Abstract

In wireless communication channels, the signals arriving at the receiver may be of stochastic nature or be superpositioned due to non-uniform scattering and shadowing. For the ease of computation, we generally assume the mean ergodic property of communication channels which is error prone. The well known lognormal model fails to capture the extreme tail fluctuations in the presence of shadowing. In this setting, we exploit the importance of Tsallis non-extensive parameter ‘q’ to characterize various fading channels. The q-lognormal distribution captures the tail phenomena due to presence of non-extensive parameter ‘q’. In this paper, we provide an excellent agreement between the generated synthetic signal and the proposed q-Lognormal distribution for different values of parameter ‘q’. This paper also presents the analytical expression for the superstatistics Weibull/q-lognormal model to capture both fading and shadowing effects. It is observed that the Weibull/q-Lognormal model provides a better fit to the generated signal for $$q=1.8$$ in comparison to the well known Weibull/Lognormal model. Finally, we provide an excellent agreement between the derived measures viz., amount of fading, outage probability, average channel capacity with extensive Monte-Carlo simulation scheme.

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