@article{
 title = {MIMO antenna selection using biogeography-based optimization with nonlinear migration models},
 type = {article},
 year = {2018},
 keywords = {ant colony optimization,antenna selection,biogeography-based optimization,evolutionaryr algorithms,genetic algorithm,multiple-input multiple-output systems},
 volume = {31},
 id = {12b4d4ec-74aa-349a-ab0b-5c79a6e60d5e},
 created = {2020-02-29T16:57:45.278Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:03.499Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Fountoukidis2018},
 private_publication = {false},
 abstract = {This papers deals with the problem of antenna selection (AS) for a multiple-input multiple-output (MIMO) wireless system under the constraint of the channel capacity maximization. The biogeography-based optimization (BBO) algorithm is applied on the joint transmitter and receiver AS problem. Moreover, the performance of different BBO migration models is compared with a real valued genetic algorithm (RVGA) as well as with the ant colony optimization (ACO). Representative simulation scenarios are provided in detail, involving selection of 2 × 4,3 × 5,4 × 6,8 × 8 antennas in a 16 × 16 MIMO system. The numerical results demonstrate the efficiency and the applicability of the BBO algorithm in modern MIMO wireless systems.},
 bibtype = {article},
 author = {Fountoukidis, Konstantinos C. and Kalialakis, Christos and Psannis, Kostas E. and Siakavara, Katherine and Goudos, Sotirios K. and Sarigiannidis, Panagiotis and Obaidat, Mohammad},
 doi = {10.1002/dac.3813},
 journal = {International Journal of Communication Systems},
 number = {17}
}

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