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This book thoroughly examines the design of full-duplex medium access control (MAC) protocols in wireless networks. It is organized into three main sections: (a) Fundamentals and preliminaries of full-duplex communications, (b) A comprehensive review of the existing full-duplex MAC protocols, and (c) Designs of full-duplex MAC protocols in three typical wireless networks, i.e., wireless local access networks (WLANs), multi-hop networks and millimeter-wave networks. Also, the authors extensively address key challenges in these three wireless full-duplex networks, such as the hidden-node problem, accumulative interference, and deafness and blockage problems. Solutions to these challenges are meticulously devised to enhance the overall network performance. The wireless full-duplex communication technique, facilitating simultaneous transmission and reception within the same frequency band, holds immense potential for enhancing spectrum efficiency and network capacity. It emerges as a pivotal technology in the sixth-generation (6G) networks. This book provides a comprehensive review and in-depth exploration of full-duplex MAC design across various networks, encompassing WLANs, multi-hop networks, and millimeter-wave networks. Acknowledging the challenges faced by full-duplex WLANs, particularly the hidden-node problem, it also introduces a pioneering hidden-node-free design and a MAC protocol design, which features a full-duplex enhanced carrier-sensing mechanism. Addressing the need to augment end-to-end throughput in multi-hop networks employing full-duplex relaying, the authors present an analytical model for end-to-end throughput and propose a multi-hop full-duplex MAC protocol designed to optimize network performance. Furthermore, the exploration extends to full-duplex millimeter-wave networks, delving into issues of deafness and blockage. A directional full-duplex MAC protocol is introduced to enhance network capacity and mitigate blockage problems. This book concludes by outlining prospective research directions within the related fields of study and offers valuable insights for future exploration. This book targets researchers and advanced level students in computer science and electrical engineering. It also caters to professionals engaged in the fields of wireless networks, full-duplex system, protocol design, and network optimization will also buy this book.

This book provides a comprehensive review and in-depth discussion of the state-of-the-art research literature and propose energy-efficient computation offloading and resources management for mobile edge computing (MEC), covering task offloading, channel allocation, frequency scaling and resource scheduling. Since the task arrival process and channel conditions are stochastic and dynamic, the authors first propose an energy efficient dynamic computing offloading scheme to minimize energy consumption and guarantee end devices'delay performance. To further improve energy efficiency combined with tail energy, the authors present a computation offloading and frequency scaling scheme to jointly deal with the stochastic task allocation and CPU-cycle frequency scaling for minimal energy consumption while guaranteeing the system stability. They also investigate delay-aware and energy-efficient computation offloading in a dynamic MEC system with multiple edge servers, and introduce anend-to-end deep reinforcement learning (DRL) approach to select the best edge server for offloading and allocate the optimal computational resource such that the expected long-term utility is maximized. Finally, the authors study the multi-task computation offloading in multi-access MEC via non-orthogonal multiple access (NOMA) and accounting for the time-varying channel conditions. An online algorithm based on DRL is proposed to efficiently learn the near-optimal offloading solutions.Researchers working in mobile edge computing, task offloading and resource management, as well as advanced level students in electrical and computer engineering, telecommunications, computer science or other related disciplines will find this book useful as a reference. Professionals working within these related fields will also benefit from this book.

This book provides a comprehensive review and in-depth study on efficient beamforming design and rigorous performance analysis in mmWave networks, covering beam alignment, beamforming training and beamforming-aided caching. Due to significant beam alignment latency between the transmitter and the receiver in existing mmWave systems, this book proposes a machine learning based beam alignment algorithm for mmWave networks to determine the optimal beam pair with a low latency. Then, to analyze and enhance the performance of beamforming training (BFT) protocol in 802.11ad mmWave networks, an analytical model is presented to evaluate the performance of BFT protocol and an enhancement scheme is proposed to improve its performance in high user density scenarios. Furthermore, it investigates the beamforming-aided caching problem in mmWave networks, and proposes a device-to-device assisted cooperative edge caching to alleviate backhaul congestion and reduce content retrieval delay. This book concludes with future research directions in the related fields of study. The presented beamforming designs and the corresponding research results covered in this book, provides valuable insights for practical mmWave network deployment and motivate new ideas for future mmWave networking.This book targets researchers working in the fields of mmWave networks, beamforming design, and resource management as well as graduate students studying the areas of electrical engineering, computing engineering and computer science. Professionals in industry who work in this field will find this book useful as a reference.