A survey on machine learning-based performance improvement of wireless networks: PHY, MAC and network layer
This paper presents a systematic and comprehensive survey that reviews the latest research
efforts focused on machine learning (ML) based performance improvement of wireless …
efforts focused on machine learning (ML) based performance improvement of wireless …
A survey of modulation classification using deep learning: Signal representation and data preprocessing
Modulation classification is one of the key tasks for communications systems monitoring,
management, and control for addressing technical issues, including spectrum awareness …
management, and control for addressing technical issues, including spectrum awareness …
Deep learning models for wireless signal classification with distributed low-cost spectrum sensors
This paper looks into the modulation classification problem for a distributed wireless
spectrum sensing network. First, a new data-driven model for automatic modulation …
spectrum sensing network. First, a new data-driven model for automatic modulation …
[HTML][HTML] Fedstellar: A platform for decentralized federated learning
Abstract In 2016, Google proposed Federated Learning (FL) as a novel paradigm to train
Machine Learning (ML) models across the participants of a federation while preserving data …
Machine Learning (ML) models across the participants of a federation while preserving data …
End-to-end learning from spectrum data: A deep learning approach for wireless signal identification in spectrum monitoring applications
This paper presents end-to-end learning from spectrum data-an umbrella term for new
sophisticated wireless signal identification approaches in spectrum monitoring applications …
sophisticated wireless signal identification approaches in spectrum monitoring applications …
Machine learning for wireless link quality estimation: A survey
Since the emergence of wireless communication networks, a plethora of research papers
focus their attention on the quality aspects of wireless links. The analysis of the rich body of …
focus their attention on the quality aspects of wireless links. The analysis of the rich body of …
Real-time radio technology and modulation classification via an LSTM auto-encoder
Identification of the type of communication technology and/or modulation scheme based on
detected radio signal are challenging problems encountered in a variety of applications …
detected radio signal are challenging problems encountered in a variety of applications …
Fusion methods for CNN-based automatic modulation classification
An automatic modulation classification has a very broad application in wireless
communications. Recently, deep learning has been used to solve this problem and …
communications. Recently, deep learning has been used to solve this problem and …
Reinforcement learning-based multislot double-threshold spectrum sensing with Bayesian fusion for industrial big spectrum data
With the rapid increase of industrial systems, industrial spectrum is step** into the era of
big data, and at the same time spectrum resources are facing serious shortage. Cognitive …
big data, and at the same time spectrum resources are facing serious shortage. Cognitive …
Intelligent and behavioral-based detection of malware in IoT spectrum sensors
Abstract The number of Cyber-Physical Systems (CPS) available in industrial environments
is growing mainly due to the evolution of the Internet-of-Things (IoT) paradigm. In such a …
is growing mainly due to the evolution of the Internet-of-Things (IoT) paradigm. In such a …