Base Station Location and Service Assignments in W–CDMA Networks

Abstract

D esigning a wideband code division multiple access (W-CDMA) network is a complicated task requiring the selection of sites for radio towers, analysis of customer demand, and assurance of service quality in terms of signal-to-interference ratio requirements. This investigation presents a net-revenue maximization model that can help a network planner with the selection of tower sites and the calculation of service capacity. The integer programming model takes as input a set of candidate tower locations with corresponding costs, a number of customer locations with corresponding demand for traffic, and the revenue potential for each unit of capacity allocated to each demand point. Based on these data, the model can be used to determine the selection of radio towers and the service capacity of the resulting radio network. The basic model is a large integer program and requires a special algorithm for practical solution. Our algorithm uses a priority branching scheme, an optimization-gap tolerance between 1% and 10%, and two sets of global valid inequalities that tighten the upper bounds obtained from the linear programming relaxation. The algorithm has been implemented in software for the AMPL/CPLEX system and an empirical investigation has been conducted. Using over 300 problem instances with up to 40 towers and 250 service locations, various combinations of algorithm settings have been evaluated. Using the recommended setting results in a design tool that generally runs in under 20 minutes on a 667 MHz AlphaStation.

On Improving the Capacity of Solving Large-scale Wireless Network Design Problems by Genetic Algorithms

“…The natural formulation (BM-PFMAP) expands a basic model that is widely used for the WND in different application contexts, such as DVB, (e.g., [12]), UMTS (e.g., [1,11]) and WiMAX ( [6,7]). In principle, such basic model and (BM-PFMAP) can be solved by commercial solvers such as IBM ILOG CPLEX [10].…”

“…In principle, such basic model and (BM-PFMAP) can be solved by commercial solvers such as IBM ILOG CPLEX [10]. However, it is well-known (see [7]) that: (i) the fading coefficients may vary in a wide range leading to (very) ill-conditioned coefficient matrices that make the solution process numerically unstable; (ii) the big-M coefficients generate poor quality bounds that dramatically reduce the effectiveness of standard solution approach [13]; (iii) the resulting coverage plans are often unreliable and may contain errors (e.g., [7,11]). In practice, the basic model and (BM-PFMAP) can be solved to optimality only when used for small-sized instances.…”

Solving a minimum-power covering problem with overlap constraint for cellular network design

“…The latter is typically represented by the average cell load. The trade-off between infrastructure cost and profit has been dealt with by integer programming by Kalvenes [15]. In [18], Olinick and Rosenberger approached this trade-off by a stochastic optimization model to take into account demand uncertainty.…”

Planning wireless networks by shortest path

“…Several algorithms have been developed to solve different planning problems. Many of these are based on Mixed Integer Linear Programming (MILP) formulations (see [3,8,9,11] for mobile planning, [10,14] for broadcasting). However, as pointed out by several authors (see, for example, [11]), these formulations suffer from weakness of the respective bounds and, even worst, from numerical inaccuracy: in practice, they fail to solve even small/medium sized instances of practical interest.…”