Malicious Node Restricted Quantized Data Fusion Scheme for Trustworthy Spectrum Sensing in Cognitive Radio Networks

Authors:

Arpita Chakraborty,Jyoti Sekhar Banerjee,Abir Chattopadhyay,

DOI NO:

https://doi.org/10.26782/jmcms.2020.01.00004

Keywords:

Cognitive radio,fusion rules,cooperative spectrum sensing,quantized fusion rule,

Abstract

Accuracy in spectrum sensing is very much required in cognitive radio network, which is a revolutionary paradigm to drift the spectrum underutilization problem. To enhance the detection performance in presence of shadowing or fading multiple SUs cooperate among themselves. But the collaboration and so the detection process is severely affected by the presence of some harmful secondary users known as Malicious users. As a result of this false sensing, spectrum wastage or interference with primary users may happen which are not at all desired for the system. The proposed approach in this paper has intelligently excluded these malicious users from the decision making process and thus improves the efficiency of the system.

Refference:

I. A. Ghasemi and 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 ’05), pp. 131– 136, November 2005

II. A. Ghasemi and E. S. Sousa, “Opportunistic spectrum access in fading channels through collaborative sensing,” Journal of Communications, vol. 2,no. 2, pp. 71–82, 2007
III. A. Ghasemi, & E. S. Sousa, “Spectrum sensing in cognitive radio networks: the cooperation-processing tradeoff”, Wireless Communications and Mobile Computing, 7(9), 1049-1060, 2007
IV. A. Chakraborty, and J.S. Banerjee, “An Advance Q Learning (AQL) Approach for Path Planning and Obstacle Avoidance of a Mobile Robot”. International Journal of Intelligent Mechatronics and Robotics, 3(1), pp 53-73
2013
V. A. Chakraborty, J. S. Banerjee, and A. Chattopadhyay, “Non-Uniform Quantized Data Fusion Rule Alleviating Control Channel Overhead for Cooperative Spectrum Sensing in Cognitive Radio Networks”. In: Proc. IACC, pp 210-215 2017
VI. A. Chakraborty, J. S. Banerjee, and A. Chattopadhyay, “Non-uniform quantized data fusion rule for data rate saving and reducing control channel overhead for cooperative spectrum sensing in cognitive radio networks”, Wireless Personal Communications, Springer, 104(2), 837-851, 2019
VII. D. Das, et. al., “Analysis of Implementation Factors of 3D Printer: The Key Enabling Technology for making Prototypes of the Engineering Design and Manufacturing”, International Journal of Computer Applications, pp.8-14, 2017
VIII. E. Hossain, D. Niyato, and Z. Han, “Dynamic Spectrum Access in Cognitive Radio Networks”, Cambridge University Press, Cambridge, UK, 2008 IX. E. Visotsky, S. Ku ffher, and R. Peterson, “On collaborative detection of TV transmissions in support of dynamic spectrum sharing”, in Proceedings of the 1st IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN ’05), pp. 338–345, Baltimore, USA, November 2005
X. F. Akyildiz, B. F. Lo, and R. Balakrishnan, “Cooperative spectrum sensing in cognitive radio networks: A survey”, Physical Communication (Elsevier) Journal, vol. 4, no. 1, pp. 40-62, March. 2011

XI. I. Pandey, et. al., “WBAN: A Smart Approach to Next Generation ehealthcare System”, In 2019 3rd International Conference on Computing Methodologies and Communication (ICCMC), pp. 344-349, IEEE, 2019

XII. J. Mitola III and G. Q. Maguire Jr., “Cognitive radio: making software radios more personal”, IEEE Personal Communications, vol. 6, no. 4, pp. 13–18, 1999
XIII. J. Mitola III, “Cognitive Radio— An Integrated Agent Architecture for Software Defined Radio”.Royal Institute of Technology, 2000
XIV. J. S. Banerjee, A. Chakraborty, and A. Chattopadhyay, “Relay node selection using analytical hierarchy process (AHP) for secondary transmission in multi-user cooperative cognitive radio systems”, in Proc. ETAEERE 2016,
LNEE-Springer, Dec. 2016
XV. J. S. Banerjee, A. Chakraborty, and A. Chattopadhyay, “Fuzzy based relay selection for secondary transmission in cooperative cognitive radio networks”, in Proc. OPTRONIX 2016, Springer, India, Aug. 2016
XVI. J. S. Banerjee, et. al., “A Comparative Study on Cognitive Radio Implementation Issues”, International Journal of Computer Applications, vol.45, no.15, pp. 44-51, May.2012
XVII. J. S. Banerjee, A. Chakraborty, and A. Chattopadhyay, “Reliable best-relay selection for secondary transmission in co-operation based cognitive radio systems: A multi-criteria approach”, Journal of Mechanics of Continua and
Mathematical Sciences, 13(2), 24-42, 2018
XVIII. J. S. Banerjee, and A. Chakraborty, “Fundamentals of Software Defined Radio and Cooperative Spectrum Sensing: A Step Ahead of Cognitive Radio Networks”. In Handbook of Research on Software-Defined and Cognitive Radio Technologies for Dynamic Spectrum Management, IGI Global, pp 499-543 2015
XIX. J. S. Banerjee, A. Chakraborty, and K. Karmakar, “Architecture of Cognitive Radio Networks”. In N. Meghanathan & Y.B.Reddy (Ed.), Cognitive Radio Technology Applications for Wireless and Mobile Ad Hoc Networks, IGI
Global, pp 125-152 2013
XX. J. S. Banerjee, and A. Chakraborty, “Modeling of Software Defined Radio Architecture & Cognitive Radio, the Next Generation Dynamic and Smart Spectrum Access Technology”. In M.H. Rehmani & Y. Faheem (Ed.),
Cognitive Radio Sensor Networks: Applications, Architectures, and Challenges, IGI Global, pp. 127-158 2014
XXI. J. Banerjee, et. al., “Impact of machine learning in various network security applications”, In 2019 3rd International Conference on Computing Methodologies and Communication (ICCMC), pp. 276-281, IEEE, 2019
XXII. J. S. Banerjee, et. al., “A Survey on Agri-Crisis in India Based on Engineering Aspects”, Int. J. of Data Modeling and Knowledge Management, 3(1–2), pp.71-76, 2013
XXIII. J. S. Banerjee, A. Chakraborty, and A. Chattopadhyay, “A novel best relay selection protocol for cooperative cognitive radio systems using fuzzy AHP”, Journal of Mechanics of Continua and Mathematical Sciences, 13(2), 72-87,
2018
XXIV. K. B. Letaief and W. Zhang, “Cooperative spectrum sensing”, in Cognitive Wireless Communication Networks, Springer, New York, NY, USA, 2007

XXV. Laneman, J. N., et al. “Cooperative diversity in wireless networks: Efficient protocols and outage behavior”, IEEE Trans. Inform. Theory, 50(12), pp.3062-3080, 2004
XXVI. M. K. Simon, & M. S. Alouini, [Digital communication over fading channels]. John Wiley & Sons, Hoboken, NJ, Vol. 95, 2005

XXVII. O. Saha; A. Chakraborty, and J. S. Banerjee, “A Decision Framework of ITBased Stream Selection Using Analytical Hierarchy Process (AHP) for Admission in Technical Institutions”, In: Proc. OPTRONIX 2017, IEEE, pp.
1-6, Nov. 2017
XXVIII. O. Saha; A. Chakraborty, and J. S. Banerjee, “A Fuzzy AHP Approach to ITBased Stream Selection for Admission in Technical Institutions in India”, In: Proc. IEMIS, AISC-Springer, pp. 847-858, 2019

XXIX. R. Chen, J.-M. Park, and J. H. Reed, “Defense against primary user emulation attacks in cognitive radio networks”, IEEE Journalon Selected Areas in Communications,vol.26,no.1,pp. 25–37, 2008
XXX. R. Chen, J.-M. Park, and K. Bian, “Robust distributed spectrum sensing in cognitive radio networks”, in Proceedings of IEEE International Conference on Computer Communications (INFOCOM ’08), pp. 31–35, Phoenix, Ariz,
USA, April 2008

XXXI. S. Haykin, “Cognitive radio: brain-empowered wireless communications”, IEEE Journal on Selected Areas in Communications, vol. 23, no. 2, pp. 201–220, 2005
XXXII. S. M. Mishra, A. Sahai, and R. W. Brodersen, “Cooperative sensing among cognitive radios”, in Proceedings of the IEEE International Conference on Communications (ICC ’06), vol. 4, pp. 1658–1663, Istanbul, Turkey, June 2006
XXXIII. S. Paul, A. Chakraborty, and J. S. Banerjee, “A Fuzzy AHP-Based Relay Node Selection Protocol for Wireless Body Area Networks (WBAN)”, In: Proc. OPTRONIX 2017, IEEE, pp. 1-6, Nov. 2017
XXXIV. S. Paul, A. Chakraborty, and J. S. Banerjee, “The Extent Analysis Based Fuzzy AHP Approach for Relay Selection in WBAN”, In: Proc. CISC, (pp.331-341). Springer, Singapore, 2019
XXXV. T. Newman and T. Clancy, “Security threats to cognitive radio signal classifiers”, in Proceedings of the Virginia Tech Wireless Personal Communications Symposium, Blacksburg, USA, June 2009
XXXVI. T. Clancy and 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 (Crown Com ’08), Singapore, May 2008
XXXVII. Z. Han and K. J. R. Liu, “Resource Allocation for Wireless Networks: Basics, Techniques, and pplications”, Cambridge University Press, Cambridge, UK, 2008

View Download