arrow
Return

Adaptive Modulation and Coding Using Neural Network Based SNR Estimation

delete2019-01-01
delete34
delete
OA
AI
S
Shun Kojima *
K
Kazuki Maruta
DOI:10.1109/ACCESS.2019.2946973delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
In this paper, we propose a novel Adaptive Modulation and Coding (AMC) scheme enabled by Artificial Neural Network (ANN) aided Signal-to-Noise power Ratio (SNR) estimation. The Power Spectral Density (PSD) values are trained for SNR classification and it is mapped to respective Modulation and Coding Scheme (MCS) sets. Once trained, optimal MCS can be determined in low calculation complexity. The proposed approach is robust especially in high mobility environment since the PSD appearance is hardly influenced by the Doppler shift. Its effectiveness in terms of throughput is presented through computer simulations compared to the existing Error Vector Magnitude (EVM) based link adaptation scheme.
Keywords:
SNR estimation
artificial neural network
adaptive modulation and coding
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Access cover
IEEE Access
IF:
3.6
Papers:
9.7W
Citations:
29.4W

Organization

C
Chiba University
Scholars:
1.5W
Papers: 1.1W
Citations: 1.0W