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This brief introduces the fundamental theory and development of managing radio resources using a water-filling algorithm that can optimize system performance in wireless communication. Geometric Water-Filling (GWF) is a crucial underlying tool in emerging communication systems such as multiple input multiple output systems, cognitive radio systems, and green communication systems. Early chapters introduce emerging wireless technologies and provide a detailed analysis of water-filling. The brief investigates single user and multi-user issues of radio resource management, allocation of resources, and energy harvesting. Effective algorithms demonstrate the incredible potential capabilities of water-filling mechanisms. This brief is designed for researchers and professionals working with resource management and wireless communications. Advanced-level students in computer science and engineering will also find the information valuable.
Radio resource management (Wireless communications). --- Wireless communication systems. --- Electrical & Computer Engineering --- Engineering & Applied Sciences --- Telecommunications --- Radio resource management (Wireless communications) --- Computer networks. --- Mathematical models. --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Wireless communications resource management --- Computer science. --- Computer communication systems. --- Electrical engineering. --- Computer Science. --- Computer Communication Networks. --- Communications Engineering, Networks. --- Resource allocation --- Wireless communication systems --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Electronic data processing --- Network computers --- Management --- Distributed processing --- Telecommunication. --- Electric communication --- Mass communication --- Telecom --- Telecommunication industry --- Communication --- Information theory --- Telecommuting --- Electric engineering --- Engineering
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This timely book provides broad coverage of vehicular ad-hoc network (VANET) issues, such as security, and network selection. Machine learning based methods are applied to solve these issues. This book also includes four rigorously refereed chapters from prominent international researchers working in this subject area. The material serves as a useful reference for researchers, graduate students, and practitioners seeking solutions to VANET communication and security related issues. This book will also help readers understand how to use machine learning to address the security and communication challenges in VANETs. Vehicular ad-hoc networks (VANETs) support vehicle-to-vehicle communications and vehicle-to-infrastructure communications to improve the transmission security, help build unmanned-driving, and support booming applications of onboard units (OBUs). The high mobility of OBUs and the large-scale dynamic network with fixed roadside units (RSUs) make the VANET vulnerable to jamming. The anti-jamming communication of VANETs can be significantly improved by using unmanned aerial vehicles (UAVs) to relay the OBU message. UAVs help relay the OBU message to improve the signal-to-interference-plus-noise-ratio of the OBU signals, and thus reduce the bit-error-rate of the OBU message, especially if the serving RSUs are blocked by jammers and/or interference, which is also demonstrated in this book. This book serves as a useful reference for researchers, graduate students, and practitioners seeking solutions to VANET communication and security related issues.
Computer networks. --- Mobile communication systems. --- Ad hoc networks (Computer networks) --- Wireless communication systems. --- Data protection. --- Artificial intelligence. --- Telecommunication. --- Wireless and Mobile Communication. --- Security. --- Artificial Intelligence. --- Communications Engineering, Networks. --- Vehicles --- Vehicular communication systems --- Radio --- Wireless communication systems --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Data governance --- Data regulation --- Personal data protection --- Protection, Data --- Communication systems, Wireless --- Wireless data communication systems --- Wireless information networks --- Wireless telecommunication systems --- Telecommunication systems --- Electric communication --- Mass communication --- Telecom --- Telecommunication industry --- Telecommunications --- Communication --- Information theory --- Telecommuting --- Communication systems --- Electrical engineering. --- Electric engineering --- Engineering
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This brief introduces the fundamental theory and development of managing radio resources using a water-filling algorithm that can optimize system performance in wireless communication. Geometric Water-Filling (GWF) is a crucial underlying tool in emerging communication systems such as multiple input multiple output systems, cognitive radio systems, and green communication systems. Early chapters introduce emerging wireless technologies and provide a detailed analysis of water-filling. The brief investigates single user and multi-user issues of radio resource management, allocation of resources, and energy harvesting. Effective algorithms demonstrate the incredible potential capabilities of water-filling mechanisms. This brief is designed for researchers and professionals working with resource management and wireless communications. Advanced-level students in computer science and engineering will also find the information valuable.
Telecommunication technology --- Mass communications --- Computer science --- Computer architecture. Operating systems --- computers --- tekstverwerking --- computernetwerken --- computerkunde --- communicatietechnologie
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This timely book provides broad coverage of vehicular ad-hoc network (VANET) issues, such as security, and network selection. Machine learning based methods are applied to solve these issues. This book also includes four rigorously refereed chapters from prominent international researchers working in this subject area. The material serves as a useful reference for researchers, graduate students, and practitioners seeking solutions to VANET communication and security related issues. This book will also help readers understand how to use machine learning to address the security and communication challenges in VANETs. Vehicular ad-hoc networks (VANETs) support vehicle-to-vehicle communications and vehicle-to-infrastructure communications to improve the transmission security, help build unmanned-driving, and support booming applications of onboard units (OBUs). The high mobility of OBUs and the large-scale dynamic network with fixed roadside units (RSUs) make the VANET vulnerable to jamming. The anti-jamming communication of VANETs can be significantly improved by using unmanned aerial vehicles (UAVs) to relay the OBU message. UAVs help relay the OBU message to improve the signal-to-interference-plus-noise-ratio of the OBU signals, and thus reduce the bit-error-rate of the OBU message, especially if the serving RSUs are blocked by jammers and/or interference, which is also demonstrated in this book. This book serves as a useful reference for researchers, graduate students, and practitioners seeking solutions to VANET communication and security related issues.
Telecommunication technology --- Production management --- Mass communications --- Computer architecture. Operating systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- veiligheid (mensen) --- ad-hocnetwerken --- machine learning --- tekstverwerking --- computerbeveiliging --- KI (kunstmatige intelligentie) --- mobiele communicatie --- communicatietechnologie --- AI (artificiële intelligentie)
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This book introduces wireless traffic steering as a paradigm to realize green communication in multi-tier heterogeneous cellular networks. By matching network resources and dynamic mobile traffic demand, traffic steering helps to reduce on-grid power consumption with on-demand services provided. This book reviews existing solutions from the perspectives of energy consumption reduction and renewable energy harvesting. Specifically, it explains how traffic steering can improve energy efficiency through intelligent traffic-resource matching. Several promising traffic steering approaches for dynamic network planning and renewable energy demand-supply balancing are discussed. This book presents an energy-aware traffic steering method for networks with energy harvesting, which optimizes the traffic allocated to each cell based on the renewable energy status. Renewable energy demand-supply balancing is a key factor in energy dynamics, aimed at enhancing renewable energy sustainability to reduce on-grid energy consumption. Dynamic network planning adjusts cell density with traffic variations to provide on-demand service, which reduces network power consumption with quality of service provisioning during off-peak hours. With intra- or inter-tier traffic steering, cell density is dynamically optimized with regards to the instant traffic load for conventional homogeneous and multi-tier heterogeneous cellular networks, respectively. This book is beneficial for researchers and graduate students interested in traffic management and future wireless networking.
Engineering. --- Renewable energy resources. --- Computer communication systems. --- Electrical engineering. --- Renewable energy sources. --- Alternate energy sources. --- Green energy industries. --- Communications Engineering, Networks. --- Renewable and Green Energy. --- Computer Communication Networks. --- Green energy industries --- Alternate energy sources --- Alternative energy sources --- Energy sources, Renewable --- Sustainable energy sources --- Electric engineering --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Construction --- Cell phone systems. --- Telecommunication --- Traffic. --- Telecommunication traffic --- Teletraffic --- Traffic engineering (Telecommunication) --- Traffic theory (Telecommunication) --- Cellular radio --- Cellular radiotelephone systems --- Cellular systems (Telecommunication) --- Cellular telephone systems --- Mobile telephony --- Wireless telephone systems (Cell phone) --- Mobile communication systems --- Telephone systems --- Telecommunication. --- Power resources --- Renewable natural resources --- Agriculture and energy --- Electric communication --- Mass communication --- Telecom --- Telecommunication industry --- Telecommunications --- Communication --- Information theory --- Telecommuting --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Cyberinfrastructure --- Electronic data processing --- Network computers --- Engineering --- Distributed processing --- Computer networks.
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Telecommunication technology --- Production management --- Mass communications --- Computer architecture. Operating systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- veiligheid (mensen) --- ad-hocnetwerken --- machine learning --- tekstverwerking --- computerbeveiliging --- KI (kunstmatige intelligentie) --- mobiele communicatie --- communicatietechnologie
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This book introduces wireless traffic steering as a paradigm to realize green communication in multi-tier heterogeneous cellular networks. By matching network resources and dynamic mobile traffic demand, traffic steering helps to reduce on-grid power consumption with on-demand services provided. This book reviews existing solutions from the perspectives of energy consumption reduction and renewable energy harvesting. Specifically, it explains how traffic steering can improve energy efficiency through intelligent traffic-resource matching. Several promising traffic steering approaches for dynamic network planning and renewable energy demand-supply balancing are discussed. This book presents an energy-aware traffic steering method for networks with energy harvesting, which optimizes the traffic allocated to each cell based on the renewable energy status. Renewable energy demand-supply balancing is a key factor in energy dynamics, aimed at enhancing renewable energy sustainability to reduce on-grid energy consumption. Dynamic network planning adjusts cell density with traffic variations to provide on-demand service, which reduces network power consumption with quality of service provisioning during off-peak hours. With intra- or inter-tier traffic steering, cell density is dynamically optimized with regards to the instant traffic load for conventional homogeneous and multi-tier heterogeneous cellular networks, respectively. This book is beneficial for researchers and graduate students interested in traffic management and future wireless networking.
Relation between energy and economics --- Electrical engineering --- Applied physical engineering --- Environmental protection. Environmental technology --- Mass communications --- Computer architecture. Operating systems --- energiemanagement (economie) --- alternatieve energie --- duurzame energie --- energie-economie --- draadloze computernetwerken --- hernieuwbare energie --- mobiele netwerken --- duurzaamheid --- industrie --- milieuproblematiek --- ingenieurswetenschappen --- computernetwerken --- elektrotechniek --- communicatietechnologie
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