Adaptive Cell Tower Location Using Geostatistics Mohan R. Akella, 1 Eric Delmelle, 2 Rajan Batta, 3,4 Peter Rogerson 4,5,6 Alan Blatt 7 1 Strategy and Operations, Deloitte Consulting India Pvt. Ltd., Hyderabad, India, 2 Department of Geography and Earth Sciences, Center for Applied Geographic Information Systems (CAGIS), University of North Carolina—Charlotte, Charlotte, NC, 3 Department of Industrial and Systems Engineering, University at Buffalo (SUNY), Buffalo, NY, 4 National Center for Geographic Information and Analysis, Buffalo, NY, 5 Department of Geography, University at Buffalo (SUNY), Buffalo, NY, 6 Department of Biostatistics, University at Buffalo (SUNY), Buffalo, NY, 7 Center for Transportation Injury Research, Calspan-University of Buffalo Research Center (CUBRC), Buffalo, NY In this article, we address the problem of allocating an additional cell tower (or a set of towers) to an existing cellular network, maximizing the call completion probability. Our approach is derived from the adaptive spatial sampling problem using kriging, capitalizing on spatial correlation between cell phone signal strength data points and accounting for terrain morphology. Cell phone demand is reflected by population counts in the form of weights. The objective function, which is the weighted call completion probability, is highly nonlinear and complex (nondifferentiable and dis- continuous). Sequential and simultaneous discrete optimization techniques are pre- sented, and heuristics such as simulated annealing and Nelder–Mead are suggested to solve our problem. The adaptive spatial sampling problem is defined and related to the additional facility location problem. The approach is illustrated using data on cell phone call completion probability in a rural region of Erie County in western New York, and accounts for terrain variation using a line-of-sight approach. Finally, the computational results of sequential and simultaneous approaches are compared. Our model is also applicable to other facility location problems that aim to minimize the uncertainty associated with a customer visiting a new facility that has been added to an existing set of facilities. Introduction and literature review This article is motivated by the challenge of optimally locating new base stations for wireless service, using data on existing cell phone signal strength measurements, Correspondence: Eric Delmelle, Department of Geography and Earth Sciences, Center for Applied Geographic Information Systems (CAGIS), University of North Carolina—Charlotte, Charlotte, NC 28223, U.S.A. e-mail: eric.delmelle@uncc.edu Submitted: February 12, 2007. Revised version accepted: October 6, 2008. Geographical Analysis 42 (2010) 227–244 r 2010 The Ohio State University 227 Geographical Analysis ISSN 0016-7363