Automatic modulation recognition (AMR) detects the modulation scheme of the received
signals for further signal processing without needing prior information, and provides the …

Bioelectronics encompassing electronic components and circuits for accessing human
information play a vital role in real-time and continuous monitoring of biophysiological …

Due to the computing capability and memory limitations, it is difficult to apply the traditional
deep learning (DL) models to the edge devices (EDs) for realizing lightweight automatic …

Direct spread spectrum communication has the advantages of strong anti-jamming ability
and low probability of interception, which plays an essential role in both civil and military …

Automatic modulation classification (AMC) is of crucial importance in the sixth generation
wireless communication networks. Deep learning (DL)-based AMC schemes have attracted …

随着无线通信应用边界的不断扩展, 无线通信应用环境也日趋复杂多样, 面临射频损伤,
信道衰落, 干扰和噪声等负面影响, 给接收端恢复原始信息带来挑战. 借鉴深度学习方法在计算机 …

The concept of spectrum sensing has emerged as a fundamental solution to address the
growing demand for accessing the limited resources of wireless communications networks …

Automatic modulation classification for radio signals is an important task in many
applications, including cognitive radio, radio spectrum monitoring and signal decoding in …

It is difficult for traditional signal-recognition methods to effectively classify and identify
multiple emitter signals in a low SNR environment. This paper proposes a multi-emitter …

Despite the substantial success of deep learning for Automatic Modulation Classification
(AMC), models trained on a specific transmitter configuration and channel model often fail to …