Deep learning has been widely exploited in radio modulation recognition in recent years. In
this paper, we exploit empirical mode decomposition (EMD) and variational mode …

Due to the constraint of spectrum availability in the recent era, technologies such as
cognitive radio and spectrum sensing have found a central stage in the communications …

This paper presents a novel hybrid extreme learning machine (ELM) with cuckoo search
algorithm (CSA) for the classification purposes of the digitally modulated signals, such as …

Blind modulation recognition (BMR) has been proposed as a promising approach for
massive multiple-input multiple-output (M-MIMO) systems to support massive user …

We present a novel modulation recognition for weighted-type fractional Fourier transform
(WFRFT)-based systems using the fourth-order cumulants. First, the constellation …

Automatic modulation recognition (AMR) is used in various domains—from general-purpose
communication to many military applications—thanks to the growing popularity of the …

针对现实信号调制方式标注易发生错误, 即训练数据集中信号调制方式标签存在噪声情形,
我们选取l 1 模损失函数及其推广形式作为对标签噪声具有鲁棒性的损失函数 …

Automatic modulation classification (AMC), which aims to identify the modulation types of
unknown signals without any prior knowledge, plays a key role in intelligent wireless …

Automatic modulation classification (AMC) plays a crucial role in the stages of processing
signals from unknown sources and monitoring the airwaves. This paper presents an AMC …

Automatic Modulation Classification (AMC) is an essential technology that is widely applied
into various communications scenarios. In recent years, many Machine Learning and Deep …