Abstract
Deploying cells in a 5G mobile communication environment has been a difficult optimization problem because many conflict factors, such as coverage ratio and interference, have to be taken into account at the same time. The hyper-dense deployment problem (HDDP) for the 5G environment has attracted the attention of researchers from different disciplines, because it provides a way to depict the deployment problem we have to confront in a 5G environment. In this paper, an effective search algorithm is presented for solving the HDDP. The proposed algorithm is based on a novel metaheuristic algorithm, called search economics for hyper-dense deployment problem (SE-HDDP); the main difference is in that it will divide the solution space into a set of subspaces and determine the investment of searches based on the expected value (i.e., potential) of each subspace. The simulation results show that the proposed algorithm is able to find a better solution than the other metaheuristic and rule-based algorithms compared in this paper.
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