TY - JOUR
T1 - A Genetic Algorithm-based Antenna Selection Approach for Large-but-Finite MIMO Networks
AU - Makki, Behrooz
AU - Ide, Anatole
AU - Svensson, Tommy
AU - Eriksson, Thomas
AU - Alouini, Mohamed-Slim
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2016/12/29
Y1 - 2016/12/29
N2 - We study the performance of antenna selectionbased multiple-input-multiple-output (MIMO) networks with large but finite number of transmit antennas and receivers. Considering the continuous and bursty communication scenarios with different users’ data request probabilities, we develop an efficient antenna selection scheme using genetic algorithms (GA). As demonstrated, the proposed algorithm is generic in the sense that it can be used in the cases with different objective functions, precoding methods, levels of available channel state information and channel models. Our results show that the proposed GAbased algorithm reaches (almost) the same throughput as the exhaustive search-based optimal approach, with substantially less implementation complexity.
AB - We study the performance of antenna selectionbased multiple-input-multiple-output (MIMO) networks with large but finite number of transmit antennas and receivers. Considering the continuous and bursty communication scenarios with different users’ data request probabilities, we develop an efficient antenna selection scheme using genetic algorithms (GA). As demonstrated, the proposed algorithm is generic in the sense that it can be used in the cases with different objective functions, precoding methods, levels of available channel state information and channel models. Our results show that the proposed GAbased algorithm reaches (almost) the same throughput as the exhaustive search-based optimal approach, with substantially less implementation complexity.
UR - http://hdl.handle.net/10754/623706
UR - http://ieeexplore.ieee.org/document/7801976/
UR - http://www.scopus.com/inward/record.url?scp=85029213146&partnerID=8YFLogxK
U2 - 10.1109/tvt.2016.2646139
DO - 10.1109/tvt.2016.2646139
M3 - Article
SN - 0018-9545
VL - 66
SP - 6591
EP - 6595
JO - IEEE Transactions on Vehicular Technology
JF - IEEE Transactions on Vehicular Technology
IS - 7
ER -