A Genetic Algorithm-based Antenna Selection Approach for Large-but-Finite MIMO Networks

Behrooz Makki, Anatole Ide, Tommy Svensson, Thomas Eriksson, Mohamed-Slim Alouini

Research output: Contribution to journalArticlepeer-review

39 Scopus citations


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.
Original languageEnglish (US)
Pages (from-to)6591-6595
Number of pages5
JournalIEEE Transactions on Vehicular Technology
Issue number7
StatePublished - Dec 29 2016


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