Abstract
Cognitive Radio Network (CRN) is an intelligent wireless communication system that adapts itself to variations in the incoming radio frequency stimuli by modifying the operating parameters. Using the spectrum sensing techniques, the idle channels are detected, and allocated to the Secondary Users (SUs). The existing cooperative spectrum sensing techniques such as centralized sensing technique, Distributed sensing technique, and External sensing technique exploit efficient prediction models for allocating the frequency spectrum to SUs. For an optimal assignment of the channel using channel parameters, the channel estimation techniques such as pilot-assisted channel estimation, blind and semi blind estimation technique, and decision directed channel estimation technique are analyzed. The flexible nature of the CRN introduces various security attacks such as Primary User Emulation Attack, Objective Function Attack, Jamming Attack, Spectrum Sensing Data Falsification (SSDF), Control Channel Saturation DoS Attack (CCSD), Selfish Channel Negotiation (SCN), Sinkhole Attacks, HELLO Flood Attacks and Lion Attack. From the surveyed results, it is observed that the existing spectrum sensing, and prediction-based techniques consume more energy, and minimal data transmission rate for detecting the idle channel. Further, the end-to-end delay, energy consumption, end-to-end delay, and bandwidth are not minimized by the existing techniques.
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References
Report of the Spectrum Efficiency Working Group, Federal Communications Commission, Spectrum Policy Task Force, 2002.
Tong, L., Sadler, B.M., and Dong, M., Pilot assisted wireless transmissions: General Model, Design Criteria, and Signal Processing, IEEE Signal Process. Mag., 2004, vol. 21, no. 6, pp. 12–25.
Adireddy, S., Tong, L., and Viswanathan, H., Optimal placement of training for frequency-selective block-fading channels, IEEE Trans. Inf. Theory, 2002, vol. 48, pp. 2338–2353.
Hassibi, B. and Hochwald, B.M., How much training is needed in multiple-antenna wireless links? IEEE Trans. Inf. Theory, 2003, vol. 49, pp. 951–963.
Petropulu, A., Zhang, R., and Lin, R., Blind OFDM channel estimation through simple linear precoding, IEEE Trans. Wireless Commun., 2004, vol. 3, pp. 647–655.
Li, Y., Simplified channel estimation for OFDM systems with multiple transmit antennas, IEEE Trans. Wireless Commun., 2002, vol. 1, pp. 67–75.
Li, Y., Winters, J.H., and Sollenberger, N.R., MIMO-OFDM for wireless communications: Signal detection with enhanced channel estimation, IEEE Trans. Commun., 2002, vol. 50, pp. 1471–1477.
Aktman, J. and Hanzo, L., Decision directed channel estimation employing approximation subspace tracking, Proc. Spring, 2007, vol. 5, pp. 3056–3060.
Renzo, M., Imbriglio, L., Graziosi, F., and Santucci, F., Distributed data fusion over correlated log-normal sensing and reporting channels: Application to cognitive radio networks, IEEE Trans. Wireless Commun., 2008, vol. 8, pp. 5813–5821.
Olivieri, M.P., Barnett, G., Lackpour, A., Davis, A., and Ngo, P., A scalable dynamic spectrum allocation system with interference mitigation for teams of spectrally agile software defined radios, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005, pp. 170–179.
Weidling, F., Datla, D., Petty, V., Krishnan, P., and Minden, G., A framework for RFspectrum measurements and analysis, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005.
Oh, D.-C. and Lee, Y.-H., Energy detection based spectrum sensing for sensing error minimization in cognitive radio networks, International Journal of Communication Networks and Information Security (IJCNIS), 2009, vol.1.
Lehtomäki, J.J., Vartiainen, J., Juntti, M., and Saarnisaari, H., Spectrum sensing with forward methods, IEEE Military Communications Conference, 2006, pp. 1–7.
Vartiainen, J., Sarvanko, H., and Lehtomäki, J., Juntti, M., and Latva-Aho, M., Spectrum sensing with LADbased methods, IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications, 2007, pp. 1–5.
Liang, Y.-C., Zeng, Y., Peh, E.C., and Hoang, A.T., Sensing-throughput tradeoff for cognitive radio networks, IEEE Trans. Wireless Commun., 2008, vol. 7, pp. 1326–1337.
Quan, Z., Cui, S., Sayed, A.H., and Poor, H.V., Wideband spectrum sensing in cognitive radio networks, IEEE International Conference on Communications, 2008, pp. 901–906.
Akyildiz, I.F., Lo, B.F., and Balakrishnan, R., Cooperative spectrum sensing in cognitive radio networks: A survey, Phys. Commun., 2011, vol. 4, pp. 40–62.
Yücek, T. and Arslan, H., Spectrum characterization for opportunistic cognitive radio systems, IEEE Military Communications Conference, 2006, pp. 1–6.
Čabrić, D. and Brodersen, R.W., Physical layer design issues unique to cognitive radio systems, IEEE 16th International Symposium on Personal, Indoor and Mobile Radio Communications, 2005, pp. 759–763.
Muraoka, K., Ariyoshi, M., and Fujii, T., A novel spectrum-sensing method based on maximum cyclic autocorrelation selection for cognitive radio system, 3rd IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2008, pp. 1–7.
Cabric, D., Mishra, S.M., and Brodersen, R.W., Implementation issues in spectrum sensing for cognitive radios, Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004, pp. 772–776.
Sahai, A., Tandra, R., Mishra, S.M., and Hoven, N., Fundamental design tradeoffs in cognitive radio systems, Proceedings of the First International Workshop on Technology and Policy for Accessing Spectrum, 2006, p.2.
Zeng, Y. and Liang, Y.-C., Spectrum-sensing algorithms for cognitive radio based on statistical covariances, IEEE Trans. Veh. Technol., 2009, vol. 58, pp. 1804–1815.
Zeng, Y. and Liang, Y.-C., Covariance based signal detections for cognitive radio, 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2007, pp. 202–207.
Zeng, Y. and Liang, Y.-C., Maximum-minimum eigenvalue detection for cognitive radio, IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications, 2007, pp. 1–5.
Farhang-Boroujeny, B., Filter bank spectrum sensing for cognitive radios, IEEE Trans. Signal Process., 2008, vol. 56, pp. 1801–1811.
Haykin, S., Cognitive radio: Brain-empowered wireless communications, IEEE J. Sel. Areas Commun., 2005, vol. 23, pp. 201–220.
Li, H., Li, C., and Dai, H., Quickest spectrum sensing in cognitive radio, 42nd Annual Conference on Information Sciences and Systems, 2008, pp. 203–208.
Kim, H. and Shin, K.G., Fast discovery of spectrum opportunities in cognitive radio networks, 3rd IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2008, pp. 1–12.
Berthold, U., Fu, F., Van der Schaar, M., and Jondral, F.K., Detection of spectral resources in cognitive radios using reinforcement learning, 3rd IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2008, pp. 1–5.
Wang, X., Ho, P.-H., and Wong, A., Towards efficient spectrum sensing for cognitive radio through knowledgebased reasoning, 3rd IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2008, pp. 1–8.
Anand, S., Jin, Z., and Subbalakshmi, K., An analytical model for primary user emulation attacks in cognitive radio networks, 3rd IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2008, pp. 1–6.
Mathur, C.N. and Subbalakshmi, K., Security issues in cognitive radio networks, in Cognitive Networks: Towards Self-Aware Networks, 2007, pp. 284–293.
Clancy, T.C. and Goergen, N., Security in cognitive radio networks: Threats and mitigation, 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications, 2008, pp. 1–8.
Hu, Y.-C., Johnson, D.B., and Perrig, A., SEAD: Secure efficient distance vector routing for mobile wireless ad hoc networks, Ad Hoc Networks, 2003, vol. 1, pp. 175–192.
Qi, C., Yue, G., Wu, L., and Nallanathan, A., Pilot design for sparse channel estimation in OFDM-based cognitive radio systems, IEEE Trans. Veh. Technol., 2014, vol. 63, pp. 982–987.
Ikki, S.S., Al-Dharrab, S., and Uysal, M., Error probability of D Frelaying with pilot-assisted channel estimation over time-varying fading channels, IEEE Trans. Veh. Technol., 2012, vol. 61, pp. 393–397.
Chenhao, Q., Lenan, W., Yongming, H., and Nallanathan, A., Joint design of pilot power and pilot pattern for sparse cognitive radio systems, IEEE Trans. Veh. Technol., 2015, vol. 64, pp. 5384–5390.
Pandey, D. and Dewangan, N., Performance analysis of pilot assisted channel estimation in OFDM, International Conference on Computer, Communication and Control (IC4), 2015, pp. 1–6.
Zhang, P., Chen, S., and Hanzo, L., Embedded iterative semi-blind channel estimation for three-stage-concatenated MIMO-Aided QAM turbo transceivers, IEEE Trans. Veh. Technol., 2014, vol. 63, pp. 439–446.
Shebl, S., Shokair, M., and Gomaa, A., Novel semi-blind spectrum sensing in cognitive radio networks with fourth-order statistics, Wireless Pers. Commun., 2015, vol. 82, pp. 2097–2113.
Chenglin Zhao, M.S., Bin Li, Long Zhao, and Xiao Peng, Blind spectrum sensing for cognitive radio over timevariant multipath flat-fading channels, EURASIP J. Wireless Commun. Networking, 2014, vol. 84, pp. 1–13.
Ying-Chang Liang, Kwang-Cheng Chen, Ye Li, G., and Mähönen, P., Cognitive radio networking and communications: An overview, IEEE Trans. Veh. Technol., 2011, vol. 60, pp. 3386–3407.
Ozden, M.T., Adaptive reconfigurable V-BLAST type equalizer for cognitive MIMO-OFDM radios, EURASIP J. Adv. Signal Process., 2015, vol. 8, pp. 1–27.
Chen, B.-S., Chang-Yi, Y., and Wei-Ji, L., Robust fast time-varying multipath fading channel estimation and equalization for MIMO-OFDM systems via a fuzzy method, IEEE Trans. Veh. Technol., 2012, vol. 61, pp. 1599–1609.
Shakhakarmi, N., Secured distributed cognitive MAC and complexity reduction in channel estimation for the cross layer based cognitive radio networks, Int. J. Comput. Sci. Issues, 2012, vol. 9, pp. 477–486.
Wu, K.-G. and Wu, J.-A., Reduced-complexity decision-directed channel estimation in OFDM systems with transmit diversity, Wireless Pers. Commun., 2013, vol. 68, pp. 175–185.
Fangwei, L., Fan, L., Jiang, Z., and Yifang, N., Reputation-based secure spectrum situation fusion in distributed cognitive radio networks, J. China Univ. Posts Telecommun., 2015, vol. 22, no. 6, pp. 110–117.
Ozbay, S. and Ercelebi, E., A new wireless network scheme for spectrum sensing in cognitive radio, Elektron. Elektrotech., 2015, vol. 21, pp. 90–95.
Sharifi, A.A., Sharifi, M., and Niya, M.J.M., Secure cooperative spectrum sensing under primary user emulation attack in cognitive radio networks: Attack-aware threshold selection approach, AEU, Int. J. Electron. Commun., 2016, vol. 70, pp. 95–104.
Sang Hyun, L., Shamaiah, M., Vikalo, H., and Vishwanath, S., Message-passing algorithms for coordinated spectrum sensing in cognitive radio networks, IEEE Commun. Lett., 2013, vol. 17, pp. 812–815.
Ansari, J., Zhang, X., and Mähönen, P., A decentralized MAC protocol for opportunistic spectrum access in cognitive wireless networks, Comput. Commun., 2013, vol. 36, pp. 1399–1410.
Banaei, A., Eslami, A., Georghiades, C.N., and Shuguang, C., Joint random spectrum sensing and access scheme for decentralized cognitive radio networks, IEEE International Conference on Communications (ICC), 2014, pp. 1391–1396.
Kaigui, B. and Jung-Min, P., Maximizing rendezvous diversity in rendezvous protocols for decentralized cognitive radio networks, IEEE Trans. Mobile Comput., 2013, vol. 12, pp. 1294–1307.
Zandi, M. and Dong, M., Distributed opportunistic spectrum access with unknown population, 1st IEEE International Conference on Communications in China (ICCC), 2012, pp. 405–410.
Hawa, M., Darabkh, K.A., Khalaf, L.D., and Rahhal, J.S., Dynamic resource allocation using load estimation in distributed cognitive radio systems, AEU, Int. J. Electron. Commun., 2015, vol. 69, no. 12, pp. 1833–1846.
Dikmese, S., Sofotasios, P.C., Ihalainen, T., Renfors, M., and Valkama, M., Efficient energy detection methods for spectrum sensing under non-flat spectral characteristics, IEEE J. Sel. Areas Commun., 2015, vol. 33, pp. 755–770.
Mariani, A., Kandeepan, S., and Giorgetti, A., Periodic spectrum sensing with non-continuous primary user transmissions, IEEE Trans. Wireless Commun., 2015, vol. 14, pp. 1636–1649.
Ejaz, W., Shah, G.A., and Kim, H.S., Energy and throughput efficient cooperative spectrum sensing in cognitive radio sensor networks, Trans. Emerging Telecommun. Technol., 2015, vol. 26, pp. 1019–1030.
Vadivelu, K.S.R. and Vijayakumari, V., Matched filter based spectrum sensing for cognitive radio at low signal to noise ratio, J. Theor. Appl. Inf. Technol., 2014, vol.62.
Shobana, R.S.S. and Muthaiah, R., Matched filter based spectrum sensing on cognitive radio for OFDM WLANs, Int. J. Eng. Technol., 2013, vol. 5, pp. 142–146.
Divya Joshi, Neeru Sharma, and Jaskirat Singh, Spectrum sensing for cognitive radio using hybrid matched filter single cycle cyclostationary feature detector, Int. J. Inf. Eng. Electron. Bus., 2015, vol.7.
Yang Liu, Z.Z., Gongpu Wang, and Dan Hu, Cyclostationary detection based spectrum sensing for cognitive radio networks, J. Commun., 2015, vol. 10, pp. 74–79.
Jayanta Mishra, D.K.B. and Manoj Kumar Swain, Ch., Cyclostationary based spectrum sensing in cognitive radio: Windowing approach, Int. J. Recent Technol. Eng., 2014, vol. 3, pp. 95–100.
Axell, E., Leus, G., Larsson, E.G., and Poor, H.V., Spectrum sensing for cognitive radio: State-of-the-art and recent advances, IEEE Signal Process. Mag., 2012, vol. 29, pp. 101–116.
Ekin, E., Abdallah, M.M., Qaraqe, K.A., and Serpedin, E., Random subcarrier allocation in OFDM-based cognitive radio networks, IEEE Trans. Signal Process., 2012, vol. 60, pp. 4758–4774.
Zhaolong Ning, Yao Yu, Qingyang Song, Yuhuai Peng, and Bo Zhang, Interference-aware spectrum sensing mechanisms in cognitive radio networks, Comput. Electr. Eng., 2015, vol. 42, pp. 193–206.
Ruiliang, C., Jung-Min, P., and Reed, J.H., Defense against primary user emulation attacks in cognitive radio networks, IEEE J. Sel. Areas Commun., 2008, vol. 26, pp. 25–37.
Xie, X. and Wang, W., Detecting primary user emulation attacks in cognitive radio networks via physical layer network coding, Procedia Comput. Sci., 2013, vol. 21, pp. 430–435.
Reddy, Y.B., Security issues and threats in cognitive radio networks, The Ninth Advanced International Conference on Telecommunications, 2013, pp. 85–90.
Pei, Q., Li, H., Ma, J., Fan, K., Defense against objective function attacks in cognitive radio networks, Chin. J. Electron., 2011, vol. 20, pp. 138–142.
Fadlullah, Z.M., Nishiyama, H., Kato, N., and Fouda, M.M., Intrusion detection system (IDS) for combating attacks against cognitive radio networks, IEEE Network, 2013, vol. 27, pp. 51–56.
Di Pietro, R. and Oligeri, G., Jamming mitigation in cognitive radio networks, IEEE Network, 2013, vol. 27, pp. 10–15.
Bhunia, S., Sengupta, S., and Vázquez-Abad, F., CR-Honeynet: A Learning & Decoy based sustenance mechanism against jamming attack in CRN, IEEE Military Communications Conference, 2014, pp. 1173–1180.
Chen, R., Park, J.-M., and Bian, K., Robust distributed spectrum sensing in cognitive radio networks, IEEE 27th Conference on Computer Communications, 2008.
Farmani, F., Jannat-Abad, M.A., and Berangi, R., Detection of SSDF attack using SVDD algorithm in cognitive radio networks, Third International Conference on Computational Intelligence, Communication Systems and Networks (CICSyN), 2011, pp. 201–204.
Wenkai, W., Husheng, L., Sun, Y.L., and Zhu, H., Attack-proof collaborative spectrum sensing in cognitive radio networks, 43rd Annual Conference on Information Sciences and Systems, 2009, pp. 130–134.
Clancy, T.C. and Goergen, N., Security in cognitive radio networks: Threats and mitigation, International Conference on Cognitive Radio Oriented Wireless Networks and Communications, 2008, pp. 1–8.
Karlof, C. and Wagner, D., Secure routing in wireless sensor networks: Attacks and countermeasures, Ad Hoc Networks, 2003, vol. 1, pp. 293–315.
Changlong, C., Min, S., and Hsieh, G., Intrusion detection of sinkhole attacks in large-scale wireless sensor networks, IEEE International Conference on Wireless Communications, Networking and Information Security (WCNIS), 2010, pp. 711–716.
Hernandez-Serrano, J., León, O., and Soriano, M., Modeling the lion attack in cognitive radio networks, EURASIP J. Wireless Commun. Networking, 2011, vol. 2011, pp.2.
Yan, G., Lv, Y., Wang, Q., and Geng, Y., Routing algorithm based on delay rate in wireless cognitive radio network, J. Networks, 2014, vol. 9, pp. 948–955.
Caleffi, M., Akyildiz, I.F., and Paura, L., OPERA: Optimal routing metric for cognitive radio ad hoc networks, IEEE Trans. Wireless Commun., 2012, vol. 11, pp. 2884–2894.
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Senthilkumar, S., Geetha Priya, C. A review of channel estimation and security techniques for CRNS. Aut. Control Comp. Sci. 50, 187–210 (2016). https://doi.org/10.3103/S0146411616030068
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DOI: https://doi.org/10.3103/S0146411616030068