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Machine Learning-Based Antenna Selection in Wireless Communications
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200초록
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 learning; multiclass classification; k-NN; SVM; data-driven prediction (DDP); optimization-driven decision (ODD); antenna selection; MIMO
- 제목
- Machine Learning-Based Antenna Selection in Wireless Communications
- 저자
- Joung, Jingon
- 발행일
- 2016-11
- 유형
- Article
- 권
- 20
- 호
- 11
- 페이지
- 2241 ~ 2244