The wireless communication industry has been and is still experiencing an exciting era of rapid development. New technologies and designs emerge on a regular basis. The timely adoption of these technologies in real-world systems relies heavily on the accurate prediction of their performance over general wireless fading channels and the associated system complexity. Theoretical performance and complexity analysis become invaluable in this process, because they can help circumvent the time-consuming computer simulation and expensive field test campaigns. These analytical results, usually in the form of elegant closed-form solutions, will also bring important insight into the dependence of the performance as well as complexity measures on system design parameters and, as such, facilitate the determination of the most suitable design choice in the face of practical implementation constraints.

Mathematical and statistical tools play a critical rule in the performance analysis of digital wireless communication systems over fading channels [1]. In fact, the proper utilization of these tools can help either simplify the existing results, which do not allow for efficient numerical evaluation, or render new analytical solutions that were previously deemed infeasible. One popular example is the application of moment generation function (MGF) in the performance analysis of digital communication system over fading channels [2]. With the unified MGF-based analytical framework, the error probability expressions, which usually involve an infinite integration of Gaussian Q-function, are simplified to a single integral of elementary functions with finite limits and, as such, facilitate convenient and accurate numerical evaluation.