Reliability Factors Based Fuzzy Logic Scheme for Spectrum Sensing
The accurate spectrum sensing is a fundamental requirement of dynamic spectrum access for deployment of Cognitive Radio Network (CRN). To acheive this requirement a Reliability factors based Fuzzy Logic (RFL) Scheme for Spectrum Sensing has been proposed in this paper. Cognitive Radio User (CRU) predicts the presence or absence of Primary User (PU) using energy detector and calculates the Reliability factors which are SNR of sensing node, threshold of energy detector and decision difference of each node with other nodes in a cooperative spectrum sensing environment. Then the decision of energy detector is combined with Reliability factors of sensing node using Fuzzy Logic. These Reliability Factors used in RFL Scheme describes the reliability of decision made by a CRU to improve the local spectrum sensing. This Fuzzy combining scheme provides the accuracy of decision made by sensornode. The simulation results have shown that the proposed technique provide better PU detection probability than existing Spectrum Sensing Techniques.
[1] Spectrum Policy Task Force Report, Technical report 02-135, Federal
communications comission, Nov. 2002.
[2] Hong-Sam T. Le and Hung D. Ly, Opportunistic Spectrum Access
Using Fuzzy Logic for Cognitive Radio Networks, Second International
Conference on Communications and Electronics, 2008.
[3] J. Ma, G. Li, B. H. Juang, Signal processing in cognitive radio,
Proceedings of IEEE, 2009.
[4] V. Stoianovici, V. Popescu, M. Murroni, A Survey on Spectrum Sensing
Techniques for Cognitive Radio, Journal Bulletin of the Transilvania
University of Brasov, 2008.
[5] Tevfik Yucek, Huseyin Arslan, A Survey of Spectrum Sensing
Algorithms for Cognitive Radio Applications, IEEE Communications
Surveys and Tutorials, 2009.
[6] J. Ma, G. Zhao, Y. Li, Soft Combination and Detection For Cooperative
Spectrum Sensing in Cognitive Radio Networks, IEEE Transactions on
Wireless Communications, 2008.
[7] S. Hussain X. Fernando, Approach for cluster-based spectrum sensing
over band-limited reporting channels, IET Communications Journal,
2011.
[8] Ejaz, W., Hasan, N., Azam, A. M and Kim, S. H, Improved local
spectrum sensing for cognitive radio networks, EURASIP Journal on
Advances in Signal Processing, 2012.
[9] Guanghua Zhang, Renshuang Ding, Lijing Huang, Using Trust
to Establish Cooperative Spectrum Sensing Framework, ELSEVIER
Journal Procedia Engineering, 2001.
[10] Dhope, T. S., Simunic, D., Cluster based cooperative sensing:-A
survey, International Conference on Communication, Information and
Computing Technology (ICCICT), 2012.
[11] D. Cabric, A. Tkachenko and R. W. Brodersen, Spectrum Sensing
measurements of pilot, energy, and collaborative detection, IEEE
MILCOM, 2007.
[12] Linda E. Doyle, Essentials of Cognitive Radio, Cambridge University
Press, pp 99-104, 2009.
[13] Anirudh M. Rao, B. R. Karthikeyan, Dipayan Mazumdar, Govind
R. Kadambi, Energy Detection Technique for Spectrum Sensing in
Cognitive Radio, SASTech - Technical Journal, 2010.
[14] Fadel F. Digham, M-S Alouini, Marvin K. Simon, On the Energy
Detection of Unknown Signals Over Fading Channels, Journal IEEE
Transactions on Communications, 2007. - Vol. 55.
[15] Tandra, R., S. and Anant, SNR Walls for Signal Detection, IEEE Journal
of Selected Topics in Signal Processing, 2008. - Vol. 2.
[16] B. Saklar, Digital Communications: Fundamentals and Applications,
Prentice Hall, Upper Saddle River 2nd edn, 2001.
[17] W. Yue, B. Zheng, Spectrum sensing algorithms for primary detection
based on reliability in cognitive radio systems, ELSEVIER Journal
Computers and Electrical Engineering, 2010.
[18] D. D. Ariananda, M. K. Lakshmanan, H. Nikookar, A Survey on
Spectrum Sensing Techniques for Cognitive Radio, Second International
Workshop on Cognitive Radio and Advanced Spectrum Management,
2009.
[19] L. A. Zadeh, Fuzzy Sets, Information and Control, vol.8 pp 338-353,
1965.
[20] C. C. Lee, Fuzzy Logic in Control Systems: Fuzzy Logic controller Part
II, IEEE Transactions on Systems, Man, and Cybernetics, 1990.
[21] M. Marja, R. Tapio, M. Miia, H. Ilkka, S. Heli, and A. Aarnem,
Application of Fuzzy Logic to Cognitive Radio Systems IEICE
Transections on Communication, 2009.
[22] J. Hou and D. C. OBrien, Vertical handover decision-making algorithm
using fuzzy logic for the integrated radio-and-OW system, Ieee
transection on Wireless Communication, 2006.
[23] Yi Zheng, Xianzhong Xie, Lili Yang, Cooperative Spectrum Sensing
Based on SNR Comparison in Fusion Center for Cognitive Radio,
International Conference on Advanced Computer Control, 2008.
[24] Yonghua Wang, Yuehong Li, Fei Yuan and Jian Yang, A Cooperative
Spectrum Sensing Scheme Based on Trust and Fuzzy Logic for
Cognitive Radio Sensor Networks, IJCSI International Journal of
Computer Science Issues, 2013.
[25] Ejaz, W., Hasan, N., Azam, A. M, Lee, S. and Kim, S. H, I3S:
Intelligent spectrum sensing scheme for cognitive radio networks,
EURASIP Journal on Wireless Communications and Networking, 2013.
[1] Spectrum Policy Task Force Report, Technical report 02-135, Federal
communications comission, Nov. 2002.
[2] Hong-Sam T. Le and Hung D. Ly, Opportunistic Spectrum Access
Using Fuzzy Logic for Cognitive Radio Networks, Second International
Conference on Communications and Electronics, 2008.
[3] J. Ma, G. Li, B. H. Juang, Signal processing in cognitive radio,
Proceedings of IEEE, 2009.
[4] V. Stoianovici, V. Popescu, M. Murroni, A Survey on Spectrum Sensing
Techniques for Cognitive Radio, Journal Bulletin of the Transilvania
University of Brasov, 2008.
[5] Tevfik Yucek, Huseyin Arslan, A Survey of Spectrum Sensing
Algorithms for Cognitive Radio Applications, IEEE Communications
Surveys and Tutorials, 2009.
[6] J. Ma, G. Zhao, Y. Li, Soft Combination and Detection For Cooperative
Spectrum Sensing in Cognitive Radio Networks, IEEE Transactions on
Wireless Communications, 2008.
[7] S. Hussain X. Fernando, Approach for cluster-based spectrum sensing
over band-limited reporting channels, IET Communications Journal,
2011.
[8] Ejaz, W., Hasan, N., Azam, A. M and Kim, S. H, Improved local
spectrum sensing for cognitive radio networks, EURASIP Journal on
Advances in Signal Processing, 2012.
[9] Guanghua Zhang, Renshuang Ding, Lijing Huang, Using Trust
to Establish Cooperative Spectrum Sensing Framework, ELSEVIER
Journal Procedia Engineering, 2001.
[10] Dhope, T. S., Simunic, D., Cluster based cooperative sensing:-A
survey, International Conference on Communication, Information and
Computing Technology (ICCICT), 2012.
[11] D. Cabric, A. Tkachenko and R. W. Brodersen, Spectrum Sensing
measurements of pilot, energy, and collaborative detection, IEEE
MILCOM, 2007.
[12] Linda E. Doyle, Essentials of Cognitive Radio, Cambridge University
Press, pp 99-104, 2009.
[13] Anirudh M. Rao, B. R. Karthikeyan, Dipayan Mazumdar, Govind
R. Kadambi, Energy Detection Technique for Spectrum Sensing in
Cognitive Radio, SASTech - Technical Journal, 2010.
[14] Fadel F. Digham, M-S Alouini, Marvin K. Simon, On the Energy
Detection of Unknown Signals Over Fading Channels, Journal IEEE
Transactions on Communications, 2007. - Vol. 55.
[15] Tandra, R., S. and Anant, SNR Walls for Signal Detection, IEEE Journal
of Selected Topics in Signal Processing, 2008. - Vol. 2.
[16] B. Saklar, Digital Communications: Fundamentals and Applications,
Prentice Hall, Upper Saddle River 2nd edn, 2001.
[17] W. Yue, B. Zheng, Spectrum sensing algorithms for primary detection
based on reliability in cognitive radio systems, ELSEVIER Journal
Computers and Electrical Engineering, 2010.
[18] D. D. Ariananda, M. K. Lakshmanan, H. Nikookar, A Survey on
Spectrum Sensing Techniques for Cognitive Radio, Second International
Workshop on Cognitive Radio and Advanced Spectrum Management,
2009.
[19] L. A. Zadeh, Fuzzy Sets, Information and Control, vol.8 pp 338-353,
1965.
[20] C. C. Lee, Fuzzy Logic in Control Systems: Fuzzy Logic controller Part
II, IEEE Transactions on Systems, Man, and Cybernetics, 1990.
[21] M. Marja, R. Tapio, M. Miia, H. Ilkka, S. Heli, and A. Aarnem,
Application of Fuzzy Logic to Cognitive Radio Systems IEICE
Transections on Communication, 2009.
[22] J. Hou and D. C. OBrien, Vertical handover decision-making algorithm
using fuzzy logic for the integrated radio-and-OW system, Ieee
transection on Wireless Communication, 2006.
[23] Yi Zheng, Xianzhong Xie, Lili Yang, Cooperative Spectrum Sensing
Based on SNR Comparison in Fusion Center for Cognitive Radio,
International Conference on Advanced Computer Control, 2008.
[24] Yonghua Wang, Yuehong Li, Fei Yuan and Jian Yang, A Cooperative
Spectrum Sensing Scheme Based on Trust and Fuzzy Logic for
Cognitive Radio Sensor Networks, IJCSI International Journal of
Computer Science Issues, 2013.
[25] Ejaz, W., Hasan, N., Azam, A. M, Lee, S. and Kim, S. H, I3S:
Intelligent spectrum sensing scheme for cognitive radio networks,
EURASIP Journal on Wireless Communications and Networking, 2013.
@article{"International Journal of Information, Control and Computer Sciences:77009", author = "Tallataf Rasheed and Adnan Rashdi and Ahmad Naeem Akhtar", title = "Reliability Factors Based Fuzzy Logic Scheme for Spectrum Sensing", abstract = "The accurate spectrum sensing is a fundamental requirement of dynamic spectrum access for deployment of Cognitive Radio Network (CRN). To acheive this requirement a Reliability factors based Fuzzy Logic (RFL) Scheme for Spectrum Sensing has been proposed in this paper. Cognitive Radio User (CRU) predicts the presence or absence of Primary User (PU) using energy detector and calculates the Reliability factors which are SNR of sensing node, threshold of energy detector and decision difference of each node with other nodes in a cooperative spectrum sensing environment. Then the decision of energy detector is combined with Reliability factors of sensing node using Fuzzy Logic. These Reliability Factors used in RFL Scheme describes the reliability of decision made by a CRU to improve the local spectrum sensing. This Fuzzy combining scheme provides the accuracy of decision made by sensornode. The simulation results have shown that the proposed technique provide better PU detection probability than existing Spectrum Sensing Techniques.", keywords = "Cognitive radio, spectrum sensing, energy detector,
reliability factors, fuzzy logic.", volume = "12", number = "2", pages = "84-6", }
