Work

Adaptive constellation scheme for QAM using unsupervised learning

Year: 2024

Type: article

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.

Source: Electronics Letters

DOI: 10.1049/ell2.70086

Author: Yeonsoo Jang

Institution: Jeju National University

Language: English

Topic: Advanced Wireless Communication Techniques

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,540

Funders: National Research Foundation, National Research Foundation of Korea, Ministry of Education, India