Novel Results for the $\kappa$– $\mu$ Extreme Fading Distribution: Generation of White Samples and Capacity Analysis
| Autor: | Eduardo Martos-Naya, Laureano Moreno-Pozas, F. J. Lopez-Martinez |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Cumulative distribution function
Inverse transform sampling Function (mathematics) Computer Science Applications Channel capacity Fading distribution Modeling and Simulation Statistics Fading Statistical physics Electrical and Electronic Engineering Random variable Computer Science::Information Theory Mathematics Rayleigh fading |
| Zdroj: | IEEE Communications Letters. 19:1580-1583 |
| ISSN: | 1089-7798 |
| DOI: | 10.1109/lcomm.2015.2453261 |
| Popis: | We provide new analytical results for the $\kappa$ – $\mu$ extreme ( $\kappa$ – $\mu$ -E) fading distribution, which is useful to model propagation conditions more severe than Rayleigh fading. First, we calculate a closed-form expression for the cumulative distribution function in terms of the first-order Marcum $Q$ -function, which allows us to accurately generate $\kappa$ – $\mu$ -E distributed random variables using the inversion method. Then, we investigate the ergodic capacity in this scenario. Strikingly, we observe that the capacity in the high-SNR regime scales differently than in all conventional fading models. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|