Dear ENG. Anoop,
A number of channel models exist todescribe the statistics of the
amplitude and phase of multipath fading signals. Nakagami-m distribution has the following advantages versus the other models:
- It is a generalized distribution which can model different fading environments.
-It has greater flexibility and accuracy in matching some experimental data than the Rayleigh, lognormal or Rice distributions .
- Rayleigh and one-sided Gaussian distribution are special cases of Nakagami-m model.
So the Nakagami-m channel model is of more general applicability in practical fading channels.
For more information please follow the link:
http://www.sersc.org/journals/IJAST/vol37/4.pdf
wish you success.
Dear ENG. Anoop,
A number of channel models exist todescribe the statistics of the
amplitude and phase of multipath fading signals. Nakagami-m distribution has the following advantages versus the other models:
- It is a generalized distribution which can model different fading environments.
-It has greater flexibility and accuracy in matching some experimental data than the Rayleigh, lognormal or Rice distributions .
- Rayleigh and one-sided Gaussian distribution are special cases of Nakagami-m model.
So the Nakagami-m channel model is of more general applicability in practical fading channels.
For more information please follow the link:
http://www.sersc.org/journals/IJAST/vol37/4.pdf
wish you success.
Dear Anoop,
In general you cant say that Nakagami-m fading is better channel simulation model than Rayleigh fading. Both of them are inter-related as it is stated above by other researchers. Based on your application you can advocate which model fits best your channel model. Note that there exist plenty of realistic channel models in practice. Hence, the appropriate model shall be analyzed before considered in your scenario as how well does it fits to the realistic channel model.
Good luck!
Nakagami-m distribution is a generalized way to model small scale fading. In general, we try to approximate the amplitude/power of a received signal using a suitable distribution. Basically, Rayleigh distribution is sufficient to model amplitude in urban areas, Rician distribution suits better in sub-urban areas where LOS components exist, and Hoyt distribution models scintillation effects. As earlier mentioned, Nakagami-m distribution is a generalized case and includes the three distributions as special cases. Means if we are done with the analysis for Nakagami-m fading, it is equally applicable in any of the above mentioned fading environments (m1 for Rician).
Moreover, approximation using Nakagami-m may not be optimum, specially at tail, and for those cases more generalized and accurate models (kappa-mu/eta-mu/etc.) need to be used.
Rayleigh fading only gives you diversity order of one, while the Nakagami-m fading model will provide you with a diversity order of m. Having said that, both Rayleigh and Nakagami-m model will not describe the line-of-sight (LOS) transmission environments well. Some authors proposed to use the Nakagami-m model to approximate the Rician fading, and such an approximation is not recommended since both models donnot even give you the same diversity order, and Nakagami-m cannot be used to describe the LOS transmission, which has been empirically verified (Read the paper by Molish). Another reason why the Nakagami-m model is popular is because its mathematical form is more analytically tractable.
Adding to the aforementioned answers, it is not about the good or bad model. It is about which distribution is more covering a wide cases of fading scenarios. Nakagami m is a generic distribution, and Rayleigh, Rician and Hyot are its special cases. So, Nakagami is generic and broad.
Can someone help me how to explain how to simulate time varying shadowed Nakagami-m fading using matlab please? or any sample code regarding this? Thank you in advance!
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