Due to the implementation and performance limitations of centralized learning automatic
modulation classification (CentAMC) method, this paper proposes a decentralized learning …

In order to address the issue of spectrum scarcity, cognitive radio (CR) offers an effective
usage of radio spectrum resources by offering dynamic spectrum access. One kind of …

Deep learning (DL)-based automatic modulation classification (AMC) is a primary research
field for identifying modulation types. However, traditional DL-based AMC approaches rely …

With the proliferation of frequency-using devices and the advent of the era of big data,
spectrum management and control are faced with challenges of effectiveness and accuracy …

This paper presents an efficient deep neural network (DNN) accelerator designed for radio
frequency (RF) signal modulation recognition. A novel DNN design optimized for mobile …

Aiming at the difficulty of data collection in the actual speech communication
countermeasure and the lack of research on the disturbed speech in the strong jamming …

Interference is a common problem in wireless communication, navigation and radar
systems. A wide variety of interferences are used to degrade the communication quality …

This paper presents an efficient Deep Neural Network (DNN) design optimized for the
modulation classification of the received Radio Frequency (RF) signal. Considering that the …

This paper proposes a decentralized automatic modulation classification (DecentAMC)
method using light network and model aggregation. Specifically, the lightweight network is …

In recent years, there has been a rapid growth in the development and usage of flying
drones due to their diverse capabilities worldwide. Public and private sectors will actively …