… the pressure of spectrum usage in wireless communication, based on the … to wireless
communication networks. An intelligent power algorithm model based on deep neural networks (…

… Recently, thanks to its strong learning ability and low testing complexity, deep neural network
(DNN) has made great success in optimization problems in wireless communication, such …

… -based approach for wireless resource management. The … -linear mapping and to use a
deep neural network (DNN) to … some algorithms of interest in wireless communications. We use …

… a wireless powered communication network (WPCN). We provide a study and analysis of a
deep neural network … In this scheme, the deep neural network provides an optimized solution …

… a novel neural network structure for jointly optimizing the transmitter and receiver in
communication … The property of convolutional neural network enables the network to process input …

… Since the first generation (1G) wireless communication network entered the market in the
1980s, the world has been dramatically changed by the development of mobile communication …

… systems, especially when there are many wireless communication devices and various
noise and interference sources present in the environment. The deep neural network (DNN) …

… [12] modified the widely used belief propagation (BP) algorithm by cascading a Convolutional
Neural Network (CNN) to the standard BP decoder, which succeeds in outputting a more …

… in this paper, we propose DL gated recurrent unit (GRU) neural networks for channel estimation
of data subcarriers as an innovative approach where the computation requirements can …

… In this paper, we exploit the popular convolutional neural networks (CNNs) to capture the
spatial local correlation by enforcing a local connectivity pattern among the neurons of …