Application of the Mixture of Lognormal Distribution to Represent the First-Order Statistics of Wireless Channels

@article{Das2020ApplicationOT,
  title={Application of the Mixture of Lognormal Distribution to Represent the First-Order Statistics of Wireless Channels},
  author={Saikat Das and Amitabh Bhattacharya},
  journal={IEEE Systems Journal},
  year={2020},
  volume={14},
  pages={4394-4401}
}
In a wireless channel, shadow fading along with multipath effect causes random fluctuations of the received signal strength at the receiver. Several composite fading distributions are available for modeling the randomness. Among them, Lognormal-based models are unable to give a closed-form expression of the composite distribution, but Gamma-based model overcomes the problem faced by the former one. However, the Gamma-based model comes with a complicated mathematical function. To get rid of that… 
An adaptive q-Lognormal model towards the computation of Average Channel Capacity in slow fading channels
TLDR
This paper portrays an adaptive generalized Tsallis’ non-extensive q-Lognormal model towards the characterization of various fading channels that operates well with the synthesized fading signals and captures the wide range of tail fluctuations to adapt different fading scenarios.

References

SHOWING 1-10 OF 37 REFERENCES
A Mixture Gamma Distribution to Model the SNR of Wireless Channels
TLDR
A mixture gamma (MG) distribution for the signal-to-noise ratio (SNR) of wireless channels is proposed, which is not only a more accurate model for composite fading, but is also a versatile approximation for any fading SNR.
Modeling and Analysis of Wireless Channels via the Mixture of Gaussian Distribution
TLDR
The proposed approach provides an accurate approximation for the envelope and the signal-to-noise ratio (SNR) distributions of wireless fading channels and provides closed-form expressions or approximations for several performance metrics used in wireless communication systems.
Performance analysis of lognormally shadowed generalized Gamma fading channels
  • H. Samimi
  • Engineering
    Int. J. Commun. Syst.
  • 2011
TLDR
An approximation method is developed which makes it possible to derive a closed-form, analytical expression forGG-L composite distribution, and bypasses the required complicated integration needed to calculate the PDF of the received signal envelope in GG-L channel.
Outage probabilities in shadowed fading channels using a compound statistical model
A compound probability density function (PDF) was recently proposed to describe wireless channels in short-term fading and shadowing. This three-parameter PDF is able to represent short-term fading
A unified approach for representing wireless channels using EM-based finite mixture of gamma distributions
TLDR
A new approach to represent different fading distributions by mixture of Gamma distributions is proposed, which relies on the expectation-maximization (EM) algorithm in conjunction with the so-called Newton-Raphson maximization algorithm to evaluate the error rate performance of wireless networks over generalized fading channels.
Error Rates in Generalized Shadowed Fading Channels
TLDR
A generalized or compound fading model which takes into account both fading and shadowing in wireless systems, which is analytically simpler than the two pdfs based on lognormal shadowing and is general enough to incorporate most of the fading andshadowing observed in wireless channels.
An Additive Model as a Physical Basis for Shadow Fading
TLDR
An additive model is proposed as an alternative physical basis for shadow fading within an "extended local area" where path loss is constant and provides insights into simulation and modeling of radio channels.
A statistical basis for lognormal shadowing effects in multipath fading channels
Empirical justifications for the lognormal, Rayleigh and Suzuki (1977) probability density functions in multipath fading channels are examined by quantifying the rates of convergence of the central
Statistical Models for Fading and Shadowed Fading Channels in Wireless Systems: A Pedagogical Perspective
TLDR
A unified analysis of statistical models for describing fading, shadowing, and shadowed fading channels is presented from a pedagogical viewpoint and the different probability density functions are compared in terms of two quantitative measures, namely the amount of fading and outage probability.
Lognormal Mixture Shadowing
TLDR
This paper proves that an arbitrary probability density function can accurately be represented by a mixture of lognormal random variables (RVs) and provides outage and cellular coverage probability expressions, where it is shown that more accurate shadow fading models yield more realistic performance estimates.
...
1
2
3
4
...