Benefits of Coalition Game Theory over Bargain Game Theory to Resolve the Problems of Spectrum Sensing in Cognitive Radio Network

Benefits of Coalition Game Theory over Bargain Game Theory to Resolve the Problems of Spectrum Sensing in Cognitive Radio Network

  IJETT-book-cover           
  
© 2023 by IJETT Journal
Volume-71 Issue-11
Year of Publication : 2023
Author : Rakhi Khedkar, Shweta Kukade, Kishor Wagh, Sharmila Wagh
DOI : 10.14445/22315381/IJETT-V71I11P214

How to Cite?

Rakhi Khedkar, Shweta Kukade, Kishor Wagh, Sharmila Wagh, "Benefits of Coalition Game Theory over Bargain Game Theory to Resolve the Problems of Spectrum Sensing in Cognitive Radio Network," International Journal of Engineering Trends and Technology, vol. 71, no. 11, pp. 129-135, 2023. Crossref, https://doi.org/10.14445/22315381/IJETT-V71I11P214

Abstract
Coalition Game Theory (CGT) enhances cooperation in a game. To state, examine and discover a key for spectrum sensing and allocation in Cognitive Radio Networks (CRN), collaboration takes a leading role. This paper states game theory's role in resolving the problems present in the spectrum sensing and allocation. The cooperative and non-cooperative game theory is discussed. The major emphasis of this paper is on how the CGT is imperative and cooperates to resolve the problems present in spectrum sensing in CRN. It specifies the merits and demerits of CGT over Bargain Game theory to fix the problems present in CRN. Finally, it is proved that the utility function of Secondary Users enhanced using CGT compared to Bargain Game Theory during spectrum sensing.

Keywords
Cognitive Radio Network, Spectrum sensing, Spectrum allocation, Coalition Game Theory, Bargain Game Theory.

References
[1] Kwang-Cheng Chen, and Ramjee Prasad, Cognitive Radio Networks, John Wiley and Sons, 2009.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Hüseyin Arslan, Cognitive Radio, Software Defined Radio, and Adaptive Wireless Systems, Springer Science and Business Media, pp. 1- 469, 2007.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Bruce A. Fette, Cognitive Radio Technology, Elsevier Science, pp. 1-656, 2006.
[Google Scholar] [Publisher Link]
[4] Alexander M. Wyglinski, Maziar Nekovee, and Thomas Hou, Cognitive Radio Communications and Networks: Principles and Practice, Elsevier Science, pp. 1-736, 2009.
[Google Scholar] [Publisher Link]
[5] Yuanhua Fu, Fan Yang, and Zhiming He, “A Quantization-Based Multibit Data Fusion Scheme for Cooperative Spectrum Sensing in Cognitive Radio Networks,” Sensors, vol. 18, no. 2, pp. 1-14, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Hurmat Ali Shah, and Insoo Koo, “Reliable Machine Learning Based Spectrum Sensing in Cognitive Radio Networks,” Wireless Communications and Mobile Computing, vol. 2018, pp. 1-18, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Walid Saad et al., “Coalitional Game Theory for Communication Networks: A tutorial,” arXiv, pp. 1-28, 2009.
[Google Scholar] [Publisher Link]
[8] Walid Saad et al., “A Distributed Coalition Formation Framework for Fair User Cooperation in Wireless Networks,” IEEE Transactions on Wireless Communications, vol. 8, no. 9, pp. 4580-4593, 2009.
[CrossRef] [Google Scholar] [Publisher Link]
[9] O. Namvar Gharehshiran, A. Attar, and V. Krishnamurthy, “Dynamic Coalition Formation for Resource Allocation in Cognitive Radio Networks,” 2010 IEEE International Conference on Communications, pp. 1-6, 2010.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Beibei Wang, Yongle Wu, and K.J. Ray Liu, “Game Theory for Cognitive Radio Networks: An Overview,” Computer Networks, vol. 54, no. 14, pp. 2537-2561, 2010.
[CrossRef] [Google Scholar] [Publisher Link]
[11] V. Balaji, and Chittaranjan Hota, “Efficient Cooperative Spectrum Sensing in Cognitive Radio Using Coalitional Game Model,” 2014 International Conference on Contemporary Computing and Informatics (IC3I), pp. 899-907, 2014.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Girraj Sharma, and Ritu Sharma, “Performance Improvement of CSS Over Imperfect Reporting Using Diversity Reception in Cognitive Radio Networks,” World Journal of Engineering, vol. 16, no. 1, pp. 87-93, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Anggun Fitrian Isnawati, “A Survey of Game Theoretical Approach in Cognitive Radio Network and 5G-6G Communications,” Journal of Communications, vol. 17, no. 10, pp. 830-843, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[14] D. Narmatha, W. Jenifa, and Pushpa Mettilsha, “Implementation of Cognitive Wireless Sensor Network with Energy Aware Cooperative Spectrum Sensing by Different Censoring Techniques,” SSRG International Journal of Electronics and Communication Engineering, vol. 7, no. 5, pp. 24-32, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[15] R.A. Khedkar, and R.A. Patil, “A Reliable Co-operative Decision-Making Technique for the Improvement in the Performance of MultiUser CRN Using Coalition Game,” IETE Journal of Research, vol. 68, no. 2, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[16] R.A. Khedkar, and R.A. Patil, “Comprehensive Dynamic Spectrum Allocation in Multi-PU Multi-SU CRN Using Coalition Game Theory,” 2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), pp. 1-6, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[17] Roger B. Myerson, Game Theory: Analysis of Conflict, Harvard University Press, pp. 1-568, 1991.
[Google Scholar] [Publisher Link]
[18] Roger A. Mccain, Game Theory: A Nontechnical Introduction to the Analysis of Strategy, 3rd ed., World Scientific Publishing Company, pp. 1-600, 2014.
[Google Scholar] [Publisher Link]
[19] Md. Shamim Hossain et al., “Hard Decision Based Cooperative Spectrum Sensing over Different Fading Channel in Cognitive Radio,” International Journal of Advance Innovations, Thoughts and Ideas, vol. 2, no. 3, pp.1-12, 2013.
[Google Scholar] [Publisher Link]
[20] Shital Vachhani, and Arjav Bavarva, “Cyclostationary Based Detection Method of Spectrum Sensing for Cognitive Radio,” International Journal of P2P Network Trends and Technology, vol. 4, no. 2, pp. 39-41, 2014.
[Google Scholar] [Publisher Link]
[21] D. Teguig, B. Scheers, and V. Le Nir, “Data Fusion Schemes for Cooperative Spectrum Sensing in Cognitive Radio Networks,” 2012 Military Communications and Information Systems Conference (MCC), pp. 1-7, 2012.
[Google Scholar] [Publisher Link]]
[22] Ajay Singh, and Ritu Rana, “Security Analysis of Cognitive Radio Netwoks Using Game Theory,” SSRG International Journal of Electronics and Communication Engineering, vol. 5, no. 2, pp. 7-9, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[23] Ashish Rauniyar, Jae Min Jang, and Soo Young Shin, “Optimal Hard Decision Fusion Rule for Centralized and Decentralized Cooperative Spectrum Sensing in Cognitive Radio Networks,” Journal of Advances in Computer Networks, vol. 3, no. 3, pp. 207-212, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[24] Megha Motta, “A Survey on Data and Decision Fusion Strategies on Spectrum Sensing in Cognitive Radio Networks,” International Journal of Advanced Research in Computer and Communication Engineering, vol. 3, no. 7, pp. 7510-7518, 2014.
[Google Scholar] [Publisher Link]