… Specifically, most studies in the physical layer have tended to focus on the application of
DNN models to wireless communication problems but not to theoretically understand how does …

… fold throughput improvements of future wireless communications, ultra-dense network (UDN)
where … An aim of this paper is to propose a deep neural network (DNN)-based framework to …

… the use of neural networks in the specific wireless application. … the use of neural networks
in wireless communications and, as … : recurrent neural networks, spiking neural networks, and …

… deep neural network (DNN), which is a basic model of deep … to solve problems on wireless
communications too. There are … taken seriously in deep learning of wireless communication. …

… a specially designed deep neural network (DNN) based on the deep image prior (DIP) network
to … We analytically prove that our LS-type deep channel estimator can approach minimum …

… A convolutional neural network (CNN) is effective when extracting spatial features, while a …
, deep learning, beyond 5G wireless communication systems, and wireless energy harvesting. …

… deep neural … is a neural network consisting of sub neural networks M𝑖,𝑖 = 1, ··· , 𝑛. The
module functions 𝑓1, ··· , 𝑓𝑛 generate 𝑔 for M if, by replacing M𝑖 with 𝑓𝑖, the neural network M …

… solve various problems in wireless networks and IoT systems [… interesting applications in
wireless communications, such as … coverage prediction in random wireless networks [20]. One …

… Deep Learning (DL), one of the most exciting developments … potential in the study of wireless
communications. In this article… Deep neural networks are used to replace a single or several …

… We present a deep learning framework based on deep neural networks (DNNs) for 5G …
more reliable wireless communications through channel hardening, since the wireless channel …