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Study and Performance Analysis of Dedicated In-Band Control Channels for Cognitive Radio Networks

Tamilarasan.S 1 , Kumar. P2

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-9 , Page no. 737-740, Sep-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i9.737740

Online published on Sep 30, 2018

Copyright © Tamilarasan.S, Kumar. P . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Tamilarasan.S, Kumar. P, “Study and Performance Analysis of Dedicated In-Band Control Channels for Cognitive Radio Networks,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.737-740, 2018.

MLA Style Citation: Tamilarasan.S, Kumar. P "Study and Performance Analysis of Dedicated In-Band Control Channels for Cognitive Radio Networks." International Journal of Computer Sciences and Engineering 6.9 (2018): 737-740.

APA Style Citation: Tamilarasan.S, Kumar. P, (2018). Study and Performance Analysis of Dedicated In-Band Control Channels for Cognitive Radio Networks. International Journal of Computer Sciences and Engineering, 6(9), 737-740.

BibTex Style Citation:
@article{P_2018,
author = {Tamilarasan.S, Kumar. P},
title = {Study and Performance Analysis of Dedicated In-Band Control Channels for Cognitive Radio Networks},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {9 2018},
volume = {6},
Issue = {9},
month = {9},
year = {2018},
issn = {2347-2693},
pages = {737-740},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2936},
doi = {https://doi.org/10.26438/ijcse/v6i9.737740}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i9.737740}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2936
TI - Study and Performance Analysis of Dedicated In-Band Control Channels for Cognitive Radio Networks
T2 - International Journal of Computer Sciences and Engineering
AU - Tamilarasan.S, Kumar. P
PY - 2018
DA - 2018/09/30
PB - IJCSE, Indore, INDIA
SP - 737-740
IS - 9
VL - 6
SN - 2347-2693
ER -

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Abstract

Recently wireless ad hoc network is an emerging new technology. Due to its emerging capability it faces spectrum scarcity problem. Resources and channels in CRN (cognitive radio network) would be allocated based on dynamic access methods with respected to sensed radio environment. Cognitive Radio (CR) technology provides a smart and optimistic solution to the problem of spectrum scarcity through Dynamic Spectrum Allocation (DSA). Due to the nature of Cognitive Radio Networks (CRNs), where two networks area unit active at the same time, a significant quantity of control messaging is essential in order to coordinate channel access, schedule sensing, and establish release connections. Efficient Control Plane messaging can be achieved by the selection of a suitable Control Channel (CC). This paper provides a comparative study of probable systems for providing reliable channels dedicated to the coordination and information distribution in License-Exempt (LE) bands. This involves determining the potential and limitations of every method.

Key-Words / Index Term

CRN, CC, Spectrum Management, Spectrum Allocation

References

[1] M. Ibnkahla, “Cooperative Cognitive Radio Networks: The Complete Spectrum Cycle”, CRC Press, 2014.
[2] P. Pawełczak, S. Pollin, W. So, A. Bahai, R. Prasad, and R. Hekmat, “Performance analysis of multichannel medium access control algorithms for opportunistic spectrum access,” IEEE Transactions on Vehicular Technology, Vol. 58, No. 6, pp. 3014–3031, 2009.
[3] Z. Zhang, K. Long, and J. Wang, “Self-organization paradigms and optimization approaches for cognitive radio technologies: a survey,” IEEE Wireless Communications, Vol. 20, No. 2, pp. 36–42, 2013.
[4] A. El-Mougy, M. Ibnkahla, G. Hattab, and W. Ejaz, “Reconfigurable wireless networks,” Proceedings of the IEEE, Vol. 103, No. 7, pp. 1125–1158, 2015.
[5] O. Mehanna, A. Sultan, and H. El Gamal, “Blind cognitive MAC protocols,” in IEEE International Conference on Communications (ICC), 2009, pp. 1–5.
[6] A. De Domenico, E. Strinati, and M. Di Benedetto, “A survey on MAC strategies for cognitive radio networks,” IEEE Communications Surveys Tutorials, Vol. 14, No. 1, pp. 21–44, 2012.
[7] B. Hamdaoui and K. G. Shin, “OS-MAC: An efficient MAC protocol for spectrum-agile wireless networks,” IEEE Transactions on Mobile Computing, Vol. 7, No. 8, pp. 915–930, 2008.
[8] A. Sabbah, “Dynamic spectrum allocation for cognitive radio networks: A comprehensive optimization approach,” Ph.D. dissertation, Queen’s Univesity, 2015.
[9] S. Debroy, S. De, and M. Chatterjee, “Contention based multichannel MAC protocol for distributed cognitive radio networks,” IEEE Transactions on Mobile Computing, Vol. 13, No. 12, pp. 2749–2762, 2014.
[10] A. M. Masri, C.-F. Chiasserini, C. Casetti, and A. Perotti, “Common control channel allocation in cognitive radio networks through UWB communication,” Journal of Communications and Networks, Vol. 14, No. 6, pp. 710–718, 2012.
[11] M. Petracca, R. Pomposini, F. Mazzenga, R. Giuliano, and M. Vari, “An always available control channel for cooperative sensing in cognitive radio networks,” in IEEE Wireless Days (WD), 2010, pp. 1–5.
[12] B. F. Lo, “A survey of common control channel design in cognitive radio networks,” Physical Communication, Vol. 4, No. 1, pp. 26–39, 2011.
[13] A. Sabbah and M. Ibnkahla, “Optimizing dynamic spectrum allocation for cognitive radio networks using hybrid access scheme,” in IEEE Wireless Communications and Networking Conference (WCNC), April 2016, pp. 2033–2038.
[14] G. Hattab and M. Ibnkahla, “Multiband spectrum access: Great promises for future cognitive radio networks,” Proceedings of the IEEE, Vol. 102, No. 3, pp. 282–306, March 2014.
[15] J. Soder, F. Mestanov, E. Sakai, K. Sakoda, and K. Agardh, “Stadium scenario for High-Effeciency WLAN (HEW),” IEEE 11-14/0381r, March 2014.
[16] B. Bellalta, “IEEE 802.11 ax: high-efficiency WLANs,” IEEE Wireless Communications, Vol. 23, No. 1, pp. 38–46, 2016.
[17] C. Wijting, K. Doppler, K. Kalliojarvi, N. Johansson, J. Nystrom, M. Olsson, A. Osseiran, M. Dottling, J. Luo, T. Svensson et al., “WINNER II system concept: advanced radio technologies for future wireless systems,” in Proceedings of the ICT-Mobile Summit Conference, 2008.
[18] A. Sabbah and M. Ibnkahla, “Integrating energy harvesting and dynamic spectrum allocation in cognitive radio networks,” in IEEE Wireless Communications and Networking Conference (WCNC), April 2016, pp. 784–789.
[19] E. B. Greenstein, A. J. Goldsmith, and J. Larry, “Principles of Cognitive Radio”. Cambridge University Press, 2012.
[20] V. S. Frost and B. Melamed, “Traffic modeling for telecommunications networks,” IEEE Communications Magazine, Vol. 32, No. 3, pp. 70–81, 1994.