  In this paper we present a tractable approach for regularizing randomly
placed points, by splitting them into two subsets: the first is generated by
means of the Mat\'ern hard-core point process, while the remaining points
constitute the complementary Mat\'ern hard-core point process. We study the
characteristics of these processes, deriving its pair-correlation functions,
and the distribution of the distance to the nearest neighbour. The results have
several applications in wireless communications, including the modeling of
wireless sensor networks, where we investigate an example of regularizing such
networks and illustrate its advantage in reducing the energy consumption of
wireless nodes.
