Marginal Moment Generating Function Based Suboptimal Adaptive Analysis for Generalized-k Fading- a Composite Model for Fading Channels

Abstract

A novel scheme based on the communication among the distributed nodes has motivated the use of composite fading models because the distributed nodes experience different levels of multipath/small scale fading, shadowing and path loss. Most of the composite fading models consider multipath fading superimposed on lognormal shadowing distribution. However, the analysis using these composite fading models with complex integral form is not able to provide closed form expressions. Therefore, the composite fading model using Generalized-K distribution is provided in which the lognormal distribution is approximated by Gamma distribution in order to have simplified and closed-form expressions. Further, the analysis is provided using moment generating function (MGF) because of its advantage over simplification of the mathematical expressions as compared to that of the probability density function (PDF) based approach. The improvement over capacity performance of the communication system is provided by adapting the transmission rate, power and coding techniques of the transmitter in accordance to the channel state information (CSI). The channel capacity for suboptimal adaptation technique over the Generalized-K fading environment is presented. The analytical expression for channel capacity for truncated channel inversion with fixed rate (CTCIFR) has been provided in terms of marginal moment generating function (MMGF) and its performance is evaluated over the Generalized-K faded environment. This MMGF based approach for the computation of channel capacity has been validated with the reported literature for channel capacity for channel inversion with fixed rate suboptimal adaptive technique