A multi-objective approach to indoor wireless heterogeneous networks planning based on biogeography-based optimization

A multi-objective approach to indoor wireless heterogeneous networks planning based on biogeography-based optimization. Goudos, S., K., Plets, D., Liu, N., Martens, L., & Joseph, W. Computer Networks, 91:564-576, 2015.
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In this paper, we present a multi-objective optimization approach for indoor wireless network planning subject to constraints for exposure minimization, coverage maximization and power consumption minimization. We consider heterogeneous networks consisting of WiFi access points (APs) and long term evolution (LTE) femtocells. We propose a design framework based on multi-objective biogeography-based optimization (MOBBO). We apply the MOBBO algorithm to network planning design cases in a real office environment. To validate this approach we compare results with other multi-objective algorithms like the nondominated sorting genetic algorithm-II (NSGA-II) and the generalized differential evolution (GDE3) algorithm. The results of the proposed method indicate the advantages and applicability of the multi-objective approach.

@article{
 title = {A multi-objective approach to indoor wireless heterogeneous networks planning based on biogeography-based optimization},
 type = {article},
 year = {2015},
 keywords = {Biogeography-based optimization,Exposure minimization,Heterogeneous networks,Indoor wireless network planning,Multi-objective optimization,Pareto optimization},
 pages = {564-576},
 volume = {91},
 id = {d767e04d-5d52-36c5-854d-41d6a8697560},
 created = {2020-02-29T16:57:44.241Z},
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 last_modified = {2023-02-11T18:54:03.082Z},
 read = {false},
 starred = {false},
 authored = {true},
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 citation_key = {Goudos2015},
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 abstract = {In this paper, we present a multi-objective optimization approach for indoor wireless network planning subject to constraints for exposure minimization, coverage maximization and power consumption minimization. We consider heterogeneous networks consisting of WiFi access points (APs) and long term evolution (LTE) femtocells. We propose a design framework based on multi-objective biogeography-based optimization (MOBBO). We apply the MOBBO algorithm to network planning design cases in a real office environment. To validate this approach we compare results with other multi-objective algorithms like the nondominated sorting genetic algorithm-II (NSGA-II) and the generalized differential evolution (GDE3) algorithm. The results of the proposed method indicate the advantages and applicability of the multi-objective approach.},
 bibtype = {article},
 author = {Goudos, Sotirios K. and Plets, David and Liu, Ning and Martens, Luc and Joseph, Wout},
 doi = {10.1016/j.comnet.2015.08.037},
 journal = {Computer Networks}
}

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