The Nakagami Distribution Law or the m-Nakagami Distribution Law is a distribution law of probability related to the distribution law gamma. It is used to model the attenuation of wireless networks across multiple paths.
Nakagami Fading occur :
- It describes the amplitude of received signal after maximum ratio diversity combining.
- The sum of multiple independent and identically distributed (i.i.d.) Rayleigh-fading signals have a Nakagami distributed signal amplitude.This is particularly relevant to model interference from multiple sources in a cellular system.
- The Nakagami distribution matches some empirical data better than other models
- Nakagami fading occurs for multipath scattering with relatively large delay-time spreads, with different clusters of reflected waves.
-The Rician and the Nakagami model behave approximately equivalently near their mean value.
This observation has been used in many recent papers to advocate the Nakagami model as an approximation for situations where a Rician model would be more appropriate.
Please look at answers of questions posed trough ResearchGate whose links is following :
- Why is Nakagami-m fading channel a good in practice in place of ...
Fading is a phenomenon which happens in wireless communication and results in fluctuation of the received signal strength or power. It occurs due to multiple copies of the same transmitted signal reaching the Rx thru various paths . Due to fading the received signal power becomes a random variable. Many probability distributions have been proposed to fit this random variable. Rayleigh dist fits that case when there is no line of sight path between Tx and Rx but a number of other paths. Rician fading fits the case when there is one line of sight path between Tx and Rx plus a number of other paths. Nakagami-m fading is very versatile as it can model a large variety of fading channels by changing the value of m in its equation. So Nakagami is a generic fading model.
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Got this recomended answer... thank you so much sir.
The wireless channel models describing the multipath propagation effect are the Rayleigh model , the Rician channel model and the Nakagami-m channel model. These models describe the probability distribution functions of signal power in the receiver site. The Rayleigh model assumes many non line of sight random paths while the Rician model assumes in addition a line of sight path. The Nakagami model is an empirical model covering wide range of multipath fading patterns through the introduction of the parameter m. So, it may give more accurate results for describing the channel when it is used to model the communication systems.
More information can be found in the site:www.springer.com/cda/content/document/cda.../9781402080838-c2.pdf?SGWID.
The Nakagami-m distribution is only one of a set of distributions that model fading in a wireless communications channel. Other distributions, such as, Rayleigh, Rice, Eta-Mu, Kappa-Mu are obtained if one consider different aspects of the channel characteristics.
When a signal leaves transmitting antenna it encounter various objects in channel with different dimension. It gets refracted, diffracted, reflected and scattered depending upon the dimension, shape and material of the objects and operating frequency. All of this results in multiple copies of the same signal with different magnitude, phase and delay which are picked up by the receiver. Received multipath components with different delay and phase add destructively and constructively which results in small scale variation of the received signal. Multipath fading is random phenomenon which is best described by statistical distributions. Rician and Rayleigh distributions model fading hence the terms Rician fading when there is atleast one LOS component and Rayleigh Fading when there is no LOS component. Nakagami-m is more general distribution which is helpful to see the
The Rayleigh distribution is frequently used to model multipath fading with no direct line-of-sight (LOS) path.
The Rician distribution is often used to model propagation paths consisting of one strong direct LOS component and many random weaker components.
The Nakagami- m distribution is its good ft to empirical fading data. It is versatile and through its parameter m, we can model signal fading conditions that range from severe to moderate, to light fading, or no fading.