 1 Measured and re-simulated state probabilities and state correlation coefficients using different dual-satellite state models for an exemplary scenario: urban, elevation1 = 45°, elevation2 = 25°, azimuth separation = 45° (g… ‘good’-state, b… ‘bad’-state, gb … ‘good bad’-state, etc.)
From: State modelling of the land mobile propagation channel for dual-satellite systems
Algorithm | Corr. | Joint state prob. (Sat1 & Sat2) | Sat1 | Sat2 | Parameters | |||||
|---|---|---|---|---|---|---|---|---|---|---|
coef. | P gg | P gb | P bg | P bb | P g | P b | P g | P b | ||
measured (Reference) | 0.15 | 0.32 | 0.46 | 0.05 | 0.16 | 0.78 | 0.22 | 0.37 | 0.63 | |
1st order Markov (Lutz) | 0.15 | 0.32 | 0.46 | 0.05 | 0.16 | 0.78 | 0.22 | 0.37 | 0.63 | 9 |
dynamic Markov | 0.15 | 0.32 | 0.46 | 0.05 | 0.16 | 0.78 | 0.22 | 0.37 | 0.63 | 11120 |
partial dynamic Markov | 0.10 | 0.35 | 0.37 | 0.10 | 0.17 | 0.72 | 0.28 | 0.45 | 0.55 | 2792 |
Semi-Markov, no fit | 0.15 | 0.32 | 0.46 | 0.05 | 0.16 | 0.78 | 0.22 | 0.37 | 0.63 | 2796 |
Semi-Markov, lognormal fit | 0.15 | 0.33 | 0.46 | 0.05 | 0.16 | 0.79 | 0.21 | 0.38 | 0.62 | 20 |
Semi-M., logn.fit + correction | 0.15 | 0.32 | 0.46 | 0.05 | 0.16 | 0.78 | 0.22 | 0.37 | 0.63 | 20 |
Semi-Markov, piecew. exp. fit | 0.15 | 0.33 | 0.45 | 0.05 | 0.17 | 0.78 | 0.22 | 0.38 | 0.62 | 64 |