1. Foundations: Random Processes
Why characterize signals?
Wireless signals encounter obstacles causing path loss, shadowing, and fading. We use statistical models to predict behavior.
- Path Loss: Power reduction over distance.
- Shadowing: Obstruction losses (Large-scale).
- Multipath Fading: Interference from multiple paths.
Wide Sense Stationarity (WSS)
Crucial for simplifying mathematical models.
2. Classification of Signal Variation
Outdoor Pathloss Models
- • Okumura-Hata Model
- • Break Point Model
Propagation Mechanics
Reflection
Diffraction
Scattering
Shadowing
Statistical Modeling (Log-Normal)
Multipath Fading
Time Dispersion
3. Shadowing & Outage Probability
Log-Normal Shadowing
The received power in dB follows a Gaussian (Normal) distribution.
Where $X_\sigma \sim \mathcal{N}(0, \sigma^2)$
Outage Probability & Coverage
Outage Probability
Prob. that received power < $P_{min}$.
Acceptance Probability (Coverage)
Prob. of good signal quality.
Example Calculation
- Margin ($\beta$): 10 dB
- Sigma ($\sigma$): 10 dB
- Acceptable Signal: 84%
- Since $Q(1) \approx 0.16$, Coverage = $1 - 0.16$
| x | 0 | 1 | 2 | 3 |
|---|---|---|---|---|
| Q(x) | 0.5 | 0.159 | 0.023 | 0.001 |
4. Geometric Effect: Two-Ray Model
Interference Pattern
The received signal is a sum of the direct path and the reflected path (which has a 180° phase shift).
Coherence Bandwidth
The frequency range where the channel is "flat".