Performance Analysis of Non-identical Cascaded $$\alpha$$–$$\mu$$ Fading Channels

Chauhan, Puspraj Singh; Kumar, Sandeep; Soni, Sanjay Kumar

doi:10.1007/s11277-020-07864-4

Cited by 5 publications

(1 citation statement)

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“…Additionally, by employing specific value to fading parameters α and μ , this distribution encompasses to Rayleigh

false(α = 2; μ = 1 false)

, Weibull

false(α, μ = 1 false)

and Nakagami‐ m

false(α = 2, μ = m false)

distributions. Following this, both physical and link layer performance metrics over α − μ , product of α − μ distribution and its special cases have been analysed in previous studies 10–14 . Apart from multipath, the radio paths of the signals are often partially or completely obstructed by different intervening objects, termed as shadowing.…”

Section: Introductionmentioning

confidence: 99%

An approximate statistical analysis of wireless channel over α − μ shadowed fading channel

Upaddhyay

Soni

Chauhan

2021

Int J Communication

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Summary In this work, we have comprehensively investigated the impact of non‐linearity (α − μ) and shadowing (inverse gamma) collectively over the wireless channel. To this effect, an approximate closed‐form probability density function (PDF) expression is derived over α − μ/inverse gamma fading channel by employing Gauss–Laguerre quadrature polynomial. The accuracy of the proposed approximate solution is validated through the Kullback–Leibler divergence test. Subsequently, the proposed solution is utilized in the development of various fundamental statistics like commutative distribution function (CDF), moment generating function (MGF) and nth moment. This contribution also includes the derivation of coding gain and diversity gain to study average symbol error probability (SEP) with MRC and EGC diversity. It is observed that diversity gain is independent of shadowing and as the channel condition improves, the coding gain decreases. Finally, the closed‐form solutions of spectral efficiency under different adaptive transmission policies are also developed specifically, optimal power and rate adaptation (OPRA) and effective capacity along with simpler low‐ and high‐power expressions. Monte‐Carlo simulations are utilized to validate the proposed analytical and numerical results.

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“…Additionally, by employing specific value to fading parameters α and μ , this distribution encompasses to Rayleigh