Machine Learning-Based Antenna Selection in Wireless Communications

doi:10.1109/LCOMM.2016.2594776

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Machine Learning-Based Antenna Selection in Wireless Communications

2016-11-01

141

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Jingon Joung *

DOI：10.1109/LCOMM.2016.2594776

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Abstract

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This letter is the first attempt to conflate a machine learning technique with wireless communications. Through interpreting the antenna selection (AS) in wireless communications (i.e., an optimization-driven decision) to multiclass-classification learning (i.e., data-driven prediction), and through comparing the learning-based AS using k-nearest neighbors and support vector machine algorithms with conventional optimization-driven AS methods in terms of communications performance, computational complexity, and feedback overhead, we provide insight into the potential of fusion of machine learning and wireless communications.

Keywords:

Machine learning

multiclass classification

k-NN

SVM

data-driven prediction (DDP)

optimization-driven decision (ODD)

antenna selection

MIMO

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