Blind channel identification aided generalized automatic modulation recognition based on deep learning
Automatic modulation recognition (AMR) plays an important role in cognitive radio (CR),
which relies on AMR responding to changes in the surrounding environment and then adjust …
which relies on AMR responding to changes in the surrounding environment and then adjust …
Deep learning aided method for automatic modulation recognition
C Yang, Z He, Y Peng, Y Wang, J Yang - IEEE Access, 2019 - ieeexplore.ieee.org
Automatic modulation recognition (AMR) is considered one of most important techniques in
the non-cooperative wireless communication systems. Traditional algorithms, eg, support …
the non-cooperative wireless communication systems. Traditional algorithms, eg, support …
Antifragile communications
This paper introduces the concept of antifragile communications, which we define as the
capability for a communications system to improve in performance due to a system stressor …
capability for a communications system to improve in performance due to a system stressor …
Convolutional neural network aided signal modulation recognition in OFDM systems
Signa1 modulation recognition (SMR) is an essential and challenging topic in orthogonal
frequency-division multiplexing (OFDM) systems, and also it is the fundamental technique …
frequency-division multiplexing (OFDM) systems, and also it is the fundamental technique …
Blind digital modulation classification for STBC‐OFDM system in presence of CFO and channels estimation errors
Here, the authors propose a robust blind digital modulation classification (BDMC) algorithm
for space time block coding (STBC)‐based MIMO‐OFDM system in the presence of carrier …
for space time block coding (STBC)‐based MIMO‐OFDM system in the presence of carrier …
Decoupling RNN training and testing observation intervals for spectrum sensing applications
Recurrent neural networks have been shown to outperform other architectures when
processing temporally correlated data, such as from wireless communication signals …
processing temporally correlated data, such as from wireless communication signals …
Deep learning-based automatic modulation recognition algorithm in non-cooperative communication systems
Z He, Y Peng, Y Zhao, J Yang, L Wang… - 2019 11th …, 2019 - ieeexplore.ieee.org
Automatic modulation recognition (AMR) is considered one of most important topics in non-
cooperative communication systems. Traditional algorithms, eg, high order cumulants (HOC) …
cooperative communication systems. Traditional algorithms, eg, high order cumulants (HOC) …
The role and applications of machine learning in future self-organizing cellular networks
In this chapter, a brief overview of the role and applications of machine learning (ML)
algorithms in future wireless cellular networks is presented, more specifically, in the context …
algorithms in future wireless cellular networks is presented, more specifically, in the context …
Deep learning aided friendly coexistence of WiFi and LTE in unlicensed bands
Unlicensed long term evolution (LTE) technology is considered one of promising solutions to
address the problem of limited spectrum resources with the booming of big data and internet …
address the problem of limited spectrum resources with the booming of big data and internet …
Interference modulation order detection with supervised learning for lte interference cancellation
TP Low, J Moon - 2015 IEEE 82nd Vehicular Technology …, 2015 - ieeexplore.ieee.org
Blind detection of interference modulation order is studied in this paper. Exploiting the
additivity property of cumulants for independent variables, we extend the techniques used in …
additivity property of cumulants for independent variables, we extend the techniques used in …