As a result of the continually growing demand for multimedia content and higher throughputs in wireless communication systems, the telecommuni-cation industry has to keep improving the use of the bandwidth resources. This access to the radiofrequency spectrum is both limited and expensive, which has naturally lead to the definition of the generic class of combinatorial optimization problems known as " Frequency Assignment Problems " (FAP). In this article, we present a new extension of these problems to the case of satellite systems that use a multibeam coverage. With the models we propose, we make sure that for each frequency plan produced there exists a corresponding satellite payload architecture that is cost-efficient and decently complex. Two approaches are presented and compared : a global constraint program that handles all the constraints simultaneously , and a decomposition method that involves both constraint programming and integer linear programming. For the latter approach where two subprob-lems are studied, we show that one of them can be modeled as a multiprocessor scheduling problem while the other can either be seen as a path-covering problem or a multidimensionnal bin-packing problem depending on the assumptions made. These analogies are used to prove that both the subproblems addressed in the decomposition method belong to the category of NP-hard problems. We also show that, for the most common class of interference graphs in multibeam satellite systems, the maximal cliques can all be enumerated in polynomial time and their number is relatively low, therefore it is perfectly acceptable to rely on them in the scheduling model that we derived. Our experiments on realistic scenarios show that the decomposition method proposed can indeed provide a solution of the problem when the global CP model does not.