Lajos Hanzo

TL;DR: A taxonomy is introduced as a framework for systematically studying the existing user association algorithms conceived for HetNets, massive MIMO, mmWave, and energy harvesting networks and provides design guidelines and potential solutions for sophisticated user association mechanisms.

TL;DR: In this paper, the authors investigated the physical layer security of NOMA in large-scale networks with invoking stochastic geometry and derived new exact expressions of the security outage probability for both single-antenna and multipleantenna aided transmission scenarios.

TL;DR: This treatise discusses a range of critical issues related to the implementation, performance enhancement and optimization of FD systems, including important topics such as hybrid FD/HD scheme, optimal relay selection and optimal power allocation, etc.

TL;DR: Numerical results show that the shared deployment outperforms the separated case significantly, and the proposed weighted optimizations achieve a similar performance to the original optimizations, despite their significantly lower computational complexity.

TL;DR: In this article, the authors review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning and investigate their employment in the compelling applications of wireless networks, including heterogeneous networks, cognitive radios (CR), Internet of Things (IoT), machine to machine networks (M2M), and so on.