Adaptive constellation scheme for QAM using unsupervised learning

Abstract

This letter proposes an adaptive constellation scheme that uses an optimal constellation according to the signal-to-noise ratio. An efficient decision method based on unsupervised learning is proposed to ensure satisfactory error performance of the adaptive constellation scheme. Upon verification, the proposed scheme is found to exhibit improved error performance, compared to the fixed constellation scheme.