Channel state duration modeling for satellite broadcasting systems

It are presented the results of a study of the Probability Density Function (PDF) of the state durations in satellite broadcasting systems. A channel state model that uses a fixed order Markov state model does not model the PDF of the state duration appropriately, which is important in the process of system planning. Therefore, we propose a dynamic higher order Markov state model that models precisely the PDF of the state duration. An extension of this approach is able to model the channel states of the multiple satellite systems as well. As an alternative it is introduced a reduced complexity channel state generation algorithm based on the PDF of the state duration. Also possible approximations of the proposed models are studied in order to reduce their computational complexity while having a good PDF match. The presented 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