Optimization of Spectrum Sensing Parameters in Cognitive Radio Using Adaptive Genetic Algorithm

• Autorzy: Chatterjee S. , Dutta S. , Bhattacharya P. P. , Roy J. S.
• Języki publikacji: EN

Abstrakty

EN

Quality of service parameters of cognitive radio, like, bandwidth, throughput and spectral efficiency are optimized using adaptive and demand based genetic algorithm. Simulation results show that the proposed method gives better real life solution to the cognitive radio network than other known approach.

Słowa kluczowe

EN

adaptive genetic algorithm; bandwidth; cognitive radio; spectrum sensing; throughput

• Wydawca: Instytut Łączności - Państwowy Instytut Badawczy
• Czasopismo: Journal of Telecommunications and Information Technology
• Rocznik: 2017
• Tom: nr 1
• Strony: 21--27
• Opis fizyczny: Bibliogr. 12 poz., rys., tab.

Twórcy

autor

Chatterjee S.

• Department of Electronics and Communication Engineering University of Engineering & Management Kolkata, West Bengal, India

autor

Dutta S.

• Reliance Jio Infocomm Ltd. Big Data Analysis Mumbai, Maharashtra, India

autor

Bhattacharya P. P.

• Department of Electronics and Communication Engineering College of Engineering and Technology Mody University of Science and Technology Lakshmangarh – 332311, Rajasthan, India

autor

Roy J. S.

• School of Electronics Engineering KIIT University Bhubaneswar, Odisha India

Bibliografia

• [1] J. Elhachmi and Z. Guennoun, “Cognitive radio spectrum allocation using genetic algorithm”, EURASIP J. on Wirel. Commun. and Netw., vol. 2016, pp. 133–143, 2016 (doi: 10.1186/s13638-0160620-6).
• [2] S. Chatterjee, J. S. Roy, and P. P. Bhattacharya, “Spectrum sensing techniques for cognitive radio – a survey”, Int. J. of Appl. Engin. Res., vol. 10, no. 7, 2015, pp. 16665–16684.
• [3] R. Deka, S. Chakraborty, and J. S. Roy, “Optimization of spectrum sensing in cognitive radio using genetic algorithm”, Facta Universit., Ser: Elec. Energ., vol. 25, no. 3, pp. 235–243, 2012 (doi: 10.2298/FUUEE1203235D).
• [4] M. J. Kaur, M. Uddin, and H. K Verma, “Optimization of QOS parameters in cognitive radio using adaptive genetic algorithm” Int. J. of Next-Gener. Netw., vol. 4, no. 2, pp. 1–15, 2012.
• [5] J. Ramesh and A. Raman, “Optimization of sensing parameters using PSO, GA for cognitive radio”, Recent Trends in Sensor Res. & Technol., vol. 2, no. 3, pp. 23–30, 2015.
• [6] P. T. A. Quang, S. R. Kim, and D. S. Kim, “A throughput-aware routing for distributed industrial cognitive radio sensor networks”, in Proc. 9th IEEE Int. Worksh. on Factory Commun. Syst. WFCS 2012, Detmold, Germany, 2012, pp. 87–90.
• [7] T. T. Le, and D.-S. Kim, “An effcient throughput improvement through bandwidth awareness in cognitive radio networks”, J. of Commun. & Netw., vol. 16, no. 2, pp. 146–154, 2014 (doi: 10.1109/JCN.2014.000025).
• [8] S. Kaur and I. K. Aulakh, “Optimization of cognitive radio sensing techniques using genetic algorithm”, Int. J. of Innov. Res. in Comp. & Commun. Engin., vol. 3, no. 5, pp. 4131–4139, 2015 (doi: 10.15680/ijircce.2015.0305104).
• [9] I. F. Akyildiz, W. Y. Lee, and K. R. Chowdhury, “Spectrum management in cognitive radio ad hoc networks”, IEEE Network, vol. 23, no. 4, pp. 6–12, 2009.
• [10] A. Mar¸tian, C. Vlǎdeanu, I. Marcu, and I. Marghescu, “Evaluation of spectrum occupancy in an urban environment in a cognitive radio context”, Int. J. on Adv. in Telecommun., vol. 3, no. 3–4, pp. 172–181, 2010.
• [11] M. Lopez-Benitez et al., “Spectral occupation measurements and blind standard recognition sensor for cognitive radio networks”, in Proc. 4th Int. Conf. on Cognitive Radio Oriented Wireless Networks & Commun. CrownCom 2009, Hannover, Germany, 2009, pp. 1–9.
• [12] X. Meng, S. Wu, L. Kuang, D. Huang, and J. Lu, “Multi-user detection for spatial modulation via structured approximate message passing”, IEEE Commun. Lett., vol. 20, no. 8, pp. 1527–1530, 2016 (doi: 10.1109/LCOMM.2016.2577627).

Uwagi

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).