1. IEEE TUTORIAL WEA 2012 Cross Layer Analysis for a Dynamic Cross Spectrum Allocation System System - A Cognitive Sensor Network Testbed Approach Autonomous Metropolitan University - Iztapalapa Electrical Engineering DepartmentEnrique Rodrguez de la Colina, PhD. erod@xanum.uam.mx May 20121

2. Outline Introduction Cognitive Radio Networks (CRN) Dynamic Spectrum Allocation (DSA) Main Functions of a Cognitive Radio Device Sensing, decision making, sharing, mobilityDSA - Test Bed Design CR - Sensor Networks Approach Sensing and media access control (MAC) Decision Making Control & MAC Communication Interface and Upper Layers Applications Proposals Software defined radio (SDR) Sustainable design Energy consumption and adapting power Conclusions & Future Work Challenges , design, technology and future applications2 3. IntroductionCOGNITIVE RADIO NETWORKS 3 4. Cognitive Radio Networks (CRN) Wireless Communication model where the devices adjust their parameters transmission and reception4 5. Background Most of the RF spectrum is assigned to licensed communications by governments5 6. Context Frequency bands are regulated by governments where fixed frequency bands are assigned. Thus the policies of use depends on, Geography Population Local use of the frequencies6 7. Context Free frequency bands are saturated by the increase of wireless technologies and applications7 8. Context Diverse ways of signal handling8 9. Context Inefficient use of the private regions of the spectrum Management in time, frequency, coding and space9 1. Wellens, Matthias; Wu, Jin; Mahonen, Petri;, Evaluation of Spectrum Occupancy in Indoor and Outdoor Scenario in the Context of Cognitive Radio, IEEE Cognitive Radio Oriented Wireless Networks and Communications, 2007 10. Cognitive Radio Networks (CRN) CR devices can be classified as, Full cognitive radio (Mitolas radio)1 All the parameters observed by a node are considered for adaptationCR device for dynamic spectrum allocation (DSA) Spectrum Sensing Cognitive Radio This approach considers only the frequency spectrum changes10 et. al. 1. J. Mitola III and G.Q Maguire, Jr., Cognitive Radio: Making Software Radios More Personal, IEEE Personal Communications (Wireless Communications), vol.6, no. 4, pp. 13-18, August 1999. 11. Cognitive Radio Networks Operative parameters change based on monitoring several factors Changes are induced by external and internal parameters such as, Communication characteristics, e.g. utilization Power energy Social behavior Tx/Rx parameters RF spectrum changes Eb/NoFrequency 11 time 12. Dynamic Spectrum Allocation (DSA) The Dynamic Spectrum Allocation (DSA) solves some issues for the frequency spectrum, the waste of frequency spectrum bands due to few use the increase number of wireless systems in some frequency portions the random use of the spectrum bands QoS for wireless services12 13. Cognitive Radio Networks One premise is to avoid interference with licensed users Licensed users (primary users) No licensed users (secondary users) Then it is required to locate devices fast and with accuracy to avoid delays Systems with different characteristics heterogeneous and homogeneous Applications adaptation 13 14. Cognitive Radio Networks Fundamentals Depending of the spectrum availability, the CR devices can be identified as,Cognitive Radio Devices in licensed bands which operates in coexistence with primary users, for example, in U.S.A. this systems operate in digital TV bandsCognitive Radio Devices away from licensed bands this devices operate only out of the licensed bands of the frequency spectrum, most of experimental testsbed or in free licensed bands14 15. Cognitive Radio Networks Fundamentals Using previous definitions the CRN can be classified as in [2], Underlay: The frequency section used by these CR devices is also used by primary users where CR devices mainly use spread spectrum techniques to avoid interference Overlay: The frequency section used by the CR devices is not occupied by licensed users, so the interference to primary users is not considerable15 2. A. M. Wyglinski, M. Nekovee, and Y. T. Hou, Cognitive Radio Communications and Networks, Principles and Practice, vol. ISBN 978-0-12-374715-0 (alk. paper): Elsevier, 2010. 16. Cognitive Radio Networks Fundamentals16 2. A. M. Wyglinski, M. Nekovee, and Y. T. Hou, Cognitive Radio Communications and Networks, Principles and Practice, vol. ISBN 978-0-12-374715-0 (alk. paper): Elsevier, 2010. 17. Cognitive Radio Networks ChallengesMain challenges for the protocols implemented in CR devices Spectrum random changes Noise and interference Communication collision between users17 18. CR devices basic functions Prof. Ian F. Akyildiz in A Survey on Spectrum Management in Cognitive Radio Networks [3] among other authors explains main functions of CR devices, Spectrum Sensing: sensing the spectrum holes. The spectrum sensing function enables the cognitive radio to adapt to its environment by detecting spectrum holes. Spectrum decision: a cognitive radio determines the data rate, the transmission mode, and the bandwidth of the transmission. Then, the appropriate spectrum band is chosen according to the spectrum characteristics and user requirements. Spectrum sharing: coordination and collaboration with other devices Spectrum mobility : mobility and connection management approaches to reduce delay and loss during spectrum handoff18 19. CRN main functions19 20. Spectrum management TasksCognitive FunctionDetermine white spaceshow?Sensingwhen?Decision makingCoordination and collaborative tasks with otherswho?CoordinationMoving and hand offwhere?MobilityDecision making and media accessProtocols and control of the CR device20 21. BackgroundFUNDAMENTAL FUNCTIONS21 22. Funciones principales Ian F. Akyildiz3 :22 3. F. Akyildiz, W.Y. Lee, M.C. Buran, and S. Mohanty, A survey on spectrum management in cognitive radio networks, IEEE Communications Magazine, vol. 46, no. 4, pp. 40-48, April 2008. 23. Functions Ian F. Akyildiz3 et al. : Spectrum Sensing Spectrum monitoringSpectrum decision: decision making, media selectingSpectrum coordination with othersSpectrumaccessandsharing: andcollaborationmobility:communications must continue moving to another spectrum portion when primary users presence23 3. F. Akyildiz, W.Y. Lee, M.C. Buran, and S. Mohanty, A survey on spectrum management in cognitive radio networks, IEEE Communications Magazine, vol. 46, no. 4, pp. 40-48, April 2008. 24. Functions Ian F. Akyildiz3 et al. : Spectrum Sensing Spectrum monitoringSpectrum decision: decision making, media selectingSpectrum coordination with othersSpectrumaccessandsharing: andcollaborationmobility:communications must continue moving to another spectrum portion when primary users presence24 3. F. Akyildiz, W.Y. Lee, M.C. Buran, and S. Mohanty, A survey on spectrum management in cognitive radio networks, IEEE Communications Magazine, vol. 46, no. 4, pp. 40-48, April 2008. 25. Funciones principales Ian F. Akyildiz3 et al. : Spectrum Sensing Spectrum monitoringSpectrum decision: decision making, media selectingSpectrum coordination with othersSpectrumaccessandsharing: andcollaborationmobility:communications must continue moving to another spectrum portion when primary users presence25 3. F. Akyildiz, W.Y. Lee, M.C. Buran, and S. Mohanty, A survey on spectrum management in cognitive radio networks, IEEE Communications Magazine, vol. 46, no. 4, pp. 40-48, April 2008. 26. Funciones principales Ian F. Akyildiz3 et al. : Spectrum Sensing Spectrum monitoringSpectrum decision: decision making, media selectingSpectrum coordination with othersSpectrumaccessandsharing: andcollaborationmobility:communications must continue moving to another spectrum portion when primary users presence26 3. F. Akyildiz, W.Y. Lee, M.C. Buran, and S. Mohanty, A survey on spectrum management in cognitive radio networks, IEEE Communications Magazine, vol. 46, no. 4, pp. 40-48, April 2008. 27. DSA proposal UPPER MAC PHYSICALPROTOCOL STACK ( LAYERS ) Cross-layer approach Application Interfaces ServicesTransport UDPRouting Multi-hop TCP Point-to-PointProtocol adaptationAccess Control Coordinate SharingFront-end Communication SensingProactiveDecision ModuleReactiveSpectrum Analysis Environment Data Control ModuleInformation27 28. DSA proposal UPPER MAC PHYSICALPROTOCOL STACK ( LAYERS ) Physical Layers Application Interfaces ServicesTransport UDPRouting Multi-hop TCP Point-to-PointProtocol adaptationAccess Control Coordinate SharingFront-end Communication SensingProactiveDecision ModuleReactiveSpectrum Analysis Environment Data Control ModuleInformation28 29. Spectrum Sensing29 30. Spectrum SensingShadowingReflectionRefractionsCR devices have the same difficulties that wireless networks, Noise and Interference Collisions between users30Fig. Reference: John Schiller, Mobile Communications, Addison Wesley, 2a Ed., 2003 31. Sensing Spectral analysis Opportunities detection Performing time Energy detection based on levels (blind detection) Digitalizing the spectrum management Availability vector binary Occupied or available31 32. Sensing Test of the spectrum occupancy: Metageek device Drawbacks Private software Input data precision32 33. Sensing and monitoring State Machine device implemented Implementation using PICs Developing a MAC system Work on the communication interface Proposed to use 2 interfaces to speed-up the system For detection For communicationCommunications interface (Microcontroller)Media Access Module (MAC) & detection33 34. Challenges for the Physical Layer Parallelization Space diversity Improve resolution Reception range Bandwidth Devices operation New techniques integration Embedded systems34 35. Sensing for a Sensor Network Approach: Interface IEEE 802.15.4 (ZigBee) Detection procedure Sequential Parallel Monitoring time response (200ms) Drawbacks Communication between hardware Technologies limitations per se35 36. Single sensing module XBee PIC module for testing XBee Modul e SlaveSignal outputStar t bit36 37. Single sensing module Sensing - delays in the detection and delays histogram Processing delayProcessing delay histogram900 300850750700650600550050100150200250Iteration300Iteration350400450500200Frequencyoccurrence800D e la y [m s]Delay [ms]250150100500 550600650700750800850900Delay [ms]Delay [ms] 37 38. Physical Layer - Sensing Sensing energy detection Channel 2 - 2.410 GHzChannel 1 - 2.405 GHz300300250150100200Frequencyoccurrence200Frequencyoccurrence250150100505000 55606570758046505458626670747882Energy [-dBm]85Energy [-dBm]Channel 4 - 2.420 GHz 350Channel 3 - 2.415 GHz 300300150100250Frequencyoccurrence200Frequencyoccurrence2502001501003850500 5504650545862Energy [-dBm]667074energy level [dBm]788260657075Energy [-dBm]energy level [dBm]8085 39. Physical Layer - Sensing 80energy detection (dBm) Energy detection (XBee Pro)700 260 4 50channel C hannel6 840 10 3012 1420 16 1810 510152025 Scanscan303540455039 0 40. Cognitive characteristics for wireless sensor networks Integration Time response and bandwidth restrictions Interfaces with other modules is a challenge Energy consumption limitations40 41. Diversity principles, example Model of communication with Additive White Gaussian Noise (AWGN) channel and being time variant the channel characteristic varies in average over the time, acceptable quality detection 90 % of the time poor quality detection 10 % of the time bit error rate (BER) of 10-10 for the acceptable quality detection, BER of 0.5 for the poor quality reception41 42. Sensing diversity principles time % 0.9BER 1.0E-10time % 0.1BER 0.55.00E-02 2.50E-022 antennas Antena 1 signal 1 no signal 0Antena2 signal 1 no signal 0Ant1 Prob0 0 1 10 1 0 10.1 0.1 0.9 0.9Ant2 Prob Probability 0.1 0.9 0.1 0.90.01 0.09 0.09 0.810.01 0.18xBER 0.005 1.8E-110.818.10E-110.01 9.9E-010.005 9.9E-112 ANT BER5.00E-03 0 reception probability 1 rx probability5.00E-033 antennas Antena 1 signal 1 no signal 0 1 2 3 4 5 6 7 8Antena2 signal 2 no signal 0Antena3 signal 3 no signal 0Ant1 ProbAnt2 ProbAnt2 Prob0 0 0 1 0 1 1 10 0 1 0 1 0 1 10 1 0 0 1 1 0 10.10 0.10 0.10 0.90 0.10 0.90 0.90 0.900.10 0.10 0.90 0.10 0.90 0.10 0.90 0.900.10 0.90 0.10 0.10 0.90 0.90 0.10 0.901.E-08 1.E+00BER 5.E-09 1.E-108 antennas Bad reception probability Good reception probability1.0E-03 9.0E-03 9.0E-03 9.0E-03 8.1E-02 8.1E-02 8.1E-02 7.3E-011.0E-03 2.7E-02xBER 5.0E-04 2.7E-122.4E-012.4E-117.3E-017.3E-113 ANT BER5.00E-0442 5.E-09 43. Diversity principles, example The resulted BER in average for a single receiver is about 0.05, which is quite erroneous However, for eight receptors, the BER would be 5x10-10 which represents a much better approach to have truthful detection another important factor to improve accuracy is the quality of the components used 43 44. DescriptionTESTBED44 45. Sensor Network Testbed Physical Layer - Sensing multiple receivers XBeeXBeeXBeeXBeePICPICPICPICXBeeXBeeXBeeXBeePICPICPICPICSignal BUSControl BUSBUSMaster Microcontroller Spectrum sensing module*PIC is a family of modified Harvard architecture microcontrollers made by Microchip TechnologyMultiple receivers and one master coordinator 45Dr. Enrique Rodrguez de la Colina 46. Physical Layer - Sensing occurrenceoccurrence Sensing two slaves coordination and tuning -01 10 Detection options001101 10 Detection options11occurrenceoccurrence000001 10 11 Detection options00 00 01 01 10 10 11 11 Detection options Detection options46 47. Physical Layer - Sensingother combinations11111111other combinations111111110000000000000000other combinations11111111occurrenceoccurrence00000000occurrenceoccurrence - eight slaves coordination and tuning00000000other combinations1111111147 48. CR MAC CR MACArchitectureCentralizedDistributedSpectrum Sharing BehaviorCooperativeNonCooperativeSpectrum Sharing ModeOverlayUnderlayAccess ModeConetention FreeConetention based48 Jie Xiang, Yan Zhang, Tor Skeie, Medium Access Control Protocols in Cognitive Radio Networks, WCMC2010; 10:31-49 Wiley InterScience 49. CR MAC49 Jie Xiang, Yan Zhang, Tor Skeie, Medium Access Control Protocols in Cognitive Radio Networks, WCMC2010; 10:31-49 Wiley InterScience 50. Distributed vs. Centralized Centralized or infrastructureAd-hoc Distributed50 51. More challengesHidden terminalFar and near terminal John Schiller, Mobile Communications, Addison Wesley, 2a Ed., 200351 52. MAC52 53. Media Access Control (MAC) MAC Proposal, includes a literature review and based on criteria design which consist of, Avoidance of a Control Common Channel (CCC) Cooperative Overlay and Underlay scheme Applicable to centralized and distributed systems Development of a customized simulator53 54. Media Access Control (MAC) Tests using a WiFi platformCognitive 1Cognitive 2 54 55. Media Access Control (MAC) Algoritmo preliminar basado en intercambio de mensajes55 56. MAC - DECISION MAKING56 57. Media Access Control (MAC)For the MAC module, Decision making module Attributes assignmentNumeric validation user-centric systemSimulation with CRUAMAC* Enrique Rodriguez-Colina, Carlos Ramirez-Perez y C. Ernesto Carrillo A:, Multiple attribute dynamic decision making for cognitive radio networks, IEEE Wireless and Optical Communications Networks (WOCN), June 2011.57 58. Decision Making Module (DMM)58 Enrique Rodriguez-Colina, Carlos Ramirez-Perez y C. Ernesto Carrillo A:, Multiple attribute dynamic decision making for cognitive radio networks, IEEE Wireless and Optical Communications Networks (WOCN), June 2011. 59. Multiple attribute dynamic decision making for CRN We model the Spectrum Decision making functionality with multiple attributes We propose a novel use of the Analytic Hierarchy Process (AHP) to optimally select available bands from a finite set of options Our approach classifies from the best to the worst bands based on the requirements from two different classes of service, Real Time and Best Effort The selection of the best available bands is done with a low execution latency. Enrique Rodriguez-Colina, Carlos Ramirez-Perez y C. Ernesto Carrillo A:, Multiple attribute dynamic decision making for cognitive radio networks, IEEE Wireless and Optical Communications Networks (WOCN), June 2011.59 60. Analytic Hierarchy Process (AHP)60 Enrique Rodriguez-Colina, Carlos Ramirez-Perez y C. Ernesto Carrillo A:, Multiple attribute dynamic decision making for cognitive radio networks, IEEE Wireless and Optical Communications Networks (WOCN), June 2011. 61. Outcome61 Enrique Rodriguez-Colina, Carlos Ramirez-Perez y C. Ernesto Carrillo A:, Multiple attribute dynamic decision making for cognitive radio networks, IEEE Wireless and Optical Communications Networks (WOCN), June 2011. 62. Example62 Enrique Rodriguez-Colina, Carlos Ramirez-Perez y C. Ernesto Carrillo A:, Multiple attribute dynamic decision making for cognitive radio networks, IEEE Wireless and Optical Communications Networks (WOCN), June 2011. 63. The proposed AHP delay response63 Enrique Rodriguez-Colina, Carlos Ramirez-Perez y C. Ernesto Carrillo A:, Multiple attribute dynamic decision making for cognitive radio networks, IEEE Wireless and Optical Communications Networks (WOCN), June 2011. 64. The proposed AHP conclusions64 Enrique Rodriguez-Colina, Carlos Ramirez-Perez y C. Ernesto Carrillo A:, Multiple attribute dynamic decision making for cognitive radio networks, IEEE Wireless and Optical Communications Networks (WOCN), June 2011. 65. Statistical - decision making Statistical model for decision making Spectrum SensingCriteria, e.g. BW, SINR, occupancydecision makerProbability error of the decision making process Ranking CorrelationDatabase of KnowledgeBand HistogramsProcessed SamplesSnapshot-measure ranksNo. times the best 1 2 3 4 5 .. bandsBest bandsNo. times 2nd place 1 23To CRbandsNo. times the worst 1 2 3 4 5 .. bandsWorst bandsV1V2Vi1 15 3 2 7 83 15 7 2 5 14 15 1 3 2 1 timeDr. Enrique Rodrguez de la Colina65 66. Reactive and Proactive ApproachSystem performance reactiveSystem performance proactive 66Enrique Rodriguez-Colina, Vctor-M. Ramos-R., Gerardo Laguna-Sanchez, Cross Layer Analysis for a Dynamic Spectrum Allocation System, -A Cognitive Sensor Network Testbed Design-, IEEE Workshop on Engineering Applications (WEA) 2012 67. Media Access Techniques Diverse techniques to access the media and its combinations, Coding [Eb/No]space time frequencyfrequencycoding time This improves the spectrum management but there are various restrictions67 68. SHARING & COLLABORATION68 69. Distributed vs. Centralized Centralized or infrastructureAd-hoc Distributed69 70. Collaboration To share the spectrum monitoring Decision making and channel selection with collaborations Communications coordination70 Jiaqi Duan, Yong Li, Performance Analysis of Cooperative Spectrum Sensing in Different Fading Channels, IEEE 2010 71. UPPER LAYERS71 72. Upper Layers UPPER MAC PHYSICALPROTOCOL STACK ( LAYERS ) Cross-layer approach Application Interfaces ServicesTransport UDPRouting Multi-hop TCP Point-to-PointProtocol adaptationAccess Control Coordinate SharingFront-end Communication SensingProactiveDecision ModuleReactiveSpectrum Analysis Environment Data Control ModuleInformation72 73. Upper Layers Routing is an issue to solve mainly when the system is multihop The Transport Layer must be more robust to changes at the same time the73 74. Upper Layers backup channels The application layer consists in a human interface to allocate the communication and to set the parameters desired by the user e.g., the size of the file to transmit Cognitive device for a sensor network where information data is sent using free channels only to avoid interference to primary users, so the scalability can be increased74 75. PROPOSALS75 76. Propuesta coexistencia de PU con CR Control channel proposal, MAC with time division and frequency division Todays technology and heterogeneous76 Nicols Bolvar, J. L. Marzo, E. Rodriguez-Colina, Distributed Control using Cognitive Pilot Channels in a Centralized Cognitive Radio Network. AICT 2010 IEEE Computer Society Conference proceedings, May 9 - 15, 2010 77. CR device model for centralized system Central system design77 Nicols Bolvar, J. L. Marzo, E. Rodriguez-Colina, Distributed Control using Cognitive Pilot Channels in a Centralized Cognitive Radio Network. AICT 2010 IEEE Computer Society Conference proceedings, May 9 - 15, 2010 78. 78 Nicols Bolvar, J. L. Marzo, E. Rodriguez-Colina, Distributed Control using Cognitive Pilot Channels in a Centralized Cognitive Radio Network. AICT 2010 IEEE Computer Society Conference proceedings, May 9 - 15, 2010 79. 79 80. Embedded system which covers the spectrum Longitud de ondaFrecuenciashttp://mynasadata.larc.nasa.gov/images/EM_Spectrum3-new.jpgA device to be able to cover the whole spectrum is the challenge80 81. Small device which covers the spectrum Control node ControlMonitoring FPGA interfaceHardware simplification81Device with full capacity 82. XBeeXBeeXBeeXBeePICPICPICPICXBeeXBeeXBeeXBeePICPICPICSmart detection in integrated platformPICSignal BUSControl BUSBUSMaster Microcontroller Spectrum sensing module *PIC is a family of modified Harvard architecture microcontrollers made by Microchip Technology82 83. Communication and channelization controls WLAN RFControl nodeFPGA interfaceRFWLANSpectrum analyserFPGA interfaceRF FPGA interfaceSignal power (W)WLAN0 1 0 1 1 1 0 10 0 1 0 1Frequency (Hz)WLAN FPGA interfaceRF Canales de comunicacin WLANWLANRF FPGA interfaceFPGA interfaceRF83 84. Integrated hardware and software Signal power (W)Bussy channel = 1 0 1 0 1 1 1 0 10 0 1 0 1Frequency (Hz)Control nodeEmulador de analizador FPGA interfaceControl interface with the use of FPGAs - PC emulates the frequency spectrum (busy = 1 y free= 0) - PC sends vector with information (0101110100101)84 85. Other CR devices competencesReal time performance Power adaptation Diverse bands inter-connection inter-Flexibility for protocol adaptationError controlNew applications adjustments 85 Mobility prediction 86. SOFTWARE DEFINED RADIO86 87. Software defined radio (SDR) Conventional Radio IF signalRF signalAmplifier Mixer FilterAmplifier Mixer FilterBase band signal Software defined radio RF signalIF signal Amplifier Mixer FilterDigital / Analog ConverterDigital signal processingRx Tx87 Cognitive Software Defined Radio: Applications of Cognitive SDR using the GNU Radio and the USRP, David Scaperoth, 2005 Joseph Mitola III, Software Radio Architecture, John Wiley & Sons, 2000 88. Software defined radio (SDR) 89. UPPER MAC PHYSICALPROTOCOL STACK ( LAYERS )Application Interfaces ServicesTransport UDPRouting Multi-hop TCP Point-to-PointProtocol adaptationAccess Control Coordinate SharingFront-end Communication SensingProactiveDecision ModuleReactiveSpectrum Analysis Environment Data Control ModuleInformation89 90. 90 91. Software defined radio (SDR) 92. Software defined radio (SDR)Se plantea la creacin de un sistema que pueda operar con la tecnologa existente92 93. Sustainable design initiative SustainableSystems adaptation for efficient use of the RF spectrum Introduction Energy reduction for future communications Sustainable development93 94. Saving energy?94-trend to reduce energy consumption- 95. Project development Sustainable development High technology communicationseconomyPlanned, cost-benefit, sustainable, feasible, ubiquitous Adaptable, ecological,environment sociallife -friendlyTechnology changes through, policies and scientific designDynamic, Feasible , usable, ubiquitous95Dr. Enrique Rodrguez de la Colina 96. Project development Sustainable development High technology communicationseconomyPlanned, cost-benefit, sustainable, feasible, ubiquitous Adaptable, ecological,environment sociallife -friendlyTechnology changes through, policies and scientific designDynamic, Feasible , usable, ubiquitous96Dr. Enrique Rodrguez de la Colina 97. Cognitive Radio techniques used Analyze the spectrum behavior Power consumption e.g.: Adaptive Power Algorithms to optimize communication97 98. Capabilities of the CRNCoding Power adaptationfrequencyError control98time UAM 99. 99 D. S. Peter Steenkiste, Gary Minden, Dipankar Raychaudhuri "Future Directions in Cognitive Radio Network Research. Executive Summary " in NSF Workshop Report 2009. 100. Conclusions More research is required to develop practical cognitive radio devices Multidisciplinary work is essential for the development of a wireless cognitive technology The ideas used by CR devices can help to create a sustainable development in wireless communications New MAC design is also required Monitoring tools and testbeds are a good approach to the CRN100 101. Future work We plan to, analyze other hardware platforms to improve the spectrum sensing function investigate other applications with cognitive radio devices The development of systems that can operate with current technology The use of GNU Radio over SDR platforms101 102. Future work Android programming Definition of new functionalities for lower layers Wireless technology integration Routing evaluation for multi-hop networks Design and implementation of new testbeds Wireless sensor network applications102 103. Bibliography 1. J. Mitola III and G.Q Maguire, Jr., Cognitive Radio: Making Software Radios More Personal, IEEE Personal Communications (Wireless Communications), vol.6, no. 4, pp. 1318, August 1999. 2. I. F. Akyildiz, W.Y. Lee, M.C. Buran, and S. Mohanty, A survey on spectrum management in cognitive radio networks, IEEE Communications Magazine, vol. 46, no. 4, pp. 40-48, April 2008. 3. F. Wang, M. Krunz, and S. Cui, Spectrum Sharing in Cognitive Radio Networks, in IEEE 27th Conference on Computer Communications, INFOCOM 2008, pp. 36-40, April 2008. 4. H. Wang, H. Qin, and L. Zhu, A Survey on MAC Protocols for Opportunistic Spectrum Access in Cognitive Radio Networks, in IEEE International Conference on Computer Science and Software Engeneering 2008, pp. 214-218, December 2008. 5. Jie Xiang, Yan Zhang, Tor Skeie, Medium Access Control Protocols in Cognitive Radio Networks, WCMC2010; 10:31-49 Wiley InterScience. 6. Andreas F. Molish, Larry J. Greenstein and Manson Shafi, Propagation Issues for Cognitive Radio, IEEE proceedings, 2009 7. John Schiller, Mobile Communications, Addison Wesley, 2a Edicin, 2003 8. Nicols Bolvar, J. L. Marzo, E. Rodriguez-Colina, Distributed Control using Cognitive Pilot Channels in a Centralized Cognitive Radio Network. AICT 2010 IEEE Computer Society Conference proceedings, May 9 - 15, 2010 9. Joseph Mitola III, Software Radio Architecture, John Wiley & Sons, 2000 10. Hongjian Sun, DI Laurenson JS Thompson, Cheng-Xiang Wang, A novel Centralized Network for Sensing Spectrum in Cognitive Radio 11. Jiaqi Duan, Yong Li, Performance Analysis of Cooperative Spectrum Sensing in Different Fading Channels, IEEE 2010103 104. Thank you, questions? Gracias a la Universidad Distrital, Bogot Colombia por la invitacin Dr. Enrique Rodrguez de la Colina erod@xanum.uam.mxUniversidad Autnoma Metropolitana Iztapalapa 104