Asymptotic multicast throughput analysis and energy efficiency in WSN under double Nakagami fading channel using Extreme value theory

Wireless sensor network (WSN) applications demand high throughput and energy efficiency for commercial adaptability. Although recent research enhances our knowledge about traditional fading, yet the shortcomings like mathematical complexity, absence of closed solution, and lack of physical insight of random behavior impede analytical study. Extreme value theory (EVT) has been used in cases where the direct solution is almost intractable. This prompts us to use EVT, in relatively more complex fading environments like double Nakagami. Here, we present an asymptotic analysis of multicasting throughput and energy efficiency for WSN communications under the assumption of independent and identically distributed channels. Considering the cumulative distribution function (CDF) of the SNR, we obtain expressions for minimum scaled SNR. The distribution of minima extreme is shown to converge to Weibull distribution and subsequently the effects of minimum scaled SNR on throughput are obtained. The influence of the varying number of users, fading strength and SNR on the per user throughput are also explored. For validation, we compare our results with recently reported approximately exact approach and find a satisfactory agreement. We also perform the Monte-Carlo simulations. This study may help in designing throughput friendly and energy-efficient systems.