计算机科学
调制(音乐)
调制指数
GSM网络
杠杆(统计)
语音识别
人工智能
模式识别(心理学)
电子工程
脉冲宽度调制
电信
哲学
物理
美学
量子力学
电压
工程类
作者
Mehmet Merih Leblebici,Ali Çalhan,Murtaza Ci̇ci̇oğlu
标识
DOI:10.1016/j.eswa.2023.122665
摘要
Automatic modulation recognition (AMR) has garnered significant attention in both civilian and military domains, with applications ranging from spectrum sensing and cognitive radio (CR) to the deterrence of adversary communication. Index modulation (IM) represents an innovative digital modulation technique that exploits the indices of parameters of communication systems to transmit extra information bits. This paper aims to examine the performance of a convolutional neural network (CNN)-based AMR across various IM systems, including spatial modulation (SM), quadrature spatial modulation (QSM), and generalized spatial modulation (GSM) with eight digital modulation schemes. In this study, we leverage confusion matrices, receiver operating characteristic (ROC) curves, and F1 scores to illustrate the recognition model's outputs.
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