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International Transaction of Electrical and Computer Engineers System. 2014, 2(6), 149-157
DOI: 10.12691/iteces-2-6-1
Open AccessArticle

Distributed Cognitive Routing in Multi-channel Multi-hop Networks with Accessibility Consideration

Mehdi Golestanian1, , Mohammad Reza Azimi2 and Reza Ghazizade1

1Department of Electrical Engineering, Birjand University, Birjand, Iran

2Department of Computer Engineering, Shahid bahonar university of Kerman, Kerman, Iran

Pub. Date: December 10, 2014

Cite this paper:
Mehdi Golestanian, Mohammad Reza Azimi and Reza Ghazizade. Distributed Cognitive Routing in Multi-channel Multi-hop Networks with Accessibility Consideration. International Transaction of Electrical and Computer Engineers System. 2014; 2(6):149-157. doi: 10.12691/iteces-2-6-1

Abstract

Among Cognitive Radio Network (CRN) research topics, routing algorithms especially for multi-channel networks are in the early stages. In this paper, we design a novel cognitive routing scheme for multi-channel multi-hop wireless networks. The main contribution of the proposed routing scheme is the sub-optimal low computational complexity which makes it applicable for distributed network architecture with power constraints. Other important aspect of the proposed routing scheme is considering the objectives related to the network performance, accessibility and efficient spectrum utilization jointly. As the simulation results demonstrate the presented scheme provides a significant improvement in the spectral efficiency and adequate QoS in term of delay propagation and interference in CRN.

Keywords:
Cognitive Radio routing multi-channel networks accessibility probability based scheme (PBS)

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References:

[1]  Y. Xiao and F. Hu, Cognitive radio networks, Auerbach Publications, 2008.
 
[2]  T. Yucek, H. Arsalan, “A survey of spectrum sensing algorithms for cognitive radio applications,” IEEE Communications and Tutorial, vol. 11, no. 1, pp. 116-130, Oct. 2009.
 
[3]  M. Cesana, F. Cuomo and E. Ekici, “Routing in Cognitive Radio Networks: Challenges and Solutions,” Ad-hoc networks Journal, vol. 9, no. 3, pp. 228-248, May. 2011.
 
[4]  M. Xie, W. Zhang and K. Wong, “A Geometric Approach to Improve Spectrum Efficiency for Cognitive Relay Networks,” IEEE Transaction on Wireless Communication, vol. 9, no. 1, pp. 268-281, Jan. 2010.
 
[5]  H. Ma, L. Zheng, X. Ma, Y. luo, “Spectrum aware routing for multi-hop cognitive radio networks with a single transceiver,” 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications, pp. 1-6, 2008.
 
[6]  G. Cheng, W. Liu, Y. Li, W. Cheng, “Spectrum aware on-demand routing in cognitive radio networks,” 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, pp. 571-574, 2007.
 
[7]  H.-P. Shiang, M. van der Schaar, “Distributed resource management in multi-hop cognitive radio networks for delay-sensitive transmission,” IEEE Transactions on Vehicular Technology, Vol. 58 no. 2, pp. 941-953, 2009.
 
[8]  I. Pefkianakis, S. Wong, S. Lu, “SAMER: spectrum aware mesh routing in cognitive radio networks,” 3rd IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks, pp. 1-5, 2008.
 
[9]  T. Liu and W. Liao, “On Routing in Multichannel Wireless Mesh Networks: Challenges and Solutions,” IEEE network, vol. 22, no. 1, pp. 13-18, Jan. 2008.
 
[10]  N. Baldo, M.Zorzi, “Learning and adaptation in cognitive radios using neural networks,” IEEE Consumer Communications and Networking Conference, pp. 998-1003, Jan. 2008.
 
[11]  I. A. Akbar, W. H. Tranter, “Dynamic Spectrum Allocation in Cognitive Radio Using Hidden Markov Models: Poisson Distributed Case,” in Proceeding of IEEE Southeast Conference, pp. 196-201, March. 2007.
 
[12]  C, Ghosh, C. Cordeiro, D. P. Agrawal, M. B. Rao, “Markov Chain Existence and Hidden Markov Models in Spectrum Sensing,” IEEE International Conference on Pervasive Computing and Communications, pp. 1-6, March. 2009.
 
[13]  Y. Song, Y. Fang, Y. Zhang, “Stochastic channel selection in cognitive radio networks,” IEEE global telecommunication conference, pp. 4878-4882, 2007.
 
[14]  D. Chen, M. Haenggi, and J. N. Laneman, “Distributed spectrum efficient routing algorithms in wireless networks,” IEEE Transaction on Wireless Communication, vol. 7, no. 12, pp. 5297-5305, Dec. 2008.
 
[15]  T. Weiss, J. Hillenbrand, A. Krohn, and F. K. Jondral, “Mutual interference in OFDM-based spectrum pooling systems,” in Proc. IEEE Vehicular Tech. Conf., pp. 1873-1877, May 2004.
 
[16]  Q. Wu, Y.Yao, J. Wang, G. Ding, “Kernel-based learning for statistical signal processing in cognitive radio networks: Theoretical foundations, example applications, and future directions,” IEEE Signal Processing Magazine, vol. 30, no. 4, pp. 126-136, July 2013.
 
[17]  “Decentralized sensor selection for cooperative spectrum sensing based on unsupervised learning,” in Proc. IEEE International Conference on Communications (ICC), June 2012, pp. 1576-1580.
 
[18]  D. Bharadia, G. Bansal, P. Calagineedi and V. K. Bhargava, “Relay and power allocation schemes for OFDM-based cognitive radio systems,” IEEE Transaction on Wireless Communications, vol. 10, no. 9, pp. 2812-2817, Sep. 2011.
 
[19]  S. Boyd and L. Vandenberghe, Convex Optimization. Cambridge University Press, 2004.
 
[20]  W. Wang, J. Cai, A. S. Alfa, “Distributed Routing Schemes with Accessibility Consideration in Multi-hop Wireless Networks,” IEEE Transaction on Wireless Communications, vol. 9, no. 10, pp. 3178-3188, Oct. 2010.