Deep learning based on artificial neural networks (ANNs) is a powerful machine-learning
method that, in recent years, has been successfully used to realize tasks such as image …

Next-generation wireless networks must support ultra-reliable, low-latency communication
and intelligently manage a massive number of Internet of Things (IoT) devices in real-time …

This paper deals with the use of emerging deep learning techniques in future wireless
communication networks. It will be shown that the data-driven approaches should not …

In order to effectively provide ultra reliable low latency communications and pervasive
connectivity for Internet of Things (IoT) devices, next-generation wireless networks can …

The design of modern wireless networks, which involves decision making and parameter
optimization, is quite challenging due to the highly dynamic, and often unknown …

Next-generation wireless networks are expected to support extremely high data rates and
radically new applications, which require a new wireless radio technology paradigm. The …

Future wireless networks have a substantial potential in terms of supporting a broad range of
complex compelling applications both in military and civilian fields, where the users are able …

Despite the growing interest in the interplay of machine learning and optimization, existing
contributions remain scattered across the research board, and a comprehensive overview …

With the rapid development of mobile devices and deep learning, mobile smart applications
using deep learning technology have sprung up. It satisfies multiple needs of users, network …

Traditional communication system design has always been based on the paradigm of first
establishing a mathematical model of the communication channel, then designing and …