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Deep Learning-Based Automatic Modulation Classification with Prediction Combination in OFDM Systems
- 송건호;
- 마이클치솜;
- 최윤철;
- 장민규;
- Yoon, Dongweon
Citations
SCOPUS
5초록
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 classification; deep learning; orthogonal frequency division multiplexing; Cognitive radio; Deep learning; Learning systems; Orthogonal frequency division multiplexing
- 제목
- Deep Learning-Based Automatic Modulation Classification with Prediction Combination in OFDM Systems
- 저자
- 송건호; 마이클치솜; 최윤철; 장민규; Yoon, Dongweon
- 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