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Machine Learning-Based Antenna Selection in Wireless Communications
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DOI：10.1109/LCOMM.2016.2594776.png)
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摘要
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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.
Keyword:
Machine learning
multiclass classification
k-NN
SVM
data-driven prediction (DDP)
optimization-driven decision (ODD)
antenna selection
MIMO
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期刊
IF:
4.4
论文数:
1.3W
被引数:
2.2W
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