MIMO antenna selection using biogeography-based optimization with nonlinear migration models

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MIMO antenna selection using biogeography-based optimization with nonlinear migration models

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K.C. Fountoukidis, C. Kalialakis, K.E. Psannis, K. Siakavara, S.K. Goudos, P. Sarigiannidis, M. Obaidat: MIMO antenna selection using biogeography-based optimization with nonlinear migration models. In: International Journal of Communication Systems, vol. 31, no. 17, 2018.

Περίληψη

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. © 2018 John Wiley & Sons, Ltd.

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BibTeX (Download)

@article{Fountoukidis2018,
title = {MIMO antenna selection using biogeography-based optimization with nonlinear migration models},
author = { K.C. Fountoukidis and C. Kalialakis and K.E. Psannis and K. Siakavara and S.K. Goudos and P. Sarigiannidis and M. Obaidat},
url = {https://www.researchgate.net/publication/327201674_MIMO_Antenna_Selection_Using_Biogeography_Based_Optimization_with_Non-Linear_Migration_Models},
doi = {10.1002/dac.3813},
year  = {2018},
date = {2018-01-01},
journal = {International Journal of Communication Systems},
volume = {31},
number = {17},
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. © 2018 John Wiley & Sons, Ltd.},
keywords = {ant colony optimization, antenna selection, biogeography-based optimization, evolutionaryr algorithms, genetic algorithm, multiple-input multiple-output systems},
pubstate = {published},
tppubtype = {article}
}
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