Machine Learning-Based Antenna Selection in Wireless Communications

Citations

WEB OF SCIENCE

159
Citations

SCOPUS

200

초록

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.

키워드

Machine learningmulticlass classificationk-NNSVMdata-driven prediction (DDP)optimization-driven decision (ODD)antenna selectionMIMO
제목
Machine Learning-Based Antenna Selection in Wireless Communications
저자
Joung, Jingon
DOI
10.1109/LCOMM.2016.2594776
발행일
2016-11
유형
Article
저널명
IEEE Communications Letters
20
11
페이지
2241 ~ 2244