Cognitive Radio Oriented Wireless Networks (eBook, PDF)

13th EAI International Conference, CROWNCOM 2018, Ghent, Belgium, September 18-20, 2018, Proceedings
Redaktion: Moerman, Ingrid; Jiao, Xianjun; Giannoulis, Spilios; Liu, Wei; Shahid, Adnan; Marquez-Barja, Johann

• Format: PDF

Produktbeschreibung

This book constitutes the refereed proceedings of the 13^th EAI International Conference on Cognitive Radio Oriented Wireless Networks, CROWNCOM 2018, held in Ghent, Belgium, in September 2018. The 20 revised full papers were selected from 26 submissions. The papers are organized thematically in tracks: Experimental, Licensed Shared Access and Dynamic Spectrum Access, and PHX and Sensing.

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Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 223
• Erscheinungstermin: 8. Januar 2019
• Englisch
• ISBN-13: 9783030054908
• Artikelnr.: 54894407

Inhaltsangabe

Experimental analysis of 5 GHz WiFi and UHF-TVWS hybrid Wireless Mesh Network back-haul links.- High-level and Compact Design of Cross-channel LTE DownLink Channel Encoder.- Detection of Different Wireless Protocols on an FPGA with the Same Analog/RF Front End.- Demonstration of Shared Spectrum Access of Different User Groups.- A Low-Latency Wireless Network for Cloud-Based Robot Control.- Comparison of incumbent user privacy preserving technologies in database driven dynamic spectrum access systems.- Spectrum Leasing for Micro-Operators Using Blockchain Networks.- SZ-SAS: A Framework for Preserving Incumbent User.- Privacy in SAS-based DSA Systems.- Secrecy Outage Probability of Cognitive Small-Cell Network with Unreliable Backhaul Connections.- Polarization-Space Based Interference Alignment for Cognitive Heterogeneous Cellular Network.- The vision of 5G and the need for change in mobile spectrum access.- Coexistence of LTE Networks Under LSA Paradigm in 2.6 GHz.- Pricing Private LTE and 5G Radio Licenses on 3.5 GHz.- LSA System Development with Sensing for Rapidly Deployable LTE Network.- Maxmin Strategy for a Dual Radar and Communication.- OFDM Waveforms System facing Uncertainty about the Background Noise.- Using Deep Learning and Radio Virtualisation for Efficient Spectrum Sharing among Coexisting Networks.- PHY and Sensing.- Evaluating Deep Neural Networks to classify Modulated and Coded Radio Signals.- Improving Spectrum Efficiency in Heterogeneous Networks using Granular Identification.- Interference Rejection Combining for Black-Space Cognitive Radio Communications.- An Image Processing Approach to Wideband Spectrum Sensing of Heterogeneous Signals.