An effective hyper-dense deployment algorithm via search economics
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Developing an effective strategy for deploying base stations of a mobile communication environment has been a critical issue for years because it typically needs to take into account several conflict factors, such as coverage ratio and interference. Since 5G cellular services are expected to be commercially available in 2020, a “good deployment strategy” for the hyper-dense deployment problem (HDDP) has attracted the attention of researchers from different disciplines in recent years. To enhance the performance of a 5G mobile communication environment, an effective search algorithm for solving the HDDP, called search economics for hyper-dense deployment problem (SE-HDDP), is presented in this paper. A distinctive feature of the proposed algorithm is that it divides the search space into a set of subspaces and dynamically allocates the computing resources to these subspaces based on their potentials during the convergence process. The simulation results show that the proposed algorithm is able to find a better result of HDDP for a 5G mobile communication environment than all the other metaheuristic and rule-based algorithms compared in this paper.
KeywordsMobile communication Deployment problem Metaheuristic algorithm Search economics
The authors would like to thank the anonymous reviewers for their valuable comments and suggestions on the paper. This work was supported in part by the Ministry of Science and Technology of Taiwan, R.O.C., under Contracts MOST106-2221-E-005-094 and MOST107-2221-E-110-078.
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