… a deep learning based end-to-end communication system for general wireless channels,
where … This problem is formulated as training a deep auto-encoder network with an untrainable …

Deep learning (DL) has proven its unprecedented … 6G wireless networks, new applications
and use cases have been emerging with stringent requirements for next-generation wireless …

… some major challenges to develop an effective wireless intrusion detection mechanism: (1) …
wireless network intrusion detection mechanism based on Conditional Deep Belief Network …

… With the development of wireless network and computer technology, wireless network …
capability in the wireless network environment. At present, deep learning is currently used in many …

… Recently, deep learning has been applied to refine the … In addition, deep learning based
methods have also shown … the traditional communication blocks, deep learning provides a new …

… purpose learning procedure. Sparked by the advantages of deep learning, we aim to provide
a novel deep learning … of QoE-based network management. Specifically, we introduce the …

… systems in the wireless domain. We postulate a series of adversarial … Wireless Adversarial
Machine Learning Problem (GWAP) where we analyze the combined effect of the wireless …

… learning to learn the spectrum and make their transmit decisions by adapting to the spectrum
dynamics. We study a canonical wireless … in a dynamic wireless environment with complex …

… First, we develop a new LSTM based deep learning solution using time domain amplitude …
of deep learning models for technology classification task in a distributed sensor network only …

… Leveraging on that, we propose a topology-aware deep learning (TADL) framework as
illustrated in fig. 1 for wireless network flow optimization. This is to tackle the aforementioned …