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Basics on the Theory of Fading Channels and Diversity
Published in Athanasios G. Kanatas, Konstantina S. Nikita, Panagiotis Mathiopoulos, New Directions in Wireless Communications Systems, 2017
Vasileios M. Kapinas, Georgia D. Ntouni, George K. Karagiannidis
A more general fading distribution that can be well-fitted to experimental data is the Nakagami-m distribution suggested in 1960 by Nakagami. In this case, the PDF of the fading envelope is given by [16] () fa(a)=2mma2m−1ΩmΓ(m)exp(−ma2Ω),a≥0
Modeling of Fading Channels
Published in Stefan R. Panić, Mihajlo Stefanović, Jelena Anastasov, Petar Spalević, Fading and Interference Mitigation in Wireless Communications, 2013
Stefan R. Panić, Mihajlo Stefanović, Jelena Anastasov, Petar Spalević
As a general fading distribution, the Nakagami- m fading model includes (as special cases) other distributions such as Rayleigh distribution (by setting parameter m value m=1 ) and one-sided Gaussian distribution (m=1/2). In addition, for more severe scenarios than Rayleigh fading m<1, the Nakagami- m distributed fading closely approximates the Hoyt distribution, by introducing a relation between parameters q and m, as follows [1]: () m=1+q2221+2q4.
An Improved Method for ASEP Evaluation over Fading Channels Based on Q-Function Approximation
Published in IETE Journal of Research, 2018
Aleksandar V. Markovic, Zoran H. Peric, Stefan R. Panic, Petar C. Spalevic, Bojan P. Prlincevic
Nakagami-m fading model describes multipath scattering with large delay-time spreads, and different clusters of reflected waves, it provides good fits to collected data in indoor and outdoor wireless environments [1]. Recent studies have also provedthat Nakagami-m fading model gives the best fit for satellite-to-indoor and satellite-to outdoor radio wave propagation [16]. Similarly, best fit to land mobile and indoor mobile multipath propagation as well as scintillating ionospheric radio links [17] can be obtained by observing Nakagami-m fading model. Being a general fading distribution, Nakagami-m fading model includes (as its singularities) other fading models such are Rayleigh distribution (by setting parameter m value m = 1), and one-sided Gaussian distribution (m = 1/2) [18]. In addition, for more severe scenarios than Rayleigh fading m < 1, the Nakagami-m distributed fading closely approximate Nakagami-q distribution, by introducing relation between parameters q and m, as follows m = (1 + q2)2 / 2(1 + 2q4) [19]. Finally, for less severe scenarios m > 1, the Nakagami-m distribution could approximate the Rician distribution, by introducing relation between parameter m and Rician K parameter as m = (1 + K2) / (1 + 2K) [20].