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Cooperative Spectrum Sensing

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Cognitive Radio and Networking for Heterogeneous Wireless Networks

Part of the book series: Signals and Communication Technology ((SCT))

Abstract

The main objective of this chapter is to provide a detailed technical insight into latest key aspects of cooperative spectrum sensing. We focus on fusion strategies, quantization enhancements, effect of imperfect reporting channel, cooperative spectrum sensing scheduling, and utilizing cooperatively sensed data via Radio Environment Map (REM).

The sharing of local observations between the secondary users and the fusion center is the most crucial factor that determines the performance of cooperative sensing. Detection performance is determined by the quality of local observations and the quality of the information received by the fusion center. Therefore, the number of quantization bins, the number of bits sent for sensing reports, the global decision logic, and the imperfections in the reporting channel and the erroneous reports due to malfunctioning or malicious secondary devices affect the system performance. Furthermore, there are many channels to sense while the cooperating nodes are few, therefore coordinating the sensing nodes for detecting high quality channels is necessary. Cooperative sensing scheduling concentrates on the scheduling of cooperative nodes and the channels to be sensed.

There is an intricate interplay among the period and size of the sensing reports and spectral resources. Decreasing the number of bits for sensing reports with acceptable performance enables increasing the number of sensing periods and better performance. Furthermore, having a bandwidth-limited reporting channel does not allow sending the whole observation and using complicated protocols for sending the sensing reports to the fusion center. Hence, this chapter also focuses on quantization enhancements.

Due to the periodic sensing requirement of a typical cognitive radio network, cumulative energy consumption for sensing becomes a challenging factor. The energy problem becomes more severe if the users are mobile. The components of energy consumption dedicated to cooperative sensing are analyzed and optimal, and sub-optimal (but efficient) sensing scheduling mechanisms are discussed in order to reduce the sensing energy consumption of the network.

Once the spectrum has been sensed cooperatively, the outcomes can be utilized via REM, which can be considered as an important part of the cognitive engine located at the network. The sensed information may also play a crucial role in the generation of REM. Hence, this chapter also focuses on how the sensing measurements could be utilized for REM construction.

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References

  1. Arslan, H.: Cognitive Radio, Software Defined Radio, and Adaptive Wireless Systems. Springer, Dordrecht (2007)

    Book  Google Scholar 

  2. Atapattu, S., Tellambura, C., Jiang, H.: Energy detection based cooperative spectrum sensing in cognitive radio networks. IEEE Trans. Wirel. Commun. 10(4), 1232–1241 (2011)

    Article  Google Scholar 

  3. Bolea, L., Pérez-Romero, J., Agustí, R., Sallent, O.: Context discovery mechanisms for cognitive radio. In: Proceedings of the 73rd Vehicular Technology Conference (VTC), Budapest, pp. 1–5 (2011)

    Google Scholar 

  4. Cabric, D., Mishra, S., Brodersen, R.: Implementation issues in spectrum sensing for cognitive radios. In: Conference Record of the 38th Asilomar Conference on Signals, Systems and Computers, vol. 1, pp. 772–776, Pacific Grove (2004)

    Google Scholar 

  5. Cabric, D., Tkachenko, A., Brodersen, R.: Spectrum sensing measurements of pilot, energy, and collaborative detection. In: Proceedings of the Military Communications Conference (MILCOM), pp. 1–7, Washington, D.C. (2006)

    Google Scholar 

  6. Cattoni, A.F., Minetti, I., Gandetto, M., Niu, R., Varshney, P.K., Regazzoni, C.S.: A spectrum sensing algorithm based on distributed cognitive models. In: Proceedings of the SDR Forum Technical Conference, Orlando (2006)

    Google Scholar 

  7. Chair, Z., Varshney, P.K.: Optimal data fusion in multiple sensor detection systems. IEEE Transact. Aerosp. Electron. Syst. AES-22(1), 98–101 (1986)

    Article  Google Scholar 

  8. Chaudhari, S., Lundén, J., Koivunen, V.: Bep walls for collaborative spectrum sensing. In: Proceedings of the International Conference on Acoustics, Speech and Signal Processing (ICASSP), Prague, pp. 2984–2987 (2011)

    Google Scholar 

  9. Chen, H., Chen, H.H.: Spectrum sensing scheduling for group spectrum sharing in cognitive radio networks. Wiley Int. J. Commun. Syst. 24(1), 62–74 (2011)

    Article  Google Scholar 

  10. Chiles, J.P., Delfiner, P.: Geostatistics: Modeling Spatial Uncertainty. Wiley, New York (2012)

    Book  Google Scholar 

  11. Conejo, A., Castillo, E., Minguez, R., Garcia-Bertrand, R.: Decomposition Techniques in Mathematical Programming. Springer, Berlin/New York (2006)

    MATH  Google Scholar 

  12. Cressie, N.: Statistics for spatial data. Wiley Terra Nova 4(5), 613–617 (1992)

    Article  Google Scholar 

  13. Dagres, I., Polydoros, A., Riihijärvi, J., Nasreddine, J., Mähönen, P., Gavrilovska, L., Atanasovski, V., van de Beek, J., Sayrac, B., Grimoud, S., Benitez, M.L., Romero, J.P., Agusti, R., Casadevall, F.: Flexible and spectrum-aware radio access through measurements and modelling in cognitive radio systems faramir, D4.1 radio environmental maps: information models and reference model. Technical report FARAMIR EU Project (2011)

    Google Scholar 

  14. Digham, F.F., Alouini, M.S., Simon, M.K.: On the energy detection of unknown signals over fading channels. In: Proceedings of the International Conference on Communications (ICC), Anchorage, vol. 5, pp. 3575–3579 (2003)

    Google Scholar 

  15. Digham, F.F., Alouini, M.S., Simon, M.K.: On the energy detection of unknown signals over fading channels. IEEE Trans. Commun. 55(1), 21–24 (2007)

    Article  Google Scholar 

  16. Eryigit, S., Bayhan, S., Tugcu, T.: Channel switching cost aware and energy-efficient cooperative sensing scheduling for cognitive radio networks. In: IEEE International Conference on Communications (ICC), Dresden, pp. 2633–2638. IEEE (2013): ©[2013] IEEE. Reprinted, with permission, from Eryigit, S., Bayhan, S., Tugcu, T.: Channel switching cost aware and energy-efficient cooperative sensing scheduling for cognitive radio networks. In: Proceedings of IEEE International Conference on Communications, Dresden, June 2013

    Google Scholar 

  17. Eryigit, S., Bayhan, S., Tugcu, T.: Energy-efficient multichannel cooperative sensing scheduling with heterogeneous channel conditions for cognitive radio networks. IEEE Trans. Veh. Technol. 62(6), 2690–2699 (2013). doi:10.1109/TVT.2013.2247070

    Article  Google Scholar 

  18. Gandetto, M., Cattoni, A.F., Regazzoni, C.S.: A distributed approach to mode identification and spectrum monitoring for cognitive radios. In: Proceedings of the SDR Forum Technical Conference, Anaheim (2005)

    Google Scholar 

  19. Gandetto, M., Regazzoni, C.S.: Spectrum sensing: a distributed approach for cognitive terminals. IEEE J. Sel. Areas Commun. 25(3), 546–557 (2007)

    Article  Google Scholar 

  20. Ganesan, G., Li, Y.: Agility improvement through cooperative diversity in cognitive radio. In: Proceedings of the Global Telecommunications Conference (GLOBECOM), Missouri, vol. 5, pp. 2505–2509 (2005)

    Google Scholar 

  21. Ganesan, G., Li, Y.: Cooperative spectrum sensing in cognitive radio networks. In: Proceedings of the First International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN), Baltimore, pp. 137–143 (2005)

    Google Scholar 

  22. Geirhofer, S., Tong, L., Sadler, B.: A measurement-based model for dynamic spectrum access in wlan channels. In: Proceedings of the Military Communications Conference (MILCOM), Washington, D.C., pp. 1–7 (2006)

    Google Scholar 

  23. Gozupek, D., Buhari, S., Alagoz, F.: A spectrum switching delay aware scheduling algorithm for centralized cognitive radio networks. IEEE Trans. Mob. Comput. 12(7), 1270–1280 (2013)

    Article  Google Scholar 

  24. Grimoud, S., Ben Jemaa, S., Sayrac, B., Moulines, E.: A REM enabled soft frequency reuse scheme. In: Proceedings of the GLOBECOM Workshops (GC Wkshps), Miami, pp. 819–823 (2010)

    Google Scholar 

  25. Hao, X., Cheung, M., Wong, V., Leung, V.: A coalition formation game for energy-efficient cooperative spectrum sensing in cognitive radio networks with multiple channels. In: IEEE Global Telecommunications Conference (GLOBECOM 2011), Houston, pp. 1–6 (2011)

    Google Scholar 

  26. Harrison, K., Mishra, S.M., Sahai, A.: How much white-space capacity is there? In: Proceedings of the International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN), Singapore, pp. 1–10 (2010)

    Google Scholar 

  27. Hashemi, H.: The indoor radio propagation channel. Proc. IEEE 81(7), 943–968 (1993)

    Article  Google Scholar 

  28. Herath, S., Rajatheva, N., Tellambura, C.: Energy detection of unknown signals in fading and diversity reception. IEEE Trans. Commun. 59(9), 2443–2453 (2011)

    Article  Google Scholar 

  29. Kaligineedi, P., Bhargava, V.K.: Sensor allocation and quantization schemes for multi-band cognitive radio cooperative sensing system. IEEE Trans. Wirel. Commun. 10(1), 284–293 (2011)

    Article  Google Scholar 

  30. Krige, D.G.: A statistical approach to some mine valuations and allied problems at the witwatersrand. Master’s thesis, University of Witwatersrand (1951)

    Google Scholar 

  31. Lee, S.H., Oh, D.C., Lee, Y.H.: Hard decision combining-based cooperative spectrum sensing in cognitive radio systems. In: Proceedings of the International Conference on Wireless Communications and Mobile Computing: Connecting the World Wirelessly, Leipzig, pp. 906–910 (2009)

    Google Scholar 

  32. Leu, A.E., McHenry, M., Mark, B.L.: Modeling and analysis of interference in listen-before-talk spectrum access schemes. Wiley Int. J. Netw. Manag. 16(2), 131–147 (2006)

    Article  Google Scholar 

  33. Liang, Y., Zeng, Y., Peh, E., Hoang, A.: Sensing-throughput tradeoff for cognitive radio networks. IEEE Trans. Wirel. Commun. 7(4), 1326–1337 (2008)

    Article  Google Scholar 

  34. Mishra, S.M., Sahai, A., Brodersen, R.W.: Cooperative sensing among cognitive radios. In: Proceedings of the International Conference on Communications (ICC), Istanbul, vol. 4, pp. 1658–1663 (2006)

    Google Scholar 

  35. Morgado, A., Carvalho, N.B.: White spaces communications in Europe. In: Proceedings of the 30th General Assembly and Scientific Symposium (URSI), Istanbul, pp. 1–4 (2011)

    Google Scholar 

  36. Murty, R., Chandra, R., Moscibroda, T., Bahl, P.V.: Senseless: a database-driven white spaces network. IEEE Trans. Mob. Comput. 11(2), 189–203 (2012)

    Article  Google Scholar 

  37. Nguyen-Thanh, N., Koo, I.: Evidence theory based cooperative spectrum sensing with efficient quantization method in cognitive radio. IEEE Trans. Veh. Technol. 60(1), 185–195 (2011)

    Article  Google Scholar 

  38. Oh, D.C., Lee, Y.H.: Cooperative spectrum sensing with imperfect feedback channel in the cognitive radio systems. Wiley Int. J. Commun. Syst. 23(6–7), 763–779 (2010)

    Google Scholar 

  39. Pawełczak, P., Guo, C., Prasad, R.V., Hekmat, R.: IRCTR-S-004-07: cluster-based spectrum sensing architecture for opportunistic spectrum access networks. Technical report, International Research Centre for Telecommunications and Radar (2006)

    Google Scholar 

  40. Peh, E., Liang, Y.C.: Optimization for cooperative sensing in cognitive radio networks. In: Proceedings of the Wireless Communications and Networking Conference (WCNC), Hong Kong, pp. 27–32 (2007)

    Google Scholar 

  41. Phillips, C., Ton, M., Sicker, D., Grunwald, D.: Practical radio environment mapping with geostatistics. In: Proceedings of the Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN), Bellevue (2012)

    Google Scholar 

  42. Picinbono, B., Duvaut, P.: Optimum quantization for detection. IEEE Trans. Commun. 36(11), 1254–1258 (1988)

    Article  Google Scholar 

  43. Qihang, P., Kun, Z., Jun, W., Shaoqian, L.: A distributed spectrum sensing scheme based on credibility and evidence theory in cognitive radio context. In: Proceedings of the 17th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Helsiniki, pp. 1–5 (2006)

    Google Scholar 

  44. Riihijärvi, J., Mähönen, P., Sajjad, S.: Influence of transmitter configurations on spatial statistics of radio environment maps. In: Proceedings of the 20th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Tokyo, pp. 853–857 (2009)

    Google Scholar 

  45. Sakran, H., Shokair, M.: Hard and softened combination for cooperative spectrum sensing over imperfect channels in cognitive radio networks. Springer Telecommun. Syst. 52(1), 61–71 (2013)

    Article  Google Scholar 

  46. Sakran, H., Shokair, M., El-Rabaie, E.S., El-Azm, A.A.: Three bits softened decision scheme in cooperative spectrum sensing among cognitive radio networks. In: Proceedings of the 28th National Radio Science Conference (NRSC), Delhi, pp. 1–9 (2011)

    Google Scholar 

  47. Shankar, N., Cordeiro, C., Challapali, K.: Spectrum agile radios: utilization and sensing architectures. In: Proceedings of the First International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN), Baltimore, pp. 160–169 (2005)

    Google Scholar 

  48. Subramani, S., Riihijarvi, J., Sayrac, B., Gavrilovska, L., Sooriyabandara, M., Farnham, T., Mahonen, P.: Towards practical REM-based radio resource management. In: Proceedings of the Future Network and Mobile Summit (FutureNetw), Warsaw, pp. 1–8 (2011)

    Google Scholar 

  49. Sun, C., Zhang, W., Letaief, K.B.: Cooperative spectrum sensing for cognitive radios under bandwidth constraints. In: Proceedings of the Wireless Communications and Networking Conference (WCNC), Hong Kong, pp. 1–5 (2007)

    Google Scholar 

  50. Sun, X., Zhang, T., Tsang, D.: Optimal energy-efficient cooperative sensing scheduling for cognitive radio networks with qos guarantee. In: 7th IEEE International Wireless Communications and Mobile Computing Conference (IWCMC), Istanbul, pp. 1825–1830 (2011)

    Google Scholar 

  51. Tandra, R., Sahai, A.: Fundamental limits on detection in low SNR under noise uncertainty. In: Proceedings of the International Conference on Wireless Networks, Communications and Mobile Computing (WirelessCom), Maui, vol. 1, pp. 464–469 (2005)

    Google Scholar 

  52. Tonkin, M.J., Larson, S.P.: Kriging water levels with a regional-linear and point-logarithmic drift. Wiley Gr. Water 40(2), 185–193 (2002)

    Article  Google Scholar 

  53. UBAK: Türkiye’de dvb-t. http://www.ubak.gov.tr/BLSM_WIYS/HGB/tr/Sag_Menu/20100816_162441_10472_1_64.html. Accessed at May 2011

  54. Unnikrishnan, J., Veeravalli, V.: Cooperative sensing for primary detection in cognitive radio. IEEE J. Sel. Top. Signal Process. 2(1), 18–27 (2008)

    Article  Google Scholar 

  55. Urkowitz, H.: Energy detection of unknown deterministic signals. Proc. IEEE 55(4), 523–531 (1967)

    Article  Google Scholar 

  56. Visotsky, E., Kuffner, S., Peterson, R.: On collaborative detection of TV transmissions in support of dynamic spectrum sharing. In: Proceedings of the First International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN), Baltimore, pp. 338–345 (2005)

    Google Scholar 

  57. Wackernagel, H.: Multivariate Geostatistics: An Introduction with Applications. Springer, Berlin (2003)

    Book  Google Scholar 

  58. Weiss, T.A.: A diversity approach for the detection of idle spectral resources in spectrum pooling systems. In: Proceedings of the 48th International Scientific Colloquium, Ilmenau, pp. 37–38 (2003)

    Google Scholar 

  59. Wirastuti, N., Sastra, N.P.: Application of the suzuki distribution to simulations of shadowing/fading effects in mobile communication. In: Proceedings of the Fourth International Conference on Information and Communication Technology and System, Surabaya Indonesia (2008)

    Google Scholar 

  60. Yilmaz, H.B., Tugcu, T.: Location estimation-based radio environment map construction in fading channels. Wirel. Commun. Mob. Comput. (2013). doi:10.1002/wcm.2367

    Google Scholar 

  61. Yilmaz, H.B., Tugcu, T., Alagoz, F.: Uniform quantizer for cooperative sensing in cognitive radio networks. In: Proceedings of the 21st International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Istanbul, pp. 548–553 (2010)

    Google Scholar 

  62. Yuan, Y., Bahl, P., Chandra, R., Chou, P.A., Ferrell, J.I., Moscibroda, T., Narlanka, S., Wu, Y.: Knows: Cognitive radio networks over white spaces. In: Proceedings of the Second International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN), Dublin, pp. 416–427 (2007)

    Google Scholar 

  63. Zhang, T., Tsang, D.: Optimal cooperative sensing scheduling for energy-efficient cognitive radio networks. In: IEEE International Conference on Computer Communications (INFOCOM), pp. 2723–2731 (2011)

    Google Scholar 

  64. Zhang, W., Mallik, R., Letaief, K.: Optimization of cooperative spectrum sensing with energy detection in cognitive radio networks. IEEE Trans. Wirel. Commun. 8(12), 5761–5766 (2009)

    Article  Google Scholar 

  65. Zhang, X., Wu, Q., Wang, J.: Optimization of sensing time in multichannel sequential sensing for cognitive radio. Wiley Int. J. Commun. Syst. (2011). doi:10.1002/dac.1341

    Google Scholar 

  66. Zhao, Y., Le, B., Reed, J.H.: Network support–the radio environment map. In: Cognitive Radio Technology, pp. 337–363. Elsevier, Amsterdam/Boston (2006)

    Google Scholar 

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Acknowledgements

This work is partially supported by the State Planning Organization of Turkey (DPT) under grant number 07K120610, Bogazici University Research Fund under grant number 7437, and COST Action IC0902.

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Authors and Affiliations

  1. Department of Computer Engineering, Bogazici University, Istanbul, Turkey

    H. Birkan Yilmaz, Salim Eryigit & Tuna Tugcu

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  1. H. Birkan Yilmaz
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  2. Salim Eryigit
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Correspondence to H. Birkan Yilmaz .

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Editors and Affiliations

  1. Electronics and Telecommunications, Sapienza University of Rome, Rome, Italy

    Maria-Gabriella Di Benedetto

  2. Electronic Systems, Aalborg University, Aalborg, Denmark

    Andrea F. Cattoni

  3. Telecommunications, Supeléc, Paris, France

    Jocelyn Fiorina

  4. École Supérieure d'Électricité, Rennes, France

    Faouzi Bader

  5. Sapienza University of Rome, Rome, Italy

    Luca De Nardis

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Yilmaz, H.B., Eryigit, S., Tugcu, T. (2015). Cooperative Spectrum Sensing. In: Di Benedetto, MG., Cattoni, A., Fiorina, J., Bader, F., De Nardis, L. (eds) Cognitive Radio and Networking for Heterogeneous Wireless Networks. Signals and Communication Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-01718-1_3

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  • DOI: https://doi.org/10.1007/978-3-319-01718-1_3

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