COGNITIVE RADIO SYSTEM FOR DYNAMIC ALLOCATION OF UHF BAND CHANNELS BASED ON 802.11AF AND USING THE ENERGY DETECTION ALGORITHM
Main Article Content
Abstract
This paper describes the development of a cognitive radio system through a software-defined radio approach, using universal software radio peripheral (USRP) devices and digital television equipment for communication in the UHF band. The algorithm was developed in LabVIEW and is based on energy detection, where the average power of the video carrier of the tv signal is calculated and compared with the established threshold value. As a result of detection, free channels are determined and assigned for the transmission of an Secondary User (SU), which will synchronize with the receiver the same working frequency. For the evaluation of the performance tests, a DTT transmitter and receiver were used, which simulate a Primary User (PU), and when the system detects it, it releases the frequency in use of the SU and assigns another free frequency to it to guarantee continuity of trasmission service. Tests were carried out to determine the efficiency of the system, taking into account the response time of the system and its efficiency to allow coexistence of systems within the same spectrum. System response times were measured, being 1.07 s and 41.47 s the shortest and longest response time respectively, for frequency change in order to avoid interference with the PU. Using sampling techniques, the average system response time was 21.33 s, proving that the system is efficient in environments with high interference for services that are not sensitive to latency.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
References
AARONIA. HyperLOG 30180. [On line]. AARONIA AG, Germany. 2019. pp. 1 [Consultation: 2020-10-05]. Available in: https://aaronia-shop.com/productos/breitbandantennen-hyperlog30180
AFONSO, Carlos. Usage of spectrum in LatinAmerica: Case studies of Argentina, Brazil, Colombia, Ecuador, Perú y Venezuela. [On line]. 2011. [consultation: 2020-10-09]. Recover from: https://www.apc.org/sites/default/files/ca_sintesis_final-AF_0.pdf
AGENCIA DE REGULACIÓN Y CONTROL DE LAS TELECOMUNICACIONES. Sound broadcasting and open television. [On line]. 2020. [consulta: 2020-10-09]. Available in: http://www.arcotel.gob.ec/radiodifusion-sonora-y-television-abierta2/
AGUILAR RENTERÍA, J. & NAVARRO CADAVID, A. “Cognitive radio – State of the Art”. Sistemas y Telemática [On line], 2011, 9(16), pp. 31-53. ISSN 1692-5238. [Consultation: 2019-11-04]. Available in: https://www.icesi.edu.co/revistas/index.php/sistemas_telematica/article/view/1028/1053.
ÁLCOCER ERAZO, Jonathan David. Performance analysis of the IEEE 802.11AF standard in TVWS through implementation in a software-defined radio platform [On line]. (Undergrade) ESPE, Sangolquí, Ecuador. 2019. pp. 1-100. [Consulta: 2020-03-24]. Available in: http://repositorio.espe.edu.ec/bitstream/21000/15813/1/T-ESPE-040692.pdf.
ALOMOTO, Diego y MARTÍNEZ, Iñigo. Analysis and simulation of algorithms for spectrum detection in cognitive radio [On line]. (Undergrade) EPN, Quito, Ecuador. 2018. pp. 1-116. [Consultation: 2020-03-24]. Available in: https://bibdigital.epn.edu.ec/bitstream/15000/19078/1/CD-8479.pdf.
ARAUJO TORRES, Michelle Estefanía. Implementation of a cognitive radio system for the detection of TVWS frequency bands [On line]. (Undergrade) ESPE, Sangolquí, Ecuador. 2018. pp. 1-123. [Consultation: 2020-03-24]. Available in: http://repositorio.espe.edu.ec/xmlui/bitstream/handle/21000/14849/T-ESPE-040376.pdf?sequence=1&isAllowed=y.
ARTIEDA, Luis & CORONEL, María. Análisis Analysis of the implementation in Ecuador of systems based on the IEEE 802.22 standard, ESPOL, Guayaquil, Ecuador. 2014. pp. 1-133 [Consultation: 2020-03-24]. Available in: https://www.dspace.espol.edu.ec/retrieve/101992/D-84450.pdf.
AWIN, F.A., et al. “Technical Issues on Cognitive Radio-Based Internet of Things Systems: A Survey”. IEEE Access [On line], 2019, 7(1), pp. 97887-97908. [Consultation: 2019-12-01]. ISSN 21693536. Available in: https://ieeexplore.ieee.org/abstract/document/8766798.
BAIRD, D. “NASA Explores Artificial Intelligence for Space Communications”. Space Communications and Navigation [On line]. 2017, diciembre, 11. [Consultation: 2019-11-06]. ISSN 1090-7807 Available in: https://www.nasa.gov/feature/goddard/2017/nasa-explores-artificial-intelligence-for-space-communications
BARRIONUEVO, Evelin y TAMAYO, Viviana. Analysis of the performance of a network with WiFi technology for long distances in a rural environment of the Sierra region [On line]. ESPE, Sangolquí, Ecuador. 2011. pp. 1-174. [Consultation: 2020-02-14]. Available in: https://repositorio.espe.edu.ec/bitstream/21000/2934/1/T-ESPE-030883.pdf.
BELTRAN, Lianne. Simulation design and analysis of Wi-Fi networks that operate in television white spaces using cognitive radio. [On line]. Madrid Polytechnique, Madrid, España. 2016. pp. 55-65. [Consultation: 2020-02-11]. Available in: http://oa.upm.es/43260/1/PFC_LIANNE_LAMORENA_BELTRAN_2016.pdf
BOLAÑOS, E. Sample and samplig. [On line]. Universidad Autónoma del Estado de Hidalgo, México. 2012. pp.2-8 [Consultation: 2020-11-07]. Available in: https://www.uaeh.edu.mx/docencia/P_Presentaciones/tizayuca/gestion_tecnologica/muestraMuestreo.pdf
CÁCERES TOVAR, Rodrigo Alberto. Techniques for detection and analysis of spectral occupancy in cognitive radio in the northwestern area of the city of Bogotá. Universidad Distrital Francisco José de Caldas, Bogotá, Colombia. 2017. pp. 1-80 [Consultation: 2020-02-14]. Available in: http://repository.udistrital.edu.co/handle/11349/5875.
CASTAÑEDA, Paulo & GUERRERO, Carla. Television White Space. 2015. pp. 1-5. [Consultation: 2020-02-14]. Available in: http://www.academia.edW26348239,"T
EKLUND, C. et al. IEEE standard 802.16: A technical overview of the Wireless MANTM air interface for broadband wireless access. IEEE Communications Magazine, 40(6), june 2012. DOI: 10.1109/MCOM.2002.1007415.
FEDERAL COMMUNICATIONS COMMISSION. “Facilitating opportunities for flexible, efficient, and reliable spectrum use employing cognitive radio technologies”. ET Docket No. 03-108. [On line], 2003, pp. 1-53. [Consultation: 2019-10-20]. Available in: https://www.fcc.gov/document/facilitating-opportunities-flexible-efficient-and-reliable-spectrum.
FLORES, A. et al. IEEE 802.11af: A standard for TV White Space Spectrum Sharing. [On line]. October 2013, IEEE Communications Magazine, 51(10), pp. 92-100, [Consultation: 2020-02-20]. Available in: https://www.researchgate.net/publication/260670622_IEEE_80211af_A_standard_for_TV_white_space_spectrum_sharing
GOMEZ, Santiago et al. COGNINET Cognitive Radios and Sensing of the Radioelectric Spectrum [On line]. Universidad de la República, Montevideo, Uruguay. 2014. pp. 1-143. [Consultation: 2020-02-14]. Available in: https://iie.fing.edu.uy/publicaciones/2014/GMS14/GMS.pdf.
GUAMO MOROCHO, Andrea Katherine. Implementation of a communications link based on principles of cognitive radio systems in the faculty of energy, industries and non-renewable natural resources of the National University of Loja through SDR (Software Defined Radio) [On line]. Universidad Nacional de Loja, Loja, Ecuador. 2019. pp. 1-109. [Consultation: 2020-02-13] Available in: https://dspace.unl.edu.ec/jspui/bitstream/123456789/22050/1/Guamo%20Morocho%2c%20Andrea%20Katherine.pdf
HAYKIN, S. “Cognitive Radio: Brain-Empowered”. IEEE Journal on Selected Areas in Communications [On line], 2005, 23(2), pp. 201-220. [Consultation: 2019-11-06]. Available in: https://ieeexplore.ieee.org/document/1391031/versions.
HERNÁNDEZ, Patricia. & CARRO, Gonzalo. Principles, standards and solutions of Cognitive Radio [On line]. Universidad de la República, Montevideo, Uruguay. 2016. pp. 1-39. [Consultation: 2020-02-02] Available in: https://iie.fing.edu.uy/proyectos/esopo/wp-content/uploads/sites/3/2017/01/Doc4_20170118_CognitiveRadio.pdf.
LEE, B.M., et al. “Implementation of a Regional Spectrum Sensing Based Cognitive Radio System for Digital TV White Space”. IETE Technical Review (Institution of Electronics and Telecommunication Engineers, India) [On line], 2018, 35(6), pp. 590-598. [Consultation: 2019-11-20]. ISSN 09745971. Available in: https://www.tandfonline.com/doi/abs/10.1080/02564602.2017.1354731.
MÁRQUEZ RAMOS, R. “Cognitive radio architectures: a review”. Tecnura Magazine [On line], 2014, 18(39), pp. 181-196. [Consultation: 2019-11-16]. Available in: http://www.scielo.org.co/pdf/tecn/v18n39/v18n39a14.pdf.
MEJÍA CANDO, Julio César. Development of an algorithm in Matlab for optimizing the resolution of a USRP B210 card for SDRADAR applications. Escuela Superior Politécnica de Chimborazo, Riobamba, Ecuador. 2017. [Consultation: 2020-03-24]. Available in: http://dspace.espoch.edu.ec/bitstream/123456789/7523/1/98T00160.pdf
JIMÉNEZ MOPOSITA, Jorge Vinicio. Analysis and evaluation of the radio spectrum in the VHF and UHF bands through an algorithm carried out in USRP radio for potential use of the IEEE 802.11af standard in the urban area of Ambato canton [On line. Escuela Superior Politécnica de Chimborazo ESPOCH, Riobamba, Ecuador. 2017. pp. 36-69. [Consultation: 2020-11-13]. Available in: http://dspace.espoch.edu.ec/handle/123456789/7406
NATIONAL INSTRUMENTS. Radio Definido por Software USRP - National Instruments [On line]. 2017 [Consulta: 12 febrero 2020]. Available in: http://www.ni.com/es-cr/shop/select/usrp-software-defined-radiodevice?modelId=125052>.
NATIONAL INSTRUMENTS. Specifications USRP-2932 [On line]. 2017 [Consultation: 12 february 2020]. Available in: http://www.ni.com/pdf/manuals/375988d.pdf.
PEDRAZA, L. et al. “Spectrum detection for cognitive radio”. Chilean magazine ingeniería [On line], 2012, 20(2), pp. 197-210. [Consulta: 2019-11-01]. Available in: https://scielo.conicyt.cl/pdf/ingeniare/v20n2/art07.pdf.
PONCE PINOS, Jaqueline Elizabeth. Evaluation of the occupation of the radio spectrum and feasibility analysis of the use of cognitive radio in the UHF band (450 – 512 MHZ) for its optimization in the city of Riobamba. (Postgrade) Escuela Superior Politécnica de Chimborazo, Riobamba, Ecuador. 2019. pp. 1-70. [Consultation: 2019-10-17]. Available in: http://dspace.espoch.edu.ec/bitstream/123456789/9439/1/20T01133.pdf
RUÍZ, L. Spectral Sensing in Cognitive Radio. [On line]. Universidad de Paderborn, Paderborn. 2015. [Consultation: 2020-07-30]. Available in: https://e-archivo.uc3m.es/bitstream/handle/10016/26659/PFC_Lucia_Ruiz_Ruiz_Resumen_Espanol.pdf.
SERRANO FLORES, María Eugenia. Application of resolution optimization algorithm for the detection of moving targets with SDRADAR technology [On line]. Escuela Superior Politécnica De Chimborazo, Riobamba, Chimborazo. 2019. [Consultation: 2020-02-12]. Available in: http://dspace.espoch.edu.ec/bitstream/123456789/11017/1/98T00240.pdf
SODAGARI, S., et al. “Technologies and Challenges for Cognitive Radio Enabled Medical Wireless Body Area Networks”. IEEE Access [On line], 2018, 6(1), pp. 29567-29586. [Consultation: 2019-11-24]. ISSN 21693536. Available in: https://ieeexplore.ieee.org/abstract/document/8370629.
SOLETO, R., et al. ISDB-T Transmission System. Trabajos de difusión científica. [On line]. 2011. pp. 70-71. [Consultation: 20 septiembre 2020]. Available in: https://www.researchgate.net/publication/277269466_Sistema_de_transmision_ISDB-T
TSCHIMBEN, S., et al. “IEEE 802.11ah SDR Implementation and Range Evaluation”. IEEE Wireless Communications and Networking Conference, WCNC [On line], 2019, vol. 2019-April, pp. 1-6. [Consultation: 2019-11-06]. ISSN 15253511. Available in: https://ieeexplore.ieee.org/document/8885445/metrics.
TUTTLEBEE, W. “Software defined radio: enabling technologies”. Published online: John Wiley & Sons, Inc. 2003. pp. 397. [Consultation: 2019-11-06]. Available in: http://onlinelibrary.wiley.com/book/10.1002/0470846003
VANERIO, Juan Martín. Expert-Based Online Prediction for Cognitive Radio Secondary Markets [On line]. Universidad de la República, Montevideo, Uruguay. 2017. pp. 1-160. [Consultation: 2020-02-14]. Available in: https://iie.fing.edu.uy/publicaciones/2017/Van17/Van17.pdf.
WANG, D., et al. “Intelligent Cognitive Radio in 5G: AI-Based Hierarchical Cognitive Cellular Networks”. IEEE Wireless Communications [On line], 2019, 26(3), pp. 54-61. [Consultation: 2019-11-06]. ISSN 15580687. Available in: https://www.researchgate.net/publication/334155919_Intelligent_Cognitive_Radio_in_5G_AI-Based_Hierarchical_Cognitive_Cellular_Networks.
WIRELESS INNOVATION FORUM. What is Software Defined Radio [On line]. 2008. [consultation: 2020-01-20]. Available in: https://www.wirelessinnovation.org/assets/documents/SoftwareDefinedRadio.pdf