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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Peng Yang received his B.E. degree in Communication Engineering and Ph.D. degree in Information and Communication Engineering from Huazhong University of Science and Technology (HUST), Wuhan, China, in 2013 and 2018, respectively. He was with the Department of Electrical and Computer Engineering, University of Waterloo, Canada, as a Visiting Ph.D. Student from Sept. 2015 to Sept. 2017, and a Postdoctoral Fellow from Sept. 2018 to Dec. 2019. Since 2020, he has been an Associate Professor with the School of Electronic Information and Communications, HUST. His current research focuses on wireless networking, mobile edge computing, video streaming and analytics.
Wen Wu received the B.E. degree in Information Engineering from South China University of Technology, Guangzhou, China, and the M.E. degree in Electrical Engineering from University of Science and Technology of China, Hefei, China, in 2012 and 2015, respectively. He received the Ph.D. degree in Electrical and Computer Engineering from University of Waterloo, Waterloo, ON, Canada, in 2019. Starting from 2019, he works as a Post-doctoral fellow with the Department of Electrical and Computer Engineering, University of Waterloo. His research interests include millimeter-wave networks and AI-empowered wireless networks.
Ning Zhang received the B.Sc. degree from Beijing Jiaotong University, Beijing, China, the M.Sc. degree from Beijing University of Posts and Telecommunications, Beijing, China, and the Ph.D. degree from the University of Waterloo, Waterloo, ON, Canada, in 2007, 2010, and 2015, respectively. After that, he was a postdoc research fellow at University of Waterloo and University of Toronto, Canada, respectively. He is now an Associate Professor at University of Windsor, Canada. His research interests include vehicular and wireless networking, mobile edge computing, and security. He serves as an Associate Editor of IEEE Internet of Things Journal, IEEE Transactions on Cognitive Communications and Networking, and IET Communications. He also serves/served as a TPC chair for IEEE VTC-Fall 2021 and IEEE SAGC 2020, a general chair for IEEE SAGC 2021, and a track/symposium chair for several international conferences and workshops, such as IEEE ICC and IEEE VTC. He has been a senior member of IEEE since 2018.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : Best Price, Torrance, CA, Etats-Unis
Etat : New. SUPER FAST SHIPPING. N° de réf. du vendeur 9783030886295
Quantité disponible : 4 disponible(s)
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : New. N° de réf. du vendeur 44025959-n
Quantité disponible : Plus de 20 disponibles
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Etat : New. In. N° de réf. du vendeur ria9783030886295_new
Quantité disponible : Plus de 20 disponibles
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : New. N° de réf. du vendeur 44025959-n
Quantité disponible : Plus de 20 disponibles
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
Etat : New. N° de réf. du vendeur ABLIING23Mar3113020032456
Quantité disponible : Plus de 20 disponibles
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 44025959
Quantité disponible : Plus de 20 disponibles
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 44025959
Quantité disponible : Plus de 20 disponibles
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 172 pp. Englisch. N° de réf. du vendeur 9783030886295
Quantité disponible : 2 disponible(s)
Vendeur : moluna, Greven, Allemagne
Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. First comprehensive books on beam alignment scheme in mmWave networks from a machine learning perspectiveProvides a review of the state-of-the-art beamforming related technologies in mmWave networksPresents the latest studies of performance. N° de réf. du vendeur 506747891
Quantité disponible : Plus de 20 disponibles
Vendeur : preigu, Osnabrück, Allemagne
Buch. Etat : Neu. Millimeter-Wave Networks | Beamforming Design and Performance Analysis | Peng Yang (u. a.) | Buch | xii | Englisch | 2021 | Springer International Publishing | EAN 9783030886295 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. N° de réf. du vendeur 120516009
Quantité disponible : 5 disponible(s)