Channel state modeling for single and multiple satellite broadcasting systems

In this contribution, we present the results of a study of the Probability Density Function (PDF) of the state durations in satellite broadcasting systems. We show that a channel state model that uses a Markov state model of order one is not appropriate if the state duration is of high importance, which can be the case in the process of system planning. In this case, a dynamic higher order Markov state model can be used. We study the modeling of the channel state duration for both single and multiple satellite broadcasting systems. In case of multiple satellite systems the channel state modeling is performed based on a dynamic higher order Markov channel state model for joint processes that depends on the current state duration. This approach is able to model the channel states of the whole system correctly, as well as the channel states of each satellite observed independently, showing the ability of capturing the state correlation between multiple satellites. Moreover, we introduce a reduced complexity channel state generation algorithm based on the PDF of the state duration. Our channel state models are validated with measurements of the Satellite Digital Audio Radio Services (S-DARS) system XM Radio carried out on various locations in the USA and Canada.