Channel Selection Algorithms Performance Evaluation for Spectrum Decision in Cognitive Radio

: pp. 87 - 94
Lviv Polytechnic National University
Lviv Polytechnic National University
Lviv Polytechnic National University

Different spectrum decision methods in a Cognitive radio network were analyzed in this paper. The technology of Cognitive Radio networks needs to make a decision which spectrum band is the best among the available free bands. Spectrum decision is closely related to all operational parameters, channel characteristics and any activity of primary users. Also, spectrum decision depends on all cognitive users inside network activities. The process of spectrum decision is not based only on cognitive users’ local observations but also on primary network channels statistical information, such as interference, path loss, wireless link errors, link layer delay. After the definition of available spectrum bands had been held, the most corresponding band of spectrum with considering channel characteristics and QoS requirements should be chosen. Spectrum decision methods can be classified as: non-load- balancing, probability-based and sensing-based spectrum decision.

An analytical system model is proposed to compare channel selection algorithms by main operational parameters to minimize total system selection time. The considered methods, which are based on balancing traffic load, can distribute secondary users load to multiple channels, in contradistinction to non-load-balancing methods that choose the first channel with the lowest busy probability. When the secondary users traffic load is low, the probability- based method shows a reduce of total system time, otherwise, when traffic load is high the sensing-based method can improve system performance.

1. I. F. Akyildiz, W. Lee, M. C. Vuran, “A Survey on Spectrum Management in Cognitive Radio Networks,” IEEE Communications Magazine, Apr. 2008, pp. 43. 2. W.-Y. Lee, I. F. Akyildiz, “A spectrum decision framework for cognitive radio networks”, IEEE Trans. Mobile Computing, Feb. 2011, pp. 161— 174. 3. M. Kyryk, V. Yanyshyn, “Effective capacity evaluation model for cognitive radio networks using OFDM” Academic Journals of L’viv Polytechnic National University, Series of Radio Electronics and Telecommunication“, 2014. — No. 796. — pp. 104–112. 4. Y. A. Gromakov, “The concept of development of mobile and wireless public”, Telecommunication No. 12, 2008, pp. 51–57. 5. M.Kyryk, V. Yanyshyn. Proactive spectrum handoff performance evaluation model for cognitive radio. — 3rd International Scientific-Practical Conference “Problems of Infocommunications. Science and Technology”, IEEE PIC S&T 2016, 4-6 October, Kharkiv, Ukraine. — pp. 18-20. 6. C.-W. Wang, L.-C. Wang, and F. Adachi, “Performance Gains for Spectrum Utilization in Cognitive Radio Networks with Spectrum Handoff”, International Symposium on Wireless Personal Multimedia Communications (WPMC), Sep. 2009. 7. H.-J. Liu, Z.-X. Wang, S.-F. Li, and M. Yi, “Study on the Performance of Spectrum Mobility in Cognitive Wireless Network,” IEEE Singapore International Conference on Communication Systems (ICCS), Jun. 2008. 8. H. Tang, “Some physical layer issues of wide-band cognitive radio systems”, in Proc. IEEE Int. Symp. on New Frontiers in Dynamic Spectrum Access Networks, Nov. 2005, pp. 151–159. 9. L. N. Volkov, M. S. Nemirovsky, Y. S. Shinakov, “Digital radio: basic methods and characteristics,” Eco-Trendz, Moscow, 2005. 10. Y. Yao, D. Erman, A. P. Popescu, “Spectrum Decision for Cognitive Radio Networks”, 10th Scandinavian Workshop on Wireless Adhoc Networks (ADHOC), Sweden, May 2011. 11. M. Kyryk, L. Matiishyn, V. Yanyshyn, “Performance comparison of cognitive radio networks spectrum sensing methods” TCSET’2016, Feb. 2016, pp. 597–600. 12. M.Kyryk, V. Yanyshyn, “Cooperative Spectrum Sensing Performance Analysis in Cognitive Radio Networks” AICT 2015, Oct. 2015. 13. C. Ng and B. Soong, “Queueing Modelling Fundamentals with Applications” Communication Networks, 2nd. John Wiley & Sons Inc., 2008. 14. Y. Song, J. Xie, “Common Hopping Based Proactive Spectrum Handoff in Cognitive Radio Ad Hoc Networks”, IEEE Global Communications Conference, Dec. 2010. 15. L. Wang, C. Wang, F. Adachi “Load-Balancing Spectrum Decision for Cognitive Radio Networks”, IEEE Journal on Selected Areas in Communications, May, 2011. 16. H. Jiang, L. Lai, R. Fan, “Optimal Selection of Channel Sensing Order in Cognitive Radio”, IEEE Trans. Wireless Communication, vol. 8 Jan. 2009. 17. C. Wang, L. Wang, “Modeling and Analysis for Proactive-decision Spectrum Handoff in Cognitive Radio Networks”, IEEE International Conference on Communications (ICC), Jun. 2009. 18. A. Banaei and C. N. Georghiades, “Throughput Analysis of a Randomized Sensing Scheme in Cell-based Ad-hoc Cognitive Networks”, IEEE International Conference on Communications (ICC), Jun. 2009.