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

Lucas Bondan

IEEE/IFIP NOMS 20145 – 9 May, 2014Krakow – Poland

Federal University of Rio Grande do Sul (UFRGS)

2

Outline

• Introduction• Background• Proposed solution• Experimental evaluation• Final remarks

3

Introduction• Crescent number of devices are using Radio

Frequency (RF) spectrum for communicationo However, this resource is limitedo 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

4

Introduction (cont.)

• Rise of CR networkso Designed to operate opportunisticallyo 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?

5

CR Characteristics

• Cognitive Capabilityo Cognitive Functions (CF)s: sensing, decision, sharing, and

mobilityo Spectrum sensing results used as input to the others

• Reconfigurabilityo RF environment is dynamic in its natureo CR devices should be reconfigurableo Network administrator should know the RF environment

Background

6

ObjectiveDesign 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

administratoro IEEE 802.22 Standard assumes a management system

7

Kitsune• Hierarchical management

system for CR networkso 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

Proposed solution

8

ComponentsNetwork Operations Control (NOC)

ManagementStation

Gateway

Cache

Agent

MIB

CF

BS

CPE

CR Network

NetworkAdministrator

Manager

Configuration

Monitoring

Visualization

…

Agent

MIB

CF

CPE

Backhaul …

Information Flow Functional Flow

Proposed solution

9

ScenarioParameter Value

Execution time per experiment 60 s

Number of channels 5

Number of CPEs 5

Poisson Mean and Variance (λ) [1 - 5] s

Sensing Duration [0.1] s

Sensing Period [1, 2] s

Maximum bandwidth per channel 6 MHz

Manager Periodicity (Pm) 30 s

Gateway Periodicity (Pg) 2 s

CPE CPE

CPECPE

ManagementStation

BS

Experimental evaluation

CPE

10

1 - Channels OccupancyExperimental 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 - GeolocationExperimental evaluation

• Geolocation is an important factor in wireless networkso 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 - TransmissionsExperimental 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 throughputExperimental evaluation

• Complementary to the previous visualization• 5 CPEs, each one transmitting in one channel• Average throughput obtained in the

transmissionso What channels present the highest/lowest throughput

14

5 - ConfigurationExperimental evaluation

Channel Sensing period [s]

Throughput[Mbps]

Variation [%]

11 0.3182

42.042 0.5490

21 0.2267

51.842 0.4708

31 0.4016

18.422 0.4923

41 0.1803

42.542 0.3138

51 0.4027

17.252 0.4867

• Reconfiguration of the sensing periodo Interval between spectrum sensing executions

• Observe the average throughput obtained

15

Conclusions• Main contribution: Hierarchical management

systemo Provides to the network administrator a way to analyze the

network environmento Eases the analysis of the spectrum sensing results

• A management system for CR networks should consider the spectrum sensing functiono Visualizations may improve the network administrator knowledge

• Configuration, monitoring, and visualization are part of a continuous process

Final remarks

16

Future Work

• Extend Kitsune operation for different networks architectureso 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

Final remarks

17

Thank you!• Questions?

Lucas BondanWebsite: inf.ufrgs.br/~lbondanE-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.

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

20

Introduction (cont.)• Rise of CR networks

o Designed to operate opportunisticallyo IEEE 802.22 Standard

• Related Worko Specific cognitive functions are addressedo Highlights the importance of management solutionso No management system for CR networks was proposed

• Objectiveo Design a management system for CR networks

21

RSSIExperimental 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 Solutiono Management system for CR networks considering the spectrum

sensing function Configuration Monitoring Visualization

o Provides a continuous learning process to the network administrator