DOCSLIB.ORG

Detection of Vacant Frequency Bands in Cognitive Radio

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Detection of Vacant Frequency Bands in Cognitive Radio MEE10:58 DETECTION OF VACANT FREQUENCY BANDS IN COGNITIVE RADIO Rehan Ahmed Yasir Arfat Ghous This thesis is presented as part of Degree of Master of Science in Electrical Engineering Blekinge Institute of Technology May 2010 Blekinge Institute of Technology School of Engineering Supervisor: (Doktorand) Maria Erman Examiner: Universitetslektor Jörgen Nordberg ii ABSTRACT Cognitive radio is an exciting promising technology which not only has the potential of dealing with the inflexible prerequisites but also the scarcity of the radio spectrum usage. Such an innovative and transforming technology presents an exemplar change in the design of wireless communication systems, as it allows the efficient utilization of the radio spectrum by transforming the capability to dispersed terminals or radio cells of radio sensing, active spectrum sharing and self-adaptation procedure. Cooperative communications and networking is one more new communication skill prototype that permits the distributed terminals in a wireless network to cooperate with each other through some distributed transmission or signal processing in order to comprehend a new appearance of space diversity to contest the detrimental effects of fading channels. In this thesis, we regard the relevance of these technologies to spectrum sensing and spectrum sharing. One of the most vital challenges for cognitive radio systems is to diagnose the existence of primary (licensed) users over an extensive range of spectrum at a particular time and explicit geographic locality. We consider the utilization of cooperative spectrum sensing in cognitive radio systems to increase the consistency of detecting of primary users. We describe spectrum sensing for cognitive radios (CRs) and project a vigorous cooperative spectrum sensing procedure for a practical framework employing cognitive radios Cooperative sensing can formulate excellent use of network assets, attain higher gain and make the network smooth. In this thesis we give a concise introduction of the principle of cooperative sensing and discuss the cooperative sensing techniques in CRs. Simulation results confirm that cooperative sensing can get better detection probability, can advance the agility gain and as a result finally help with more efficient utilization of spectrum. iii iv ACKNOWLEDGEMENTS All thanks to Almighty ALLAH who is not only the creator and the owner of this universe, but also the most merciful, beneficent and the most gracious, who provided us guidance, strength and abilities to complete our thesis successfully. We are thankful to the Faculty Staff of the school of engineering of the BTH; they were a light of guidance for us in our whole study period at BTH, particularly in building our base in education, enhancing our knowledge and sharpening our practical skills. We are especially thankful to Ms. Maria Erman, our thesis supervisor, for her help, guidance and support in completion of our project. Our everlasting gratitude and acknowledgements are for our parents for their moral support and encouragement throughout ourr study period at BTH. v vi TABLE OF CONTENTS List of Acronyms ........................................................................................................................................... x List of Figures ............................................................................................................................................xiii List of Tables .............................................................................................................................................. xiv 1. Introduction ................................................................................................................... 1 1.2 Background & Thesis motivation.................................................................................................... 2 1.3 Problem statement ........................................................................................................................... 3 1.4 Thesis Outline ................................................................................................................................. 3 2. Literature Review ................................................................................................................. 4 2.1 Introduction ...................................................................................................................................... 4 2.2 Cognitive Radio ................................................................................................................................ 4 2.2.1 Motivation and Requirements : .................................................................................................... 5 2.2.2 The Cognitive Radio operation ................................................................................................ 5 2.3 Software Defined Radio ................................................................................................................... 6 2.3.1 SDR and its Relationship with Cognitive radio .......................................................................... 6 2.4 The Cognitive Radio Network Architecture .................................................................................... 7 2.4.1 Primary network .......................................................................................................................... 7 2.4.2 Cognitive radio network .............................................................................................................. 8 2.5 Spectrum Sensing ............................................................................................................................. 9 2.5.1 Methods ..................................................................................................................................... 10 2.5.2 Challenges ................................................................................................................................. 10 2.6 Spectrum Management ................................................................................................................... 10 2.6.1 Spectrum analysis ...................................................................................................................... 10 2.6.2 Spectrum decision ..................................................................................................................... 11 2.6.3 Spectrum management challenges ............................................................................................ 11 2.7 Spectrum mobility .......................................................................................................................... 12 2.7.1 Spectrum Hando ff ...................................................................................................................... 12 2.7.2 Spectrum mobility challenges .................................................................................................... 13 2.8 Spectrum Sharing ........................................................................................................................... 14 2.8.1 Classification of spectrum sharing ................................................................................................ 14 vii 2.8.2 Spectrum sharing challenges.......................................................................................................15 2.9 OFDM Based Cognitive Radio..........................................................................................................16 3. SPECTRUM SENSING TECHNIQUES .............................................................................. 18 3.1 Introduction .................................................................................................................................... 18 3.2 Spectrum Sensing ........................................................................................................................... 18 3.3 Multi-Dimensional Spectrum Sensing ........................................................................................... 19 3.4 Challenges ...................................................................................................................................... 21 3.4.1 Hardware Requirements ............................................................................................................ 22 3.4.2 Hidden Primary User Problem .................................................................................................. 22 3.4.3 Detecting Spread Spectrum Primary Users ............................................................................... 23 3.4.4 Sensing Duration and Frequency .............................................................................................. 24 3.4.5 Decision Fusion in Cooperative Sensing ................................................................................... 25 3.4.6 Security...................................................................................................................................... 25 3.5 Spectrum Sensing Methods for Cognitive Radio ........................................................................... 26 3.5.1 Energy Detection ........................................................................................................................ 26 3.5.2 Matched Filter ........................................................................................................................... 27 3.5.3 Cyclostationary Detection ........................................................................................................
Load more

Recommended publications
  • Study of Tv White Spaces in the Context of Cognitive Radio for The
    ISSN: 0798-1015 DOI: 10.48082/espacios-a20v41n50p12 Vol. 41 (50) 2020 • Art. 12 Recibido/Received: 23/09/2020 • Aprobado/Approved: 18/11/2020 • Publicado/Published: 30/12/2020 Study of TV white spaces in the context of cognitive radio for the deployment of WiFi in rural zones of the colombian army Estudio de espacios en blanco de TV en el contexto de radio cognitiva para el despliegue de WiFi en zonas rurales del ejército colombiano AVENDAÑO, Eduardo 1 ESPINDOLA, Jorge E.2 MONTAÑEZ, Oscar J.3 Abstract This article presents a study on Television White Spaces (TVWS) to solve the connectivity of the WiFi service for the Colombian National Army in rural areas. The study analyzes regulatory aspects and technical equipment to provide a free internet access solution. Video transmission was experimentally validated, using OFDM with USRP N210 radios. With this preliminary analysis, it was possible to understand how the PHY and MAC layers of the 802.22 Standard work to select the appropriate devices. key words: tvws, usrp, cognitive radio, software-defined radio (sdr) Resumen Este artículo presenta un estudio sobre Espacios Blancos de Televisión para solucionar la conectividad del servicio WiFi para el Ejército Nacional de Colombia en zonas rurales. El estudio analiza aspectos regulatorios y el equipamiento técnico para brindar solución de acceso gratuito a internet. Se validó experimentalmente la transmisión de video, usando OFDM con radios USRP N210. Con este análisis preliminar, fue posible comprender cómo funcionan las capas PHY y MAC del Estándar 802.22 para seleccionar los dispositivos adecuados. Palabras clave: tvws, usrp, radio cognitiva, radio definida por software (sdr) 1.
    [Show full text]
  • Cognitive Frequency Hopping Based on Interference Prediction: Theory and Experimental Results ∗
    Cognitive Frequency Hopping Based on Interference Prediction: Theory and Experimental Results ∗ Stefan Geirhofera John Z. Sunb Lang Tonga Brian M. Sadlerc [email protected] [email protected] [email protected] [email protected] aSchool of Electrical and Computer Engineering, Cornell University, Ithaca, NY 14853 bResearch Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA 02139 cU.S. Army Research Laboratory, Adelphi, MD 20783 Wireless services in the unlicensed bands are proliferating but frequently face high interfer- ence from other devices due to a lack of coordination among heterogeneous technologies. In this paper we study how cognitive radio concepts enable systems to sense and predict interference patterns and adapt their spectrum access accordingly. This leads to a new cognitive coexistence paradigm, in which cognitive radio implicitly coordinates the spec- trum access of heterogeneous systems. Within this framework, we investigate coexistence with a set of parallel WLAN bands: based on predicting WLAN activity, the cognitive radio dynamically hops between the bands to avoid collisions and reduce interference. The de- velopment of a real-time test bed is presented, and used to corroborate theoretical results and model assumptions. Numerical results show a good fit between theory and experiment and demonstrate that sensing and prediction can mitigate interference effectively. I. Introduction direct information exchange among interfering sys- tems. Instead we study how a cognitive radio may Wireless devices and services are growing rapidly and reduce collisions by predicting the WLAN’s activ- are becoming ubiquitous. The unlicensed bands have ity and adapting its medium access accordingly. The played a fundamental role in this trend as illustrated cognitive concept of sensing and adaptation conse- by the rapid proliferation of WiFi and Bluetooth de- quently serves as an implicit means for coordinating vices.
    [Show full text]
  • IEEE 802.22 Wireless Regional Area Networks
    Universal Journal of Communications and Network 1(1): 27-31, 2013 http://www.hrpub.org DOI: 10.13189/ujcn.2013.010105 A Survey on Rural Broadband Wireless Access Using Cognitive Radio Technology: IEEE 802.22 Wireless Regional Area Networks M.Ravi Kumar*, S.Manoj Kumar, M.balajee Dept. of IT (MCA), G M R Institute of Technology Rajam, Andhra Pradesh, India *Corresponding Author: [email protected] Copyright © 2013 Horizon Research Publishing All rights reserved. Abstract The previous and most popular broadband (6MHz, 7MHz, or 8MHz) to address, as a primary objective, wireless technology i.e. WiMAX which is limited about to rural and remote areas and low population density 10 miles, there are power and line of sight issues yet to be underserved markets with performance levels similar to resolved for a broader coverage area. WiMAX deployment is those of Broadband access technologies such as digital therefore limited to densely populate metropolitan areas. subscriber line (xDSL) technologies and Digital Cable What about rural and sparsely populated, geographically modem service. A secondary objective is to have this system dispersed regional areas? Here is the upcoming solution for scale to serve denser population areas where spectrum is that which is implemented by IEEE .The IEEE 802.22 available. The WRAN system must be capable of supporting standard defines a system for a Wireless Regional Area a mix of data, voice and audio/video applications. These Network i.e. WRAN that uses unused or white spaces within include Internet access, VoIP, video teleconferencing and the television bands between 54 and 862 MHz, especially streaming video.
    [Show full text]
  • Spectrum Occupancy Measurements and Analysis in 2.4 Ghz WLAN
    electronics Article Spectrum Occupancy Measurements and Analysis in 2.4 GHz WLAN Adnan Ahmad Cheema 1 and Sana Salous 2,* 1 School of Engineering, Ulster University, Jordanstown BT37 0QB, UK 2 Department of Engineering, Durham University, Durham DH1 3LE, UK * Correspondence: [email protected]; Tel.: +0044-191-33-42532 Received: 26 July 2019; Accepted: 7 September 2019; Published: 10 September 2019 Abstract: High time resolution spectrum occupancy measurements and analysis are presented for 2.4 GHz WLAN signals. A custom-designed wideband sensing engine records the received power of signals, and its performance is presented to select the decision threshold required to define the channel state (busy/idle). Two sets of measurements are presented where data were collected using an omni-directional and directional antenna in an indoor environment. Statistics of the idle time windows in the 2.4 GHz WLAN are analyzed using a wider set of distributions, which require fewer parameters to compute and are more practical for implementation compared to the widely-used phase type or Gaussian mixture distributions. For the omni-directional antenna, it was found that the lognormal and gamma distributions can be used to model the behavior of the idle time windows under different network traffic loads. In addition, the measurements show that the low time resolution and angle of arrival affect the statistics of the idle time windows. Keywords: cognitive radio; spectrum occupancy; dynamic spectrum access; time resolution; directional; sensing engine 1. Introduction The vision of 5G network (5GN) encapsulates many application areas, e.g. mobile broadband, connected health, intelligent transportation, and industry automation [1].
    [Show full text]
  • OFDM Based Transceiver for a Cognitive Radio
    Published by : International Journal of Engineering Research & Technology (IJERT) http://www.ijert.org ISSN: 2278-0181 Vol. 5 Issue 07, July-2016 OFDM based Transceiver for a Cognitive Radio Mundlamuri Kowshik, Electronics and Communication Engineering Shiv Nadar University Greater Noida, Uttar Pradesh, India Abstract: Cognitive radio is the heir of next generation accurate identification of empty spectrum ask for efficient wireless communication. This will be the next big leap in the spectrum sensing algorithms etc. This attracts a large process of making wireless communication efficient. In this number of research activities across the world. paper, we present the implementation and benefits of Orthogonal frequency division multiplexing (OFDM) orthogonal frequency division multiplexing commonly known is the technique proposed in this paper to be used in the as OFDM in the transceiver (transmitter and receiver) of a transceiver of a cognitive radio. OFDM is a digital multi- cognitive radio. The transmitter part of the OFDM transceiver is implemented as a model in LabVIEW and carrier modulation technique. OFDM is widely is used dumped in a NI based FPGA. This papers aims to show how across various fields in wireless transmission. The OFDM falls in place with the other components of a typical flexibility and features offered by OFDM makes it so cognitive radio also the challenges faced while adopting popular in the field of wireless communication. The OFDM. transceiver which is studied in this paper employs OFDM and we shall see the features and challenges it offers in the Keywords: Cognitive radio, OFDM. upcoming sections of this paper. The main goal of this paper is to integrate OFDM A.
    [Show full text]
  • Cognitive Radio for Coexistence of Heterogeneous Wireless Networks Stefano Boldrini
    Cognitive radio for coexistence of heterogeneous wireless networks Stefano Boldrini To cite this version: Stefano Boldrini. Cognitive radio for coexistence of heterogeneous wireless networks. Other. Supélec; Università degli studi La Sapienza (Rome), 2014. English. NNT : 2014SUPL0012. tel-01080508 HAL Id: tel-01080508 https://tel.archives-ouvertes.fr/tel-01080508 Submitted on 5 Nov 2014 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. ! N°!d’ordre:!2014.12.TH! ! ! SUPELEC' ' ECOLE'DOCTORALE'STITS' «"Sciences"et"Technologies"de"l’Information"des"Télécommunications"et"des"Systèmes"»" ' ' ' THÈSE'DE'DOCTORAT' ' DOMAINE:'STIC' Spécialité:'Télécommunications' ' ' ' Soutenue'le'10'avril'2014' ' par:' ' SteFano'BOLDRINI' ' ' Radio'cognitive'pour'la'coexistence'de'réseaux'radio'hétérogènes' (Cognitive!radio!for!coexistence!of!heterogeneous!wireless!networks)! ' ' ' ' ' ' Directeur'de'thèse:! Maria.Gabriella!DI!BENEDETTO! Professeur,!Sapienza!Université!de!Rome! CoMdirecteur'de'thèse:! Jocelyn!FIORINA! Professeur,!Supélec! ! Composition'du'jury:' ! Président"du"jury:!
    [Show full text]
  • Cognitive Radio Networks for Internet of Things and Wireless Sensor Networks
    sensors Article Cognitive Radio Networks for Internet of Things and Wireless Sensor Networks Heejung Yu 1 and Yousaf Bin Zikria 2,* 1 Department of Electronics and Information Engineering, Korea University, Sejong 30019, Korea; [email protected] 2 Department of Information and Communication Engineering, Yeungnam University, 280 Daehak-Ro, Gyeongsangbuk-do, Gyeongsan-si 38541, Korea * Correspondence: [email protected]; Tel.: +82-53-810-3098 Received: 12 September 2020; Accepted: 15 September 2020; Published: 16 September 2020 Abstract: Recent innovation, growth, and deployment of internet of things (IoT) networks are changing the daily life of people. 5G networks are widely deployed around the world, and they are important for continuous growth of IoT. The next generation cellular networks and wireless sensor networks (WSN) make the road to the target of the next generation IoT networks. The challenges of the next generation IoT networks remain in reducing the overall network latency and increasing throughput without sacrificing reliability. One feasible alternative is coexistence of networks operating on different frequencies. However, data bandwidth support and spectrum availability are the major challenges. Therefore, cognitive radio networks (CRN) are the best available technology to cater to all these challenges for the co-existence of IoT, WSN, 5G, and beyond-5G networks. Keywords: CRN; IoT; WSN; 5G; spectrum sensing; spectrum sharing 1. Introduction The numerous Internet of Things (IoT) technologies have contributed to explosive increase in the number of Internet-connected devices. The exponential growth of these smart connected devices is driving the revolution in social life of people. Move-forward in such a direction is the fifth-generation (5G) and beyond-5G connectivity.
    [Show full text]
  • Intelligent and Efficient Development of Wireless Networks: a Review of Cognitive Radio Networks
    Review SPECIAL TOPIC October 2012 Vol.57 No.28-29: 36623676 Basic Theories in Cognitive Wireless Networks doi: 10.1007/s11434-012-5334-5 SPECIAL TOPICS: Intelligent and efficient development of wireless networks: A review of cognitive radio networks ZHANG Ping*, LIU Yang, FENG ZhiYong, ZHANG QiXun, LI Qian & XU Ding Wireless Technology Innovation Institute (WTI), Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China Received November 10, 2011; accepted May 10, 2012 Facing the challenges on how to improve spectrum efficiency and how to realize heterogeneous network convergence in future wireless networks, a cognitive radio network (CRN) is proposed as one of the solutions. This has become a major research topic in recent years and it is timely to give an overview of the development of CRN and to summarize key issues and technologies. The fundamental concepts of CRN, including the cognitive cycle model, the network architecture, and the cognitive ability and intelligent decision functions, are introduced in detail based on recent advances. Key issues for each topic, followed with recent research on theory and method, are then classified and the industrialization developments of CRN testbeds based on TD-LTE cellular system and standards are briefly presented. Finally, conclusions are reached on the perspectives and directions of future development. cognitive radio networks, network architecture, cognitive ability, spectrum sensing, intelligent decision and dynamic spec- trum allocation, end-to-end performance Citation: Zhang P, Liu Y, Feng Z Y, et al. Intelligent and efficient development of wireless networks: A review of cognitive radio networks.
    [Show full text]
  • TR 102 802 V1.1.1 (2010-02) Technical Report
    ETSI TR 102 802 V1.1.1 (2010-02) Technical Report Reconfigurable Radio Systems (RRS); Cognitive Radio System Concept 2 ETSI TR 102 802 V1.1.1 (2010-02) Reference DTR/RRS-01002 Keywords architecture, network, radio ETSI 650 Route des Lucioles F-06921 Sophia Antipolis Cedex - FRANCE Tel.: +33 4 92 94 42 00 Fax: +33 4 93 65 47 16 Siret N° 348 623 562 00017 - NAF 742 C Association à but non lucratif enregistrée à la Sous-Préfecture de Grasse (06) N° 7803/88 Important notice Individual copies of the present document can be downloaded from: http://www.etsi.org The present document may be made available in more than one electronic version or in print. In any case of existing or perceived difference in contents between such versions, the reference version is the Portable Document Format (PDF). In case of dispute, the reference shall be the printing on ETSI printers of the PDF version kept on a specific network drive within ETSI Secretariat. Users of the present document should be aware that the document may be subject to revision or change of status. Information on the current status of this and other ETSI documents is available at http://portal.etsi.org/tb/status/status.asp If you find errors in the present document, please send your comment to one of the following services: http://portal.etsi.org/chaircor/ETSI_support.asp Copyright Notification No part may be reproduced except as authorized by written permission. The copyright and the foregoing restriction extend to reproduction in all media. © European Telecommunications Standards Institute 2010.
    [Show full text]
  • SDR and Cognitive Radio for Military Applications
    UNCLASSIFIED/UNLIMITED SDR and Cognitive Radio for Military Applications Tricia J. Willink Communications Research Centre 3701 Carling Ave., Box 11490, Station H Ottawa, ON, K2H 8S2 CANADA email:[email protected] ABSTRACT The development of software-defined radios (SDRs) should provide a small, light and cost-efficient platform capable of supporting multiple waveforms over a large frequency range. While there are challenges in achieving the vision of rapidly portable waveforms, the SDR is a critical technology for future military communications, and is an enabling platform for cognitive radio. Cognitive radio is proposed as a technology for exploiting the EM spectrum more effectively. While the main frequency bands of interest are fully licenced to authorised users, they are often unoccupied over large geographic areas or for significant time intervals. Cognitive radios are envisioned as aware, adaptable and intelligent devices, capable of learning and operating autonomously in a wide range of scenarios. The key feature of cognitive radios is the capability to identify unused frequency bands, to jump to them and select appropriate radio parameters. These radios must be able to operate without causing unacceptable interference to authorised users of the frequency band, therefore they must monitor for the presence of the primary user, and take into account the possible location of receivers of its signals. INTRODUCTION The adoption of the network-centric warfare (NCW), or net-enabled operations (NEOps), philosophy by western and allied nations requires a similarly revolutionary approach to communications technology. The basis of NEOps is the sharing of information among front-line forces, decision makers, sensors, weapons, etc.
    [Show full text]
  • Wireless Spectral Interference
    Trends in the Wireless Industry Dennis A. Roberson WiNCom - Wireless Network & Communications Research Center Illinois Institute of Technology Illinois Institute of Technology 1 Fundamental Challenge Spectrum Scarcity! Illinois Institute of Technology 2 Illinois Institute of Technology 3 Conundrum! Most of the Spectrum… Illinois Institute of Technology 4 Conundrum! Most of the Spectrum… In most of the Places… Illinois Institute of Technology 5 Conundrum! Most of the Spectrum… In most of the Places… Most of the Time… Illinois Institute of Technology 6 Conundrum! Most of the Spectrum… In most of the Places… Most of the Time… is completely unused! Illinois Institute of Technology 7 Conundrum! Most of the Spectrum… In most of the Places… Most of the Time… is completely unused! For your purposes, So far, so good! Illinois Institute of Technology 8 New York City (August 2004 - during Republican Convention) Illinois Institute of Technology 9 High Utilization (Public Safety Band) High Bandwidth, Spread SpectrumHigh Bandwidth, Signal Spread High Bandwidth,Spectrum SpreadSignal Spectrum Signal 17% Duty Cycle 17% Duty17% Duty Cycle Cycle Upper Bound (Frequency Resolution 65 MHz/501=130Upper Bound kHz/bin) (Frequency Resolution 65 50% Duty Cycle is too High, 19% Utilization Measured Using Small UpperMHz/501=130 Bound (Frequency kHz/bin) Resolution 65 Frequency Bins (450-455 MHz) MHz/501=130 kHz/bin) Courtesy of Mark McHenrry, Shared Spectrum Illinois Institute of Technology 10 Measured Spectrum Occupancy At Seven Locations Riverbend Park, Great Falls,
    [Show full text]
  • Service Discovery and Device Identification in Cognitive Radio
    1 Service Discovery and Device Identification in Cognitive Radio Networks Rob Miller, Wenyuan Xu, Pandurang Kamat, Wade Trappe Wireless Information Network Laboratory (WINLAB), Rutgers University. Email: f wenyuan, pkamat, trappe [email protected] Abstract— Cognitive Radios (CR) will be able to commu- incompatible. Such communication can aid in interfer- nicate adaptively in an effort to optimize spectral efficiency. ence avoidance and therefore result in more efficient An integral step towards this goal involves obtaining a spectral collaboration. Cognitive radios (CR) achieve this representative view of the various services operating in level of cross-protocol communication since they expose a local area. Although it is possible to load different the lower-layers of the protocol stack to researchers and software modules to identify each potential service, such an approach is needlessly inefficient. Instead, rather than use developers. a collection of complete protocols on a CR, we believe that Because cognitive radios support dynamic physical it is essential to have a separate identification module that layer adaptation, future wireless networks will consist of is capable of reliably identifying services and devices while various wireless devices communicating with each other minimizing the code needed. In particular, by effectively using one or more protocols. Figure 1 shows a future leveraging protocol-specific properties, we show that it is wireless network where WiFi and Bluetooth devices are possible to utilize data from narrowband spectral sampling in order to identify broader band services and individual operating amongst cognitive radios. In this scenario, devices. We demonstrate the feasibility of such service and WiFi device W can communicate with CR C and CR device identification using GNU Radio and the Universal D via 802.11.
    [Show full text]