目前的频谱感知算法以模型驱动为主, 其感知性能过于依赖预定的统计模型,
这使得其在信道环境复杂的卫星通信场景中的部署变得困难. 对LEO 卫星过境期间的信噪比 …

In this thesis, we investigate the designs of pragmatic data detectors and channel decoders
with the assistance of deep learning. We focus on three emerging and fundamental research …

Demand for wireless connectivity has never been higher and continues to grow rapidly.
Connecting more devices requires mindfulness in managing the limited resources of energy …

Wireless electromagnetic transmission using layered annulus space made up of tubing,
casing and packer in production wells is an effective means of overcoming the corrosion …

In wireless communication systems, a received signal is corrupted by various means, such
as noise, multi-path fading, and defects in hardware. To properly demodulate the signal and …

Underwater acoustic channel is a frequency selective fading channel with severe multipath
effect and significant Doppler shift, which greatly limits the performance of underwater …

Deep learning (DL) is one of the fastest developing areas in artificial intelligence, it has been
recently gained studies and application in computer vision, automatic driving, automatic …

Performance analysis of a Deep Neural Network for digital demodulation in Gridless Nyquist-WDM
Systems Page 1 Performance analysis of a Deep Neural Network for digital demodulation in …

This paper presents a data-driven unsupervised Deep Learning-based joint channel
estimation and signal detection method for a narrowband wireless communication system …

Future wireless communications is expected to bring significant changes along with a
number of emerging technologies such as 5G, virtual reality, edge computing, and IoT …