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

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 …

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 …

Resource allocation and transceivers in wireless networks are usually designed by solving
optimization problems subject to specific constraints, which can be formulated as variable or …

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 …

Mathematical optimization is now widely regarded as an indispensable modeling and
solution tool for the design of wireless communications systems. While optimization has …

The recent revival of AI is revolutionizing almost every branch of science and technology.
Given the ubiquitous smart mobile gadgets and IoT devices, it is expected that a majority of …

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

A comprehensive review to the theory, application and research of machine learning for
future wireless communications In one single volume, Machine Learning for Future Wireless …

Fueled by recent advances in deep neural networks, reinforcement learning (RL) has been
in the limelight because of many recent breakthroughs in artificial intelligence, including …