… Moreover, they have evaluated their system using the advanced wireless network datasets.
… the deep learning methods. In addition, they are also used the standard machine learning …

… The recent success of deep learning underpins new and … the gap between deep learning
and mobile and wireless networking … gate methods that tailor deep learning to individual mobile …

… in wireless network applications: 1) Higher prediction accuracy. Wireless networks have …
, channel interference, etc. machine learning methods cannot analyze these features deeply …

… of the bytebased approaches for TC in wireless networks using a shared spectrum and
presents a general framework to perform TC at any layer of radio network stack using a spectrum …

… then present our considered deep learning system model. To describe our research problem
in an easy manner, we consider a simple wireless network backbone consisting of several …

… of machine learning and deep learning in wireless networks. … behaviour of network scenarios
in several adhoc networks (… data, deep learning (DL) is becoming a powerful method to add …

… is very important in a wireless network. In this paper, we propose a novel deep learning
approach for spatiotemporal modeling and prediction in cellular networks, using big system data. …

… The conventional approaches for wireless network optimization are discussed first, with a …
deep learning in the context of multi-hop wireless network flow optimization is also included. …

… techniques are not new to communication systems, and indeed several machine learning
approaches have been developed and proposed to aid the design and operation of …

… based protocol identification method, with the purpose of improving the performance of
QoE-based network management. Specifically, we introduce the deep learning based method for …