Abstract

At present, wireless communications are an integral part of day to day life. To make this communication effective and efficient, we have to place our transmitters in such a way that we can provide reliable service with a minimum cost. However, properly accomplishing this becomes a very difficult and computationally complex task when real–world considerations such as variation in signal strength due to distance and differences in the propagation environment (i.e., different degrees of obstruction) are taken into account. Therefore, the objective of this research is to develop effective and efficient methodologies to design an optimum wireless transmitter allocation strategy. To achieve this objective, we consider this decision problem as a grid–based location problem (GBLP), and develop an ILP model that is designed to provide the optimal solution for the transmitter location problem. These ILP models are often difficult to solve. As such, we developed a problem–specific decomposition approach to solve large–scale GBLP ILP problems, which we demonstrate has significantly reduced solution runtimes while not impacting optimality.

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