Skip to main content
SpringerLink
Log in

Spectrum Sensing in Cognitive Radio Networks: Potential Challenges and Future Perspective

  • Chapter
  • First Online:
Spectrum Sharing in Cognitive Radio Networks

Abstract

Due to the huge number of diverse wireless devices and technologies, spectacular increases in the number of wireless subscribers, advent of new applications and continuous demand for higher data-rates, the radio frequency (RF) spectrum is becoming more and more crowded. This development calls for systems and devices that are aware of their surrounding RF environment, so they can facilitate flexible, efficient, and reliable operation and utilization of the available spectral resources. Thus, the spectrum sensing is becoming progressively more important to recent and future wireless communication systems for identifying underutilized spectrum and characterizing interference, with the goal of achieving reliable and efficient operation. Cognitive radio is an intelligent radio that is aware of its surrounding environment, capable of learning and adapting its behavior and operation to provide a good match to its surrounding environment and to the user’s needs. Spectrum sensing is the key requirement and one of the most challenging issues for the cognitive radio system. This chapter presents a comprehensive survey of the physical layer spectrum sensing techniques for cognitive radios. The major challenges in spectrum sensing are outlined and several techniques for improving spectrum sensing performance are discussed. Further, a hybrid model for non-cooperative spectrum sensing is presented; with this terminology, the proper channelization of the three techniques is introduced, with relevant discussion. This approach helps in detecting the idle spectrum opportunistically, with better spectrum utilization under non-cooperative sensing, resulting in enhanced spectrum efficiency. We also explore sensing under a cooperative environment. The approach presented aids in opportunistically detecting idle spectrum bands (spectrum holes that are the underutilized sub-bands of the radio spectrum), with better utilization of the spectrum than under non-cooperative sensing, and increased overall spectrum efficiency.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Q. Zhao, B.M. Sadler, A survey of dynamic spectrum access. IEEE Signal Process. Mag. 24(3), 79–89 (2007)

    Article  Google Scholar 

  2. Q. Zhao, L. Tong, A. Swami, Y. Chen, Decentralized cognitive MAC for opportunistic spectrum access in ad hoc networks: a POMDP framework. IEEE J. Sel. Areas Commun. 25(3), 589–600 (2007)

    Article  Google Scholar 

  3. H.-S. Chen, W. Gao, D.G. Daut, Spectrum sensing for wireless microphone signals, in Proceedings of the 5th IEEE Annual Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks. SECON Workshops ’08, 16–20 June 2008, pp. 1–5

    Google Scholar 

  4. Y. Chen, Q. Zhao, A. Swami, Distributed spectrum sensing and access in cognitive radio networks with energy constraint. IEEE Trans. Signal Process. 57(2), 783–797 (2009)

    Article  MathSciNet  Google Scholar 

  5. Q. Zhao, B. Krishnamachari, K. Liu, On myopic sensing for multi-channel opportunistic access: structure, optimality, and performance. IEEE Trans. Wireless Commun. 7(12), 5431–5440 (2008)

    Article  Google Scholar 

  6. S.H.A. Ahmad, M. Liu, T. Javidi, Q. Zhao, B. Krishnamachari, Optimality of myopic sensing in multichannel opportunistic access. IEEE Trans. Inf. Theory 55(9), 4040–4050 (2009)

    Article  MathSciNet  Google Scholar 

  7. R.S. Sutton, A.G. Barto, Reinforcement Learning: An Introduction (MIT Press, Cambridge, MA, 1998)

    Google Scholar 

  8. S. Haykin, Neural Networks: A Comprehensive Foundation, 2nd edn. (Prentice-Hall, Inc., 1999)

    Google Scholar 

  9. T. Yucek, H. Arslan, A survey of spectrum sensing algorithms for cognitive radio applications. IEEE Commun. Surv. Tutorials 11(1), 116–130, First Quarter (2009)

    Google Scholar 

  10. W.D. Horne, Adaptive spectrum access: using the full spectrum space, in Proceedings of the Annual Telecommunications Policy Research, Arlington, VA, Oct 2003

    Google Scholar 

  11. S. Haykin, D.J. Thomson, J.H. Reed, Spectrum sensing for cognitive radio. Proc. IEEE 97(5), 849–877 (2009)

    Article  Google Scholar 

  12. C. Cormiob, K.R. Chowdhury, A survey on MAC protocols for cognitive radio networks. Ad Hoc Netw. 7(7), 1315–1329 (2009)

    Article  Google Scholar 

  13. A. Sabharwal, P. Schniter, D. Guo, D.W. Bliss, S. Rangarajan, R. Wichman, In-band full-duplex wireless: challenges and opportunities. IEEE J. Sel. Areas Commun. 32(9), 1637–1652 (2014)

    Article  Google Scholar 

  14. B. Shen, K.S. Kwak, Soft combination schemes for cooperative spectrum sensing in cognitive radio networks. ETRI 31(3), 263–273 (2009)

    Article  Google Scholar 

  15. M. Kam, Q. Zhu, W.S. Gray, Optimal data fusion of correlated local decisions in multiple sensor detection systems. IEEE Trans. Aerosp. Electron. Syst. 28(3), 916–920 (1992)

    Article  Google Scholar 

  16. B. Chen, R.X. Jiang, T. Kasetkasem, P.K. Varshney, Channel aware decision fusion in wireless sensor networks. IEEE Trans. Signal Process. 52(12), 3454–3458 (2004)

    Google Scholar 

  17. Z. Chair, P.K. Varshney, Optimal data fusion in multiple sensor detection systems. IEEE Trans. Aerosp. Electron. Syst. 22(1), 98–101 (1986)

    Article  Google Scholar 

  18. X. Chen, H.H. Chen, W. Meng, Cooperative communications for cognitive radio networks—from theory to applications. IEEE Commun. Surv. Tutorials 16(3), 1180–1192, Third Quarter (2014)

    Google Scholar 

  19. B. Wang, K.J. Ray Liu, Advances in cognitive radio networks: a survey. IEEE J. Sel. Top. Signal Process. 5(1), 5–23 (2011)

    Google Scholar 

  20. S.M. Mishra, A. Sahai, R.W. Brodersen, Cooperative sensing among cognitive radios, in Proceedings of the IEEE International Conference on Communications (ICC’06), Istanbul, June 2006, vol 4, pp. 1658–1663 (2006)

    Google Scholar 

  21. A. Ghasemi, E.S. Sousa, Collaborative spectrum sensing for opportunistic access in fading environments, in Proceedings of the 1st IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN 2005), Baltimore, MD, USA, 8–11 Nov 2005, pp. 131–136

    Google Scholar 

  22. W. Yue, B. Zheng, A two-stage spectrum sensing technique in cognitive radio systems based on combining energy detection and one-order cyclostationary feature detection, in Proceedings of the International Symposium on Web Information Systems and Applications (WISA09), China, 22–24 May 2009, pp. 327–330

    Google Scholar 

  23. P.R. Nair, A.P. Vinod, A.K. Krishna, A fast two stage detector for spectrum sensing in cognitive radios, in Proceedings of the IEEE Vehicular Technology Conference (VTC Fall), San Francisco, CA, 5–8 Sept 2011, pp. 1–5

    Google Scholar 

  24. P.R. Nair, AP Vinod, A.K. Krishna, An adaptive threshold based energy detector for spectrum sensing in cognitive radios at low SNR, in Proceedings of the IEEE International Conference on Communication Systems (ICCS, 2010), pp. 574–578

    Google Scholar 

  25. T.C. Clancy, On the use of interference temperature for dynamic spectrum access. Ann. Telecommun. 64(7), 573–585 (2009)

    Article  Google Scholar 

  26. R. Tandra, A. Sahai, SNR walls for signal detection. IEEE J. Sel. Top. Signal Process. 2(1), 4–17 (2008)

    Article  Google Scholar 

  27. D.J. Torrieri, Principles of Military Communication Systems (Artech, Dedham, MA, 1981)

    Google Scholar 

  28. J. Lehtomäki, Analysis of energy based signal detection, Ph.D. thesis, Faculty of Technology, University of Oulu, 2005

    Google Scholar 

  29. A. Ghasemi, E.S. Sousa, Opportunistic spectrum access in fading channels through collaborative sensing. J. Commun. 2(2), 71–82 (2007)

    Article  Google Scholar 

  30. J. Ma, Y. Li, Soft combination and detection for cooperative spectrum sensing in cognitive radio networks, in Proceedings of the IEEE Global Communications Conference (GLOBECOM), 26–30 Nov 2007, pp. 3139–3143

    Google Scholar 

  31. H. Kim, K.G. Shin, In-band spectrum sensing in cognitive radio networks: energy detection or feature detection? in Proceedings of the 14th ACM International Conference on Mobile Computing and Networking (MobiCom), 14–19 Sept 2008, pp. 14–25

    Google Scholar 

  32. J.J. Lehtomäki, M. Juntti, H. Saarnisaari, CFAR strategiesor channelized radiometer. IEEE Signal Process. Lett. 12(1), 13–16 (2005)

    Google Scholar 

  33. V.I. Kostylev, Energy detection of a signal with random amplitude, in Proceedings of the IEEE International Conference on Communications (ICC), vol 3, 28 Apr–2 May 2002, pp. 1606–1610

    Google Scholar 

  34. F.F. Digham, M.-S. Alouini, M.K. Simon, On the energy detection of unknown signals over fading channels, in IEEE International Conference on Communications (ICC), vol 5, 11–15 May 2003, pp. 3575–3579

    Google Scholar 

  35. A. Ghasemi, E.S. Sousa, Impact of user collaboration on the performance of sensing based opportunistic spectrum access, in Proceedings of the 64th IEEE Vehicular Technology Conference (VTC-2006 Fall), 25–28 Sept 2006, pp. 1–6

    Google Scholar 

  36. D. Cabric, A. Tkachenko, R. Brodersen, Spectrum sensing measurements of pilot, energy, and collaborative detection, in Proceedings of the Military Communications Conference (MILCOM), 23–25 Oct 2006, pp. 1–7

    Google Scholar 

  37. D. Cabric, Addressing the feasibility of cognitive radios. IEEE Signal Process. Mag. 25(6), 85–93 (2008)

    Article  Google Scholar 

  38. Z. Xuping, P. Jianguo, Energy-detection based spectrum sensing for cognitive radio”, in Proceedings of the IET Conference on Wireless, Mobile and Sensor Networks (CCWMSN07), Shanghai, 12–14 Dec 2007, pp. 944–947

    Google Scholar 

  39. H.V. Trees, Detection, Estimation, and Modulation Theory (Wiley, New York, 1968)

    MATH  Google Scholar 

  40. R. Tandra, A. Sahai, Fundamental limits on detection in low SNR under noise uncertainty, in Proceedings of the Wireless Communication, June 2005, pp. 464–469

    Google Scholar 

  41. M.P. Olivieri, G. Barnett, A. Lackpour, A. Davis, A scalable dynamic spectrum allocation system with interference mitigation for teams of spectrally agile software defined radios, in Proceedings of the IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN), Baltimore, MD, Nov 2005, pp. 170–179

    Google Scholar 

  42. F. Weidling, D. Datla, V. Petty, P. Krishnan, G. Minden, A framework for RF spectrum measurements and analysis, in Proceedings of the IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN), Baltimore, MD, Nov 2005, pp. 573–576

    Google Scholar 

  43. D.-C. Oh, Y.-H. Lee, Energy detection based spectrum sensing for sensing error minimization in cognitive radio networks. Int. J. Commun. Netw. Inf. Secur. 1(1) (2009)

    Google Scholar 

  44. J. Lehtomaki, J. Vartiainen, M. Juntti, H. Saarnisaari, Spectrum sensing with forward methods, in Proceedings of the IEEE Military Communication Conference, Washington, D.C., Oct 2006, pp. 1–7

    Google Scholar 

  45. J. Vartiainen, H. Sarvanko, J. Lehtomki, M. Juntti, M. Latva-aho, Spectrum sensing with LAD-based methods, in Proceedings of the 18th Annual IEEE International Symposium on Personal, Indoor, Mobile Radio Communication (PIMRC) 2007, pp. 1–5

    Google Scholar 

  46. Y.-C. Liang, E.P.Y. Zeng, A.T. Hoang, Sensing-throughput tradeoff for cognitive radio networks, in Proceedings of the IEEE International Conference on Communication (ICC), Glasgow, UK, June 2007, pp. 5330–5335

    Google Scholar 

  47. Z. Quan, S. Cui, A.H. Sayed, H.V. Poor, Wideband spectrum sensing in cognitive radio networks, in Proceedings of the IEEE International Conference on Communication, Beijing, China, May 2008, pp. 901–906

    Google Scholar 

  48. M. Wylie-Green, Dynamic spectrum sensing by multiband OFDM radio for interference mitigation, in Proceedings of the 1st IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN), 2005, pp. 619–625

    Google Scholar 

  49. S. Kapoor, S.V.R.K. Rao, G. Singh, Opportunistic spectrum sensing by employing matched filter in cognitive radio network, in Proceedings of the IEEE International Conference on Communication Systems and Network Technologies (CSNT), 2011, India, pp. 580–583

    Google Scholar 

  50. J. Ma, G.Y. Li, B.H. Juang, Signal processing in cognitive radio. Proc. IEEE 97(5), 805–823 (2009)

    Article  Google Scholar 

  51. L. Lu, X. Zhou, U. Onunkwo, G.Y. Li, Ten years of research in spectrum sensing and sharing in cognitive radio. EURASIP J. Wireless Commun. Netw. 2012(1), 28 (2012)

    Article  Google Scholar 

  52. D. Cabric, A. Tkachenko, R.W. Brodersen, Spectrum sensing measurements of pilot, energy, and collaborative detection, in Proceedings of the Military Communications Conference (MILCOM), 2006, pp. 1–7

    Google Scholar 

  53. S. Kapoor, G Singh, Non-cooperative spectrum sensing: a hybrid model approach, in Proceedings of International Conference on Devices and Communications (ICDeCom), 2011, India, pp. 1–5

    Google Scholar 

  54. S.M. Kay, Fundamentals of Statistical Signal Processing, 5th edn. (Prentice Hall, 2004), pp. 487–488

    Google Scholar 

  55. K. Muraoka, M. Ariyoshi, T. Fujii, A novel spectrum-sensing method based on maximum cyclic autocorrelation selection for cognitive radio system, in Proceedings of the 3rd IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySpan), 2008, pp. 1–7

    Google Scholar 

  56. R. Tandra, A. Sahai, Noise calibration, delay coherence and SNR walls for signal detection, in Proceedings of the 3rd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (2008), pp. 1–11

    Google Scholar 

  57. M. Öner, F. Jondral, Air interface recognition for a software radio system exploiting cyclostationarity, in Proceedings of the 15th IEEE International Symposium on Personal, Indoor, Mobile Radio Communication (PIMRC), vol 3 (2004), pp. 1947–1951

    Google Scholar 

  58. A. Fehske, J.D. Gaeddert, J.H. Reed, A new approach to signal classification using spectral correlation and neural networks, in Proceedings of the IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN), Baltimore, MD, Nov 2005, pp. 144–150

    Google Scholar 

  59. A. Ghasemi, E.S. Sousa, Spectrum sensing in cognitive radio networks: requirements, challenges and design trade-offs. IEEE Commun. Mag. 46(4), 32–39 (2008)

    Article  Google Scholar 

  60. W.A. Gardner, Signal interception: performance advantages of cyclic-feature detectors. IEEE Trans. Commun. 40, 149–159 (1992)

    Article  MATH  Google Scholar 

  61. A. Sahai, N. Hoven, R. Tandra, Some fundamental limits on cognitive radio, in Allerton Conference on Communication, Control, and Computing (2004), pp. 1662–1671

    Google Scholar 

  62. D. Cabric, Addressing feasibility of cognitive radios. IEEE Signal Process. Mag. 25(6), 85–93 (2008)

    Article  Google Scholar 

  63. T. Yücek, H. Arslan, Spectrum characterization for opportunistic cognitive radio systems, in Proceedings of the IEEE Military Communication Conference (2006), pp. 1–6

    Google Scholar 

  64. D. Cabric, R.W. Brodersen, Physical layer design issues unique to cognitive radio systems, in Proceedings of the IEEE 16th International Symposium on Personal, Indoor, Mobile Radio Communication (PIMRC), vol 2 (2005), pp. 759–763

    Google Scholar 

  65. N. Shankar, C. Cordeiro, K. Challapali, Spectrum agile radios: utilization and sensing architectures, in Proceedings of the 1st IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN) (2005), pp. 160–169

    Google Scholar 

  66. J. Lunden, V. Koivunen, A. Huttunen, H. Poor, Spectrum sensing in cognitive radios based on multiple cyclic frequencies, in Proceedings of the 2nd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom) (2007), pp. 37–43

    Google Scholar 

  67. L.P. Goh, Z. Lei, F. Chin, Feature detector for DVB-T signal in multipath fading channel, in Proceedings of the 2nd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom), 2007

    Google Scholar 

  68. G. Vardoulias, J. Faroughi-Esfahani, G. Clemo, R. Haines, Blind radio access technology discovery and monitoring for software defined radio communication systems: Problems and techniques, in Proceedings of the 2nd International Conference on 3G Mobile Communication Technology (2001), pp. 306–310

    Google Scholar 

  69. M. Mehta, N. Drew, G. Vardoulias, N. Greco, C. Niedermeier, Reconfigurable terminals: an overview of architectural solutions. IEEE Commun. Mag. 39(8), 82–89 (2001)

    Article  Google Scholar 

  70. R. Chen, J. Park, Ensuring trustworthy spectrum sensing in cognitive radio networks, in Proceedings of the 1st IEEE Workshops on Networking Technologies for Software Defined Radio (SDR) Networks (2006), pp. 110–119

    Google Scholar 

  71. P.K. Varshney, C.S. Burrus, Distributed Detection and Data Fusion (Springer, New York, 1997)

    Book  Google Scholar 

  72. D. Cabric, S.M. Mishra, Robert W. Brodersen, Implementation issues in spectrum sensing for cognitive radios, in Proceedings of Asilomar Conference on Signals, Systems, and Computers, vol 1 (2004), pp. 772–776

    Google Scholar 

  73. G. Ganesan, Ye Li, Cooperative spectrum sensing in cognitive radio, part I: two user networks. IEEE Trans. Wireless Commun. 6(6), 2204–2213 (2007)

    Article  Google Scholar 

  74. G. Ganesan, Ye Li, Cooperative spectrum sensing in cognitive radio, part II: multiuser networks. IEEE Trans. Wireless Commun. 6(6), 2214–2222 (2007)

    Article  Google Scholar 

  75. R. Peterson, E. Visotsky, S. Kuffner, On collaborative detection of tv transmissions in support of dynamic spectrum sharing, in Proceedings of the 1st International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN 2005), 2005, pp. 338–345

    Google Scholar 

  76. A. Dobra, D. Kempe, J. Gehrke, Gossip-based computation of aggregate information, in Proceeding of IEEE Symposium on Foundations of Computer Science (FOC), Oct 2003, pp. 482–491

    Google Scholar 

  77. D.N.C. Tse, J.N. Laneman, G.W. Wornell, Cooperative diversity in wireless networks: efficient protocols and outage behavior. IEEE Trans. Inf. Theory 50(12), 3062–3080 (2004)

    Google Scholar 

  78. J. Hillenbrand, T. Weiss, F.K. Jondral, Calculation of detection and false alarm probabilities in spectrum pooling systems. IEEE Commun. Lett. 9(4), 349–351 (2005)

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

  81. G. Amir, S.S. Elvino, Spectrum sensing in cognitive radio networks: the cooperation-processing tradeoff. Wireless Commun. Mobile Comput. 7(9), 1049–1060 (2007)

    Article  Google Scholar 

  82. G. Scutari, D. Palomar, S. Barbarossa, Cognitive MIMO radio. IEEE Signal Process. Mag. 25(6), 46–59 (2008)

    Article  MATH  Google Scholar 

  83. W. Zhang, K.B. Letaief, Cooperative spectrum sensing with transmit and relay diversity in cognitive radio networks. IEEE Trans. Wireless Commun. 7(12), 4761–4766 (2008)

    Article  Google Scholar 

  84. K.B. Letaief, W. Zhang, Cooperative communications for cognitive radio networks. Proc. IEEE 97(5), 878–893 (2009)

    Article  Google Scholar 

  85. R. Viswanathan, V. Aalo, On counting rules in distributed detection. IEEE Trans. Acoust. Speech Signal Process. 37(5), 772–775 (1989)

    Article  Google Scholar 

  86. G. Ganesan, Y.G. Li, Agility improvement through cooperation diversity in cognitive radio, in Proceedings of the IEEE Global Communications Conference, St Louis, Missouri, USA, 28 Nov–2 Dec 2005, vol 5, pp. 2505–2509

    Google Scholar 

  87. Y.C. Liang, Y.H. Zeng, E.C.Y. Peh, Anh Tuan Hoang, Sensing-throughput tradeoff for cognitive radio networks. IEEE Trans. Wireless Commun. 7(4), 1326–1337 (2008)

    Article  Google Scholar 

  88. J.Y. Shen, T. Jiang, S.Y. Liu, Zhongshan Zhang, Maximum channel throughput via cooperative spectrum sensing in cognitive radio networks. IEEE Trans. Wireless Commun. 8(10), 5166–5175 (2009)

    Article  Google Scholar 

  89. E.C.Y. Peh, Y.C. Liang, Y.L. Guan, Yonghong Zeng, Optimization of cooperative spectrum sensing in cognitive radio networks: a sensing-throughput tradeoff view. IEEE Trans. Veh. Technol. 58(9), 5294–5299 (2009)

    Article  Google Scholar 

  90. Y.H. Zeng, Y.C. Liang, Spectrum-sensing algorithms for cognitive radio based on statistical covariances. IEEE Trans. Veh. Technol. 58(4), 1804–1815 (2009)

    Article  Google Scholar 

  91. W. Saad, Z. Han, M. Debbah, A. Hjorungnes, T. Basar, Coalitional games for distributed collaborative spectrum sensing in cognitive radio networks. Proc. IEEE INFOCOM 2009, 2114–2122 (2009)

    Google Scholar 

  92. B. Wang, K. Ray Liu, T. Clancy, Evolutionary cooperative spectrum sensing game: how to collaborate? IEEE Trans. Commun. 58(3), 890–900 (2010)

    Google Scholar 

  93. I.F. Akyildiz, W.-Y. Lee, M.C. Vuran, S. Mohanty, NeXt generation/dynamic spectrum access/cognitive radio wireless networks: a survey. Comput. Netw. 50(13), 2127–2159 (2006)

    Article  MATH  Google Scholar 

  94. B.F. Lo, I.F. Akyildiz, A.M. Al-Dhelaan, Efficient recovery control channel design in cognitive radio ad hoc networks. IEEE Trans. Veh. Technol. 59(9), 4513–4526 (2010)

    Article  Google Scholar 

  95. R. Blum, S. Kassam, H. Poor, Distributed detection with multiple sensors I. Advanced topics. Proc. IEEE 85(1), 64–79 (1997)

    Article  Google Scholar 

  96. FCC, Second memorandum opinion and order, ET Docket No. 10-174

    Google Scholar 

  97. M. Armbrust, A. Fox, R. Griffith, A.D. Joseph, R. Katz, A. Konwinski, G. Lee, D. Patterson, A. Rabkin, I. Stoica, M. Zaharia, A view of cloud computing. Commun. ACM 53, 50–58 (2010)

    Article  Google Scholar 

  98. V. Namboodiri, Towards sustainability in portable computing through cloud computing and cognitive radios” in Proceedings of 39th International Conference on Parallel Processing Workshops (ICPPW 2010), 2010, pp. 468–475

    Google Scholar 

  99. Y. Xing, C.N. Mathur, M. Haleem, R. Chandramouli, K. Subbalakshmi, Dynamic spectrum access with QoS and interference temperature constraints. IEEE Trans. Mobile Comput. 6(4), 423–433 (2007)

    Article  Google Scholar 

  100. J. Bater, H.P. Tan, K.N Brown, L. Doyle, Modelling interference temperature constraints for spectrum access in cognitive radio networks, in Proceeding of IEEE International Conference on Communications, ICC’07, June 2007, pp. 6493–6498

    Google Scholar 

  101. Establishement of interference temperature metric to quantify and manage interference and to expand available unlicensed operation in certain fixed mobile and satellite frequency bands, FCC, 2003, FCC Doc. ET Docket 03-289

    Google Scholar 

  102. P.J. Kolodzy, Interference temperature: a metric for dynamic spectrum utilization. Int. J. Netw. Manag. 16(2), 103–113 (2006)

    Article  Google Scholar 

  103. T.C. Clancy, Formalizing the interference temperature model. J. Wireless Commun. Mobile Comput. 7(9), 1077–1086 (2007)

    Article  Google Scholar 

  104. A. Wagstaff, N. Merricks, A subspace-based method for spectrum sensing, in Proceedings of SDR Forum Technical Conference (2007)

    Google Scholar 

  105. Z. Ye, G. Memik, J. Grosspietsch, Energy detection using estimated noise variance for spectrum sensing in cognitive radio networks, in Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC 2008), 2008, pp. 711–716

    Google Scholar 

  106. D.R. Joshi et al., Gradient-based threshold adaptation for energy detector in cognitive radio systems. IEEE Commun. Lett. 15(1), 19–21 (2011)

    Article  Google Scholar 

  107. X. Zhai, H. He, G. Zheng, Optimal threshold and weighted cooperative data combining rule in cognitive radio network, in Proceedings of the 12th IEEE International Conference on Communication Technology (ICCT), 2010, pp. 1464–1467

    Google Scholar 

  108. Y.M. Maatug, Spectrum sensing in cognitive radio: multi-detection techniques, MS dissertation, University of Waterloo, Ontario, Canada, 2012

    Google Scholar 

  109. S. Haykin, Cognitive radio: brain-empowered wireless communications. IEEE J. Sel. Areas Commun. 23(2), 201–220 (2005)

    Article  Google Scholar 

  110. H. Arslan, Cognitive Radio, Software Defined Radio, and Adaptive Wireless Systems (Springer, Berlin, 2007)

    Google Scholar 

  111. S. Xie, Y. Liu, Y. Zhang, R. Yu, A parallel cooperative spectrum sensing in cognitive radio networks. IEEE Trans. Veh. Technol. 59(8), 4079–4092 (2010)

    Article  Google Scholar 

  112. T.C. Clancy, N. Goergen, Security in cognitive radio networks: threats and mitigation, in Proceedings of the 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom 2008), Singapore, 15–17 May 2008, pp. 1–8

    Google Scholar 

  113. A. Fragkiadakis, E. Tragos, I. Askoxylakis, A survey on security threats and detection techniques in cognitive radio networks. IEEE Commun. Surv. Tutorials 15(1), 428–445 (2013)

    Article  Google Scholar 

  114. J.L. Burbank, Security in cognitive radio networks: the required evolution in approaches to wireless network security, in Proceedings of the 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom 2008), Singapore, 15–17 May 2008, pp. 1–7

    Google Scholar 

  115. H. Jiang, L. Lai, R. Fan, H. Poor, Optimal selection of channel sensing order in cognitive radio. IEEE Trans. Wireless Commun. 8(1), 297–307 (2009)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Jaypee University of Information Technology, Solan, Himachal Pradesh, India

    Shweta Pandit

  2. Department of Electronics and Communication Engineering, Jaypee University of Information Technology, Solan, Himachal Pradesh, India

    Ghanshyam Singh

Authors
  1. Shweta Pandit
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ghanshyam Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shweta Pandit .

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this chapter

Cite this chapter

Pandit, S., Singh, G. (2017). Spectrum Sensing in Cognitive Radio Networks: Potential Challenges and Future Perspective. In: Spectrum Sharing in Cognitive Radio Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-53147-2_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-53147-2_2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-53146-5

  • Online ISBN: 978-3-319-53147-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation