Cognitive Radio-Oriented Wireless Networks

14th EAI International Conference, CrownCom 2019, Poznan, Poland, June 11¿12, 2019, Proceedings
1. Auflage 2019
ISBN: 978-3-030-25747-7
Verlag: Springer International Publishing

Buch, Englisch, Band 291, 410 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 639 g

Reihe: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

This book constitutes the refereed proceedings of the 14th International Conference on Cognitive Radio-Oriented Wireless Networks, CROWNCOM 2019, held in Poznan, Poland, in June 2019. The 30 revised full papers were selected from 48 submissions and present a large scope of research topic also covering IoT in 5G and how cognitive mechanisms shall help leveraging access for numerous devices; mmWave and how specific propagation and operation in these bands bring new sharing mechanisms; how resource allocation amongst bands (including offload mechanisms) shall be solved. The key focus will be on how rich data analysis can improve the delivery of above defined services.

Zielgruppe

Research

Autoren/Hrsg.

Kliks, Adrian

Kryszkiewicz, Pawe¿

Kryszkiewicz, Pawel

Bader, Faouzi

Sybis, Micha¿

Triantafyllopoulou, Dionysia

Caicedo, Carlos E.

Sezgin, Aydin

Dimitriou, Nikos

Sybis, Michal

Fachgebiete

• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Mobilfunk- und Drahtlosnetzwerke & Anwendungen
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Drahtlostechnologie

Inhaltsverzeichnis

PoMeS: Profit-Maximizing Sensor Selection for Crowd-Sensed Spectrum Discovery.- Tenant-Aware Slice Admission Control using Neural Networks-Based Policy Agent Main Track.- Novel Filter Bank Based Cooperative Spectrum Sensing under RF Impairments and Channel Fading Beyond 5G Cognitive Radios.- Performance Evaluation of Windowing Based Energy Detector in Multipath and Multi-Signal Scenarios.- Transmitter Classification With Supervised Deep Learning.- Preferential Radar Method for Dynamic Assignment of Wi-Fi Channels.- Tactical radio operator’s combat readiness as context information for dynamic spectrum management within military mobile ad hoc networks.- Dynamic Placement Algorithm for MultipleClasses of Mobile Base Stations in Public SafetyNetworks.- Spectrum analysis using semantic models for context.- Margin-based Active Online Learning Techniques for Cooperative Spectrum Sharing in CR Networks.- On the Feasibility of a Secondary Service Transmission Over an Existent Satellite Infrastructure.- Cooperative Delay-Constrained Cognitive Radio Networks: Throughput Maximization With Full-Duplex Capability Impact.- Radio Environment Maps for Military Cognitive Networks: Density of Sensor Network vs. Map Quality.- An Out-of-Sample Extension for Wireless Multipoint Channel Charting.- Machine Learning based RATs Selection supporting Multi-Connectivity for Reliability.- Spectrum-agile Cognitive Interference Avoidance through Deep Reinforcement Learning.- Localization techniques for 5G Radio Environment Maps.- A Hybrid Chain based Incentive Mechanism for Resource Leasing in NDN.- Reinforcement Learning-based Radio Access Network Slicing for a 5G System with Support for Cellular V2X.- Assessment of Spectrum Management Approaches to Private Industrial Networks.- Unlocking the Potential of QoS-Aware Pricing under the Licensed Shared Access Regime.- Location dependent spectrum valuation of private LTE and 5G networks in Europe.- Spectrum allocation options for point-to-multipoint services in 5G.- Wireless Network Virtualization with Long-Term Device-to-Device Communication.- Assessing the Feasibility of the Citizens Broadband Radio Service Concept for the Private Industrial Internet of Things Networks.- Wrkshop on Open Radio Platforms for 5G Research and Beyond.- Enhanced Resource Management for Web Based Thin Clients Using Cross-Platform Progressive Offline Capabilities.- Stabilized Distributed Layered Grant-Free NOMA for mMTC.- 5G CrowdCell with mm-Wave SDR Based Backhaul.- Performance Analysis of Full Duplex Wireless Multi-Hop Networks.