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Important performance metrics in cellular networks like SINR, SIR etc, can be written as functions of the 'propagation process', which is the ratio of the fading variable and the path-loss/attenuation function.
PropProcess.m simulates the propagation process for various fading distributions, done via random variable simulation or using propagation invariance, and plots the intensity/density function of the process. PropProcessInhom.m does the same but assumes the density of the base stations in the cellular network decreases according to a simple power-law.
In a Poisson network, the propagation process is an inhomogeneous Poisson process that is only dependent one one moment of the fading variable. These files calculate the intensity (or density) function of the propagation process for the following fading types: Log-normal, Rayleigh, Nakagami, and Rician.
These results could be easily generalized to other fading distribution when the moment E(F^{2/\beta}) is known, where F is the fading random variable, and beta is the path-loss exponent.
Cita come
H. Paul Keeler (2026). Propagation process under various fading distributions in cellular networks (https://it.mathworks.com/matlabcentral/fileexchange/43380-propagation-process-under-various-fading-distributions-in-cellular-networks), MATLAB Central File Exchange. Recuperato .
Informazioni generali
- Versione 1.0.0.0 (7,18 KB)
Compatibilità della release di MATLAB
- Compatibile con qualsiasi release
Compatibilità della piattaforma
- Windows
- macOS
- Linux
| Versione | Pubblicato | Note della release | Action |
|---|---|---|---|
| 1.0.0.0 |
