Deep Learning-Based Automatic Modulation Classification with Prediction Combination in OFDM Systems

Citations

SCOPUS

5

초록

Automatic modulation classification (AMC) is one of the important tasks in cognitive radios and spectrum surveillance. This paper proposes a deep learning (DL)-based AMC with prediction combination method for orthogonal frequency division multiplexing (OFDM) systems. We first predict the subcarrier modulation scheme of the transmitted OFDM signal with different DL models and then combine those predictions using the proposed prediction combination method to make the final decision. Through computer simulations, we show that the classification performance can be improved by the proposed prediction combination method in terms of classification accuracy.

키워드

automatic modulation classificationdeep learningorthogonal frequency division multiplexingCognitive radioDeep learningLearning systemsOrthogonal frequency division multiplexing
제목
Deep Learning-Based Automatic Modulation Classification with Prediction Combination in OFDM Systems
저자
송건호마이클치솜최윤철장민규Yoon, Dongweon
DOI
10.1109/IC-NIDC59918.2023.10390713
발행일
2023-11
유형
Conference paper
저널명
Proceedings of 2023 8th IEEE International Conference on Network Intelligence and Digital Content, IC-NIDC 2023
페이지
336 ~ 340