| Article ID: | iaor20171861 |
| Volume: | 253 |
| Issue: | 1 |
| Start Page Number: | 169 |
| End Page Number: | 191 |
| Publication Date: | Jun 2017 |
| Journal: | Annals of Operations Research |
| Authors: | Desai Jitamitra, Kishore Shalinee |
| Keywords: | combinatorial optimization, communications, simulation, energy, programming: nonlinear, heuristics |
In this paper, we present a set of (exact and approximate) mathematical models and algorithms for determining the set of (globally) optimal distributed antenna deployments and the supported user demand in cellular code division multiple access (CDMA) systems. We focus on the uplink (user‐to‐base station) formulation and assume that the base station combines all the received signals at each of the antennas using path‐gain based weights. In CDMA systems, as all users occupy the system bandwidth at the same time thereby interfering with each other, this results in a complicated 0–1 mixed‐integer multilinear programming problem, where the objective function maximizes the total system capacity, while ensuring that the minimum signal‐to‐interference‐plus‐noise ratio (SINR) constraints and maximum transmit power constraints for each user are satisfied. This highly nonlinear, nonconvex problem is reformulated to yield a tight mixed‐integer 0–1 linear programming representation via the addition of several auxiliary variables and constraints, and a specialized algorithm is designed to determine globally optimal solutions. The computational results obtained, corresponding to different user distributions, demonstrate the efficacy of the proposed models and algorithms, and clearly exhibit the viability of both exact and approximate models.