1 / 22

Kitsune : A Management System for Cognitive Radio Networks Based on Spectrum Sensing

Kitsune : A Management System for Cognitive Radio Networks Based on Spectrum Sensing. Lucas Bondan. Federal University of Rio Grande do Sul (UFRGS). IEEE/IFIP NOMS 2014 5 – 9 May, 2014 Krakow – Poland. Outline. Introduction Background Proposed solution Experimental evaluation

swain
Download Presentation

Kitsune : A Management System for Cognitive Radio Networks Based on Spectrum Sensing

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Kitsune: A Management System for Cognitive Radio Networks Based on Spectrum Sensing Lucas Bondan Federal University of Rio Grande do Sul (UFRGS) IEEE/IFIP NOMS 2014 5 – 9 May, 2014 Krakow – Poland

  2. Outline Introduction Background Proposed solution Experimental evaluation Final remarks

  3. Introduction • Crescent number of devices are using Radio Frequency (RF) spectrum for communication • However, this resource is limited • Command and Control (CaC) policy causes underutilization[FCC, 2002] • Only licensed users can transmit in licensed frequencies • Rise of Cognitive Radio (CR) concept [Mitola and Maguire, 1999] • Explored to improve the RF spectrum utilization • Cognitive capability • Reconfigurability

  4. Introduction (cont.) • Rise of CR networks • Designed to operate opportunistically • IEEE 802.22 Standard • Base Station (BS) provides Internet access to Customer-Premise Equipment (CPE) • Question: • How the management of these networks may be provided?

  5. Background CR Characteristics • Cognitive Capability • Cognitive Functions (CF)s: sensing, decision, sharing, and mobility • Spectrum sensing results used as input to the others • Reconfigurability • RF environment is dynamic in its nature • CR devices should be reconfigurable • Network administrator should know the RF environment

  6. Objective Design and develop a management system for CR networks • Enables the network administrator to know the radio environment • Configuration, monitoring,and visualization of spectrum sensing function should be provided by the management system • A continuous learning process for the network administrator • IEEE 802.22 Standard assumes a management system

  7. Proposed solution Kitsune • Hierarchical management system for CR networks • Considers CR networks characteristics, operating on the spectrum sensing function • Different networks can be managed using a hierarchical architecture • Management Information Base (MIB) based on IEEE 802.22 MIB • Information organization • Based on Resource Oriented Architecture (ROA) • Fast, simple, and robust

  8. Proposed solution Components Network Operations Control (NOC) CR Network Network Administrator CPE Agent CF MIB Management Station BS Backhaul Gateway Manager … … Visualization Configuration CPE Cache Agent Monitoring CF MIB

  9. Experimental evaluation Scenario

  10. Experimental evaluation 1 - Channels Occupancy • 5 CPEs using 5 channels (one channel per CPE) • Important to evaluate the radio environment • How the channels are used by CPEs

  11. Experimental evaluation 2 - Geolocation • Geolocation is an important factor in wireless networks • CPEs with low signal strength may be distant from the BS • 1 BS and 5 CPEs • Visualize the CR devices location and estimated coverage area

  12. Experimental evaluation 3 - Transmissions • 5 CPEs, each one transmitting in one channel • Important to analyze the number of transmissions performed by each CPE in each channel

  13. Experimental evaluation 4 - Uplink throughput • Complementary to the previous visualization • 5 CPEs, each one transmitting in one channel • Average throughput obtained in the transmissions • What channels present the highest/lowest throughput

  14. Experimental evaluation 5 - Configuration • Reconfiguration of the sensing period • Interval between spectrum sensing executions • Observe the average throughput obtained Sensing period Throughput Variation Channel [s] [Mbps] [%] 1 0.3182 1 42.04 2 0.5490 1 0.2267 2 51.84 2 0.4708 1 0.4016 3 18.42 2 0.4923 1 0.1803 4 42.54 2 0.3138 1 0.4027 5 17.25 2 0.4867

  15. Final remarks Conclusions • Main contribution: Hierarchical management system • Provides to the network administrator a way to analyze the network environment • Eases the analysis of the spectrum sensing results • A management system for CR networks should consider the spectrum sensing function • Visualizations may improve the network administrator knowledge • Configuration, monitoring, and visualization are part of a continuous process

  16. Final remarks Future Work • Extend Kitsune operation for different networks architectures • Concepts of management by delegation may be explored • Extend Kitsune operation to cover all cognitive functions • Turn Kitsuneable toanalyze the best algorithm for each cognitive function

  17. Thank you! Questions? Lucas Bondan Website: inf.ufrgs.br/~lbondan E-mail: lbondan@inf.ufrgs.br

  18. Bibliography [FCC, 2002] Federal Communications Comission Spectrum Policy Task Force, “Report of the Spectrum Efficiency Working Group”, FCC, 2002 [Mitola e Miguire, 1999] I. Mitola, J. and J. Maguire, G.Q., “Cognitive radio: making software radios more personal,” IEEE Personal Communications, vol. 6, pp. 13–18, 1999 [IEEE, 2011] IEEE, “IEEE Standard for Information Technology - Telecommunicationsandinformationexchangebetween systems Wireless Regional AreaNetworks (WRAN) - SpecificrequirementsPart 22: Cognitive Wireless RAN Medium Access Control (MAC) andPhysicalLayer (PHY) Specifications: Policies and Procedures for Operation in theTV Bands,” IEEE Std 802.22, pp. 1–680, 2011. [Akyildizet al., 2006] Akyildiz, I. F., Lee, W.-Y., Vuran, M. C., andMohanty, S. 2006. Next generation/dynamicspectrumaccess/cognitive radio wireless networks: A survey. Computer Networks 50, 13, 2127 – 2159. [Akyildiz; Lee; Chowdhury] Akyildiz, I. F.; Lee, W.-Y.; Chowdhury, K. R. CRAHNs: cognitive radio ad hoc networks. Ad Hoc Networks, Amsterdam, The Netherlands, v.7, n.5, p.810–836, July 2009. [CHEN et al., 2007] Chen, T.; Zhang, H.; Maggio, G. M.; Chlamtac, I. CogMesh: a cluster-based cognitive radio network. IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN), p.168–178, Apr. 2007.

  19. Bibliography (cont.) [PotierandQuian, 2011] P. Potierand L. Qian, “Network management ofcognitive radio ad hoc networks,” InternationalConferenceonCognitive Radio andAdvanced Spectrum Management, pp. 1–5, 2011. [Wang et al., 2008] C.-X. Wang, H.-H. Chen, X. Hong, and M. Guizani, “Cognitive radio network management,” IEEE Vehicular Technology Magazine, pp. 28–35, 2008. [Manfrin; Zanella; Zorzi]Manfrin, R.; Zanella, A.; Zorzi, M. CRABSS: calradio-basedadvancedspectrum scanner for cognitive networks. Wireless Communication & Mobile Computing, Chichester, UK, v.10, n.12, p.1682–1695, 2010. [Stavroulakiet al., 2012] V. Stavroulaki, A. Bantouna, Y. Kritikou, K. Tsagkaris, P. Demestichas, P. Blasco, F. Bader, M. Dohler, D. Denkovski, V. Atanasovski, L. Gavrilovska, and K. Moessner, “Knowledge Management Toolbox: Machine Learning for Cognitive Radio Networks,” IEEE Vehicular Technology Magazine, pp. 91–99, june2012 [Yucek e Arslan] T. Yucekand H. Arslan, “A surveyofspectrumsensingalgorithmsfor cognitiveradio applications,” IEEE Communications SurveysTutorials, vol. 11, pp. 116–130, 2009. [Bondan et al., 2013] Bondan, L.; Kist, M.; Kunst, R.; Both, C.; Rochol, J.; Granville, L.. ”Uma Solução para Gerenciamento de Dispositivos de Rádio Cognitivo Baseada na MIB IEEE 802.22”. Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos (SBRC), 2013, Brasília - Brazil

  20. Introduction (cont.) • Rise of CR networks • Designed to operate opportunistically • IEEE 802.22 Standard • Related Work • Specific cognitive functions are addressed • Highlights the importance of management solutions • No management system for CR networks was proposed • Objective • Design a management system for CR networks

  21. Experimental evaluation RSSI • 5 CPEs using 5 channel (one per CPE) • Importantto observe thesignalsquality. • UsingtheEnergy Detectiontechnique, a high RSSI indicatesanoccupiedchannel.

  22. Introduction (cont.) • Proposed Solution • Management system for CR networks considering the spectrum sensing function • Configuration • Monitoring • Visualization • Provides a continuous learning process to the network administrator

More Related