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January  2014, 10(1): 21-40. doi: 10.3934/jimo.2014.10.21

Effect of spectrum sensing overhead on performance for cognitive radio networks with channel bonding

Haruki Katayama 1, , Hiroyuki Masuyama 1, , Shoji Kasahara 2, and  Yutaka Takahashi 1,

1. 

Graduate School of Informatics, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan
2. 

Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama, Ikoma, Nara 630-0192, Japan

Received  September 2012 Revised  June 2013 Published  October 2013

In cognitive radio networks, secondary spectrum users detect available frequency channels by spectrum sensing. In general, the sensing time is communication overhead, and affects system's performance. In this paper, we theoretically consider the effect of sensing overhead on the system performance for cognitive radio networks with channel bonding. Specifically, we model the system with a multidimensional continuous-time Markov chain whose state is defined by the numbers of primary users, secondary users, and sensing users. The blocking probability, the forced termination probability and the throughput are derived. The analysis is validated by Monte Carlo simulation. Numerical examples show that the forced termination probability is not affected by sensing overhead, while the blocking probability and the throughput degrade with the increase in the sensing time. It is also shown that the optimal number of bonded sub-channels for the throughput performance significantly depends on the offered load from primary users.
Keywords: spectrum handoff, performance evaluation., queueing theory, Cognitive radio networks, Markov chain.
Mathematics Subject Classification: Primary: 60K25, 60J27; Secondary: 68M2.
Citation: Haruki Katayama, Hiroyuki Masuyama, Shoji Kasahara, Yutaka Takahashi. Effect of spectrum sensing overhead on performance for cognitive radio networks with channel bonding. Journal of Industrial & Management Optimization, 2014, 10 (1) : 21-40. doi: 10.3934/jimo.2014.10.21
References:
[1]

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[2]

H. T. Cheng and W. Zhuang, Simple channel sensing order in cognitive radio networks,, IEEE Journal on Selected Areas in Communications, 29 (2011), 676.   Google Scholar

[3]

C. Cordeiro, K. Challapali and D. Birru, IEEE 802.22: An Introduction to the first wireless standard based on cognitive radios,, Journal of Communications, 1 (2006), 38.  doi: 10.4304/jcm.1.1.38-47.  Google Scholar

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[6]

Y. Konishi, H. Masuyama, S. Kasahara and Y. Takahashi, Performance analysis of dynamic spectrum access with channel bonding for cognitive radio networks,, Proc. QTNA 2012, (2012).   Google Scholar

[7]

Y. Konishi, H. Masuyama, S. Kasahara and Y. Takahashi, Performance analysis of dynamic spectrum handoff scheme with variable bandwidth demand of secondary users for cognitive radio networks,, Wireless Networks, 19 (2013), 607.  doi: 10.1007/s11276-012-0488-2.  Google Scholar

[8]

T. V. Krishna and A. Das, A survey on MAC protocols in OSA networks,, Computer Networks, 53 (2009), 1377.   Google Scholar

[9]

J. Lee and J. So, Analysis of cognitive radio networks with channel aggregation,, Proc. IEEE WCNC 2010, (2010), 1.  doi: 10.1109/WCNC.2010.5506262.  Google Scholar

[10]

J. Park, P. Pawelczak and D. Cabric, To buffer or to switch: Design of multichannel MAC for OSA ad hoc networks,, Proc. IEEE DySPAN 2010, (2010), 1.  doi: 10.1109/DYSPAN.2010.5457877.  Google Scholar

[11]

P. Pawelczak, S. Pollin, H. -S. W. So, A. Bahai, R. V. Prasad and R. Hekmat, Performance analysis of multichannel medium access control algorithms for opportunistic spectrum access,, IEEE Transactions on Vehicular Technology, 58 (2009), 3014.  doi: 10.1109/TVT.2008.2009350.  Google Scholar

[12]

H. Su and X. Zhang, Cross-layer based opportunistic MAC protocols for QoS provisionings over cognitive radio wireless networks,, IEEE Journal on Selected Areas in Communications, 26 (2008), 118.  doi: 10.1109/JSAC.2008.080111.  Google Scholar

[13]

V. K. Tumuluru, P. Wang and D. Niyato, Performance analysis of cognitive radio spectrum access with prioritized traffic,, Proc. IEEE ICC 2011, (2011), 1.   Google Scholar

[14]

Y. Zhang, Dynamic spectrum access in cognitive radio wireless networks,, Proc. IEEE ICC 2008, (2008), 4927.  doi: 10.1109/ICC.2008.923.  Google Scholar

[15]

X. Zhu, L. Shen and T. -S. P. Yum, Analysis of cognitive radio spectrum access with optimal channel reservation,, IEEE Communications Letters, 11 (2007), 304.  doi: 10.1109/LCOM.2007.348282.  Google Scholar

show all references

References:
[1]

I. F. Akyildiz, W. -Y. Lee, M. C. Vuran and S. Mohanty, NeXt generation/dynamic spectrum access/cognitive radio wireless networks: A survey,, Computer Networks, 50 (2006), 2127.  doi: 10.1016/j.comnet.2006.05.001.  Google Scholar

[2]

H. T. Cheng and W. Zhuang, Simple channel sensing order in cognitive radio networks,, IEEE Journal on Selected Areas in Communications, 29 (2011), 676.   Google Scholar

[3]

C. Cordeiro, K. Challapali and D. Birru, IEEE 802.22: An Introduction to the first wireless standard based on cognitive radios,, Journal of Communications, 1 (2006), 38.  doi: 10.4304/jcm.1.1.38-47.  Google Scholar

[4]

L. Jiao, V. Pla and F. Y. Li, Analysis on channel bonding/aggregation for multi-channel cognitive radio networks,, Proc. IEEE EW 2010, (2010), 468.  doi: 10.1109/EW.2010.5483492.  Google Scholar

[5]

S. M. Kannappa and M. Saquib, Performance analysis of a cognitive network with dynamic spectrum assignment to secondary users,, Proc. IEEE ICC 2010, (2010), 1.  doi: 10.1109/ICC.2010.5502743.  Google Scholar

[6]

Y. Konishi, H. Masuyama, S. Kasahara and Y. Takahashi, Performance analysis of dynamic spectrum access with channel bonding for cognitive radio networks,, Proc. QTNA 2012, (2012).   Google Scholar

[7]

Y. Konishi, H. Masuyama, S. Kasahara and Y. Takahashi, Performance analysis of dynamic spectrum handoff scheme with variable bandwidth demand of secondary users for cognitive radio networks,, Wireless Networks, 19 (2013), 607.  doi: 10.1007/s11276-012-0488-2.  Google Scholar

[8]

T. V. Krishna and A. Das, A survey on MAC protocols in OSA networks,, Computer Networks, 53 (2009), 1377.   Google Scholar

[9]

J. Lee and J. So, Analysis of cognitive radio networks with channel aggregation,, Proc. IEEE WCNC 2010, (2010), 1.  doi: 10.1109/WCNC.2010.5506262.  Google Scholar

[10]

J. Park, P. Pawelczak and D. Cabric, To buffer or to switch: Design of multichannel MAC for OSA ad hoc networks,, Proc. IEEE DySPAN 2010, (2010), 1.  doi: 10.1109/DYSPAN.2010.5457877.  Google Scholar

[11]

P. Pawelczak, S. Pollin, H. -S. W. So, A. Bahai, R. V. Prasad and R. Hekmat, Performance analysis of multichannel medium access control algorithms for opportunistic spectrum access,, IEEE Transactions on Vehicular Technology, 58 (2009), 3014.  doi: 10.1109/TVT.2008.2009350.  Google Scholar

[12]

H. Su and X. Zhang, Cross-layer based opportunistic MAC protocols for QoS provisionings over cognitive radio wireless networks,, IEEE Journal on Selected Areas in Communications, 26 (2008), 118.  doi: 10.1109/JSAC.2008.080111.  Google Scholar

[13]

V. K. Tumuluru, P. Wang and D. Niyato, Performance analysis of cognitive radio spectrum access with prioritized traffic,, Proc. IEEE ICC 2011, (2011), 1.   Google Scholar

[14]

Y. Zhang, Dynamic spectrum access in cognitive radio wireless networks,, Proc. IEEE ICC 2008, (2008), 4927.  doi: 10.1109/ICC.2008.923.  Google Scholar

[15]

X. Zhu, L. Shen and T. -S. P. Yum, Analysis of cognitive radio spectrum access with optimal channel reservation,, IEEE Communications Letters, 11 (2007), 304.  doi: 10.1109/LCOM.2007.348282.  Google Scholar

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