This monograph presents a unified framework for energy efficiency maximization in wireless
networks via fractional programming theory. The definition of energy efficiency is introduced …

Many contemporary signal processing, machine learning and wireless communication
applications can be formulated as nonconvex nonsmooth optimization problems. Often there …

A framework for energy-efficient resource allocation in a single-user, amplify-and-forward
(AF), relay-assisted, multiple-input-multiple-output (MIMO) system is devised in this paper …

In this paper, we study an amplify-and-forward relay network with energy harvesting (EH)
source and relay nodes. Both nodes can continuously harvest energy from the environment …

In this article, we consider a resilient consensus problem for the multi-agent network where
some of the agents are subject to Byzantine attacks and may transmit erroneous state values …

This paper investigates relaying schemes in an amplify-and-forward multiple-input multiple-
output relay network, where an energy-constrained relay harvests wireless power from the …

In this paper, we propose a closed-form (ie, without the need of any iterative procedure) joint
optimization framework of the source precoder, the amplify-and-forward relaying matrices …

Many problems of recent interest in signal processing, machine learning and wireless
communications can be posed as nonconvex nonsmooth optimization problems. These …

In Part I of this paper, we proposed and analyzed a novel algorithmic framework, termed
penalty dual decomposition (PDD), for the minimization of a nonconvex nonsmooth …

Many contemporary signal processing, machine learning and wireless communication
applications can be formulated as nonconvex nonsmooth optimization problems. Often there …