Machine Learning-Based Antenna Selection in Wireless Communications

Abstract

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.