Novel Approach for Modeling Wireless Fading Channels using a Finite State Markov Chain

Abstract

Empirical modeling of wireless fading channels using common schemes such as autoregression and thefinitestate Markov chain (FSMC) is investigated. The conceptual background of both channel structures and the establishment of their mutual dependence in a confined manner are presented. The novel contribution lies in the proposal of a new approach for deriving the state transition probabilities borrowed from economic disciplines, which has not been studied so far with respect to the modeling of FSMC wireless fading channels. The proposed approach is based on equal portioning of the received signal-to-noise ratio, realized by using an alternative probability construction that was initially highlighted by Tauchen. The associated statistical procedure shows that afirst-order FSMC with a limited number of channel states can satisfactorily approximate fading. The computational overheads of the proposed technique are analyzed andproven to be less demanding compared to the conventional FSMC approach based on the levelcrossing rate. Simulations confirm the analytical results and promising performance of the new channel modelbased on the Tauchen approach without extracomplexity costs.