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Application of MVDR and MUSIC spectrum sensing techniques with implementation of node's prototype for cognitive radio AD hoc networks

Published: 21 July 2017 Publication History

Abstract

In this paper, radio spectrum management is discussed in a multi-hop distributed network architecture scenario, dedicated for Internet of Things (IoT) applications, that aims to transform everyday objects to smart objects. In this sense, important features of Cognitive Radio Ad Hoc Networks (CRAHNs) are presented. The main interest is given to spectrum sensing functionality. Thus, the Multiple Signal Classification (MUSIC) technique and the Minimum Variance Distortionless Response (MVDR) technique are implemented. Obtained result exhibits good performance and high accuracy in Bluetooth spectrum signals detection using MUSIC technique. To reduce the gap between the simulations and real implementation, we propose a low cost node prototype for CRAHNs experiment, which consists of a radio platform and a host cognitive engine. It is carried out using 'USRP (Universal Software Radio Peripheral) and GNU-Radio' Software Defined Radio (SDR) platform, implemented on a single board computer. It ensures the development of CR functions undertaken locally by the users seamlessly work in an end-to-end multi-hop scenario.

References

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D.G. Reina, S.L. Toral, F. Barrero, N. Bessis, E. Asimakopoulou, 2013. The Role of Ad Hoc Networks in the Internet of Things: A Case Scenario for Smart Environments. Internet of Things & Inter-cooperative Comput. Technol., SCI 460, pp. 89--113.
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S. El Barrak, A. Lyhyaoui, A. Puliafito, S. Serrano, 2017. Implementation of a low cost SDR-Based Spectrum sensing Prototype Using USRP and Rasbperry Pi Board. Proceedings of Engineering and Technology-PET. Vol.20 PP 54--58.
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I.F. Akyildiz, W-Y. Lee, K.R. Chowdhury, 2009. Spectrum management in cognitive radio ad hoc networks. IEEE Network. 23, 4 (2009), 6--12.
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I.F. Akyildiz, W-Y. Lee, K.R. Chowdhury, 2009. CRAHNs: Cognitive radio ad hoc networks. Ad Hoc Networks. 7, 5 (2009), 810--836
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R. O. Schmidt, 1983. New mathematical tools in direction finding and spectral analysis. Proc. SPIE 27th Ann. Symp., San Diego, California, Aug. 1983.
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  1. Application of MVDR and MUSIC spectrum sensing techniques with implementation of node's prototype for cognitive radio AD hoc networks

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        cover image ACM Other conferences
        ICSDE '17: Proceedings of the 2017 International Conference on Smart Digital Environment
        July 2017
        245 pages
        ISBN:9781450352819
        DOI:10.1145/3128128
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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        Publication History

        Published: 21 July 2017

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        Author Tags

        1. GNU-radio
        2. IoT
        3. MUSIC
        4. MVDR
        5. USRPb200
        6. adhoc networks
        7. cognitive radio
        8. spectrum sensing

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        ICSDE '17 Paper Acceptance Rate 36 of 139 submissions, 26%;
        Overall Acceptance Rate 68 of 219 submissions, 31%

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        Cited By

        View all
        • (2025)Exploring In-Network Computing with Information-Centric Networking: Review and Research OpportunitiesFuture Internet10.3390/fi1701004217:1(42)Online publication date: 18-Jan-2025
        • (2024)Robust DNN-Enabled Cooperative Spectrum Sensing2024 International Conference on Software, Telecommunications and Computer Networks (SoftCOM)10.23919/SoftCOM62040.2024.10721894(1-6)Online publication date: 26-Sep-2024
        • (2024)Impact of Rain on Frequency Bands in 4G/5G Networks: Implications for Industrial Connectivity2024 IEEE 8th Forum on Research and Technologies for Society and Industry Innovation (RTSI)10.1109/RTSI61910.2024.10761384(500-505)Online publication date: 18-Sep-2024
        • (2023)1-D Convolutional Neural Network-Based Models for Cooperative Spectrum SensingFuture Internet10.3390/fi1601001416:1(14)Online publication date: 29-Dec-2023
        • (2023)A Petri Net Model for Cognitive Radio Internet of Things Networks Exploiting GSM BandsFuture Internet10.3390/fi1503011515:3(115)Online publication date: 21-Mar-2023
        • (2023)Real time implementation of SDR-based RF source detection and localization in restricted areaTelecommunication Systems10.1007/s11235-023-01055-984:3(399-408)Online publication date: 28-Sep-2023
        • (2020)Modified Multiple Signal Classification Algorithm for WSNs Localization2020 3rd International Conference on Engineering Technology and its Applications (IICETA)10.1109/IICETA50496.2020.9318808(56-61)Online publication date: 6-Sep-2020
        • (2018)GSM-RF Channel Characterization Using a Wideband Subspace Sensing Mechanism for Cognitive Radio NetworksWireless Communications & Mobile Computing10.1155/2018/70957632018Online publication date: 14-Nov-2018
        • (2017)SVM-MUSIC Algorithm for Spectrum Sensing in Cognitive Radio Ad-Hoc NetworksAd-hoc, Mobile, and Wireless Networks10.1007/978-3-319-67910-5_13(161-170)Online publication date: 14-Sep-2017

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