Optimal Capacity Expansion of Next-generation Wireless Base Station Subsystems

With an increasing mobility of today’s workforce, organizations have a growing need for information and transactions anytime and anywhere. Mobile network operators (MNO) must therefore meet this need by deploying wireless networks capable of offering advanced voice and data services. While wireless network planning and design has been studied extensively in the literature, most work has focused on voice demand only. As MNO transition to nextgeneration wireless networks, however, voice and data traffic combined will have to be considered in these capacity expansion and allocation decisions. In this paper, we examine the wireless base station subsystem and propose a multi-demand type optimization model that solves the capacity expansion problem of current to next-generation wireless networks. We provide an integer programming formulation for the optimal design of next-generation wireless BSS with the objective of minimizing the costs associated with the installation, connection, replacement, and capacity upgrade of infrastructure equipment. Our problem is similar to the well-known hierarchical concentrator location problem, which is shown to be NPcomplete. A Lagrangian relaxation is used to obtain lower bounds for this problem. Computational results will be presented for a set of real-world and randomly generated test problems.