Practical Channel-Aware Resource Allocation

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Details

This book dives into radio resource allocation optimizations, a research area for wireless communications, in a pragmatic way and not only includes wireless channel conditions but also incorporates the channel in a simple and practical fashion via well-understood equations. Most importantly, the book presents a practical perspective by modeling channel conditions using terrain-aware propagation which narrows the gap between purely theoretical work and that of industry methods. The provided propagation modeling reflects industry grade scenarios for radio environment map and hence makes the channel based resource allocation presented in the book a field-grade view. Also, the book provides large scale simulations that account for realistic locations with terrain conditions that can produce realistic scenarios applicable in the field. Most portions of the book are accompanied with MATLAB code and occasionally MATLAB/Python/C code. The book is intended for graduate students, academics, researchers of resource allocation in mathematics, computer science, and electrical engineering departments as well as working professionals/engineers in wireless industry.

Presents radio resource allocation optimizations, including wireless channel conditions and incorporating the channel in a simple and practical fashion Includes a mathematical analysis of resource allocation with a practical industry-like propagation model Provides an introduction of terrain-based propagation modeling into radio resource allocation optimization

Autorentext

Michael Ghorbanzadeh is an industry practitioner, with an expertise in spectrum sharing, who currently works on shaping radio frequency spectrum policies related to the United States' Federal government as an Electronics Engineer in the National Telecommunications and Information Administration (NTIA) in Washington DC. Before NTIA, he worked as one of the first engineers of Federated Wireless, a startup in Arlington, VA, to commercialize spectrum sharing in the 3.5 GHz band. He has a PhD in Electrical Engineering from Virginia Tech, has published many conference and journal articles, and is an IEEE senior member.

Ahmed Abdelhadi, PhD, is an Assistant Professor in the Department of Engineering Technology at the University of Houston. His research interests are in the areas of wireless systems, cyber physical systems, machine learning, and security. Dr. Abdelhadi published more than 70 journal and conference papers and 6 books in these research topics. He is the recipient of the Best Paper Award from IEEE International Symposium on Systems Engineering (ISSE) in 2019 and the Outstanding Paper Award from IEEE International Conference of Advanced Communications Technology (ICACT) in 2020 and is a senior member of IEEE. Before joining UH, he was a Research Assistant Professor in Bradley Department of Electrical and Computer Engineering and Hume Center for National Security and Technology at Virginia Tech. He was a faculty member of Wireless @ Virginia Tech. He received his Ph.D. in Electrical and Computer Engineering from the University of Texas at Austin in 2011. He was a member in Wireless Networking and Communications Group (WNCG) and Laboratory of Informatics, Networks and Communications (LINC) group during his Ph.D.

Inhalt

Introduction.- Utility Functions and Resource Allocation.- Resource Allocation without Channel.- Distributed or Centralized.- Channel Conditions and Resource Allocation.- Propagation Modeling .- Simulation.- Conclusion. <p

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783030736316
    • Lesemotiv Verstehen
    • Genre Electrical Engineering
    • Auflage 1st edition 2022
    • Sprache Englisch
    • Anzahl Seiten 252
    • Herausgeber Springer International Publishing
    • Größe H241mm x B160mm x T20mm
    • Jahr 2021
    • EAN 9783030736316
    • Format Fester Einband
    • ISBN 3030736318
    • Veröffentlichung 09.07.2021
    • Titel Practical Channel-Aware Resource Allocation
    • Autor Ahmed Abdelhadi , Michael Ghorbanzadeh
    • Untertitel With MATLAB and Python Code
    • Gewicht 547g

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