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

2. Outline Introduction Background Proposed solution Experimental evaluation Final remarks 2

3. Introduction Crescent number of devices are using Radio Frequency (RF) spectrum for communication o However, this resource is limited o 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] o Explored to improve the RF spectrum utilization  Cognitive capability  Reconfigurability 3

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

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

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

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

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

9. Scenario 9 ParameterValue Execution time per experiment60 s Number of channels5 Number of CPEs5 Poisson Mean and Variance (λ)[1 - 5] s Sensing Duration[0.1] s Sensing Period[1, 2] s Maximum bandwidth per channel6 MHz Manager Periodicity (P m )30 s Gateway Periodicity (P g )2 s Experimental evaluation

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

11. 2 - Geolocation 11 Experimental evaluation Geolocation is an important factor in wireless networks o 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. 3 - Transmissions 12 Experimental evaluation 5 CPEs, each one transmitting in one channel Important to analyze the number of transmissions performed by each CPE in each channel

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

14. 5 - Configuration 14 Experimental evaluation Channel Sensingperiod [s] Throughput [Mbps] Variation [%] 1 10.3182 42.04 20.5490 2 10.2267 51.84 20.4708 3 10.4016 18.42 20.4923 4 10.1803 42.54 20.3138 5 10.4027 17.25 20.4867 Reconfiguration of the sensing period o Interval between spectrum sensing executions Observe the average throughput obtained

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

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

17. Thank you! Questions? 17 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 - Telecommunications and information exchange between systems Wireless Regional Area Networks (WRAN) - Specific requirements Part 22: Cognitive Wireless RAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications: Policies and Procedures for Operation in the TV Bands,” IEEE Std 802.22, pp. 1–680, 2011. [Akyildiz et al., 2006] Akyildiz, I. F., Lee, W.-Y., Vuran, M. C., and Mohanty, S. 2006. Next generation/dynamic spectrum access/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. 18

19. Bibliography (cont.) [Potier and Quian, 2011] P. Potier and L. Qian, “Network management of cognitive radio ad hoc networks,” International Conference on Cognitive Radio and Advanced 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-based advanced spectrum scanner for cognitive networks. Wireless Communication & Mobile Computing, Chichester, UK, v.10, n.12, p.1682–1695, 2010. [Stavroulaki et 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, june 2012 [Yucek e Arslan] T. Yucek and H. Arslan, “A survey of spectrum sensing algorithms for cognitive radio applications,” IEEE Communications Surveys Tutorials, 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 19

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

21. RSSI 21 Experimental evaluation 5 CPEs using 5 channel (one per CPE) Important to observe the signals quality. o Using the Energy Detection technique, a high RSSI indicates an occupied channel.

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