  The availability of satellite communication systems is extremely limited by
atmospheric impairments, such as rain (for radio frequencies) and cloud
coverage (for optical frequencies). A solution to this problem is the site
diversity technique, where a network of geographically distributed ground
stations (GSs) can ensure, with high probability, that at least one GS is
available for connection to the satellite at each time period. However, the
installation of redundant GSs induces unnecessary additional costs for the
network operator. In this context, we study an optimization problem that
minimizes the number of required GSs, subject to availability constraints.
First, the problem is transformed into a binary-integer-linear-programming
(BILP) problem, which is proven to be NP-hard. Subsequently, we design a
branch-and-bound (B&B) algorithm, with global-optimization guarantee, based on
the linear-programming (LP) relaxation and a greedy method as well. Finally,
numerical results show that the proposed algorithm significantly outperforms
state-of-the-art methods, and has low complexity in the average case.
