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Transmit Antenna Selection for Large-Scale MIMO GSM With Machine Learning | IEEE Journals & Magazine | IEEE Xplore

Transmit Antenna Selection for Large-Scale MIMO GSM With Machine Learning


Abstract:

A dynamic and flexible generalized spatial modulation (GSM) framework is proposed for large-scale MIMO systems. Our framework is leveraged on the utilization of machine l...Show More

Abstract:

A dynamic and flexible generalized spatial modulation (GSM) framework is proposed for large-scale MIMO systems. Our framework is leveraged on the utilization of machine learning methods for GSM in order to improve the error performance in the presence of time-correlated channels and channel estimation errors. The decision tree and multi-layer perceptron algorithms are adopted as transmit antenna selection approaches. Simulation results indicate that in the presence of real-life impairments, machine learning based approaches provide a superior performance when compared to the classical Euclidean distance based approach. The observations are validated through measurement results over the designed 16 × 4 MIMO test-bed using software defined radio nodes.
Published in: IEEE Wireless Communications Letters ( Volume: 9, Issue: 1, January 2020)
Page(s): 113 - 116
Date of Publication: 27 September 2019

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