• Previous Article
    A cross-layer relay selection scheme of a wireless network with multiple relays under Rayleigh fading
  • JIMO Home
  • This Issue
  • Next Article
    Catastrophe equity put options under stochastic volatility and catastrophe-dependent jumps
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

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.
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]

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.

[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.

[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.

[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.

[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.

[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).

[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.

[8]

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

[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.

[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.

[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.

[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.

[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.

[14]

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

[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.

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.

[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.

[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.

[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.

[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.

[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).

[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.

[8]

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

[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.

[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.

[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.

[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.

[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.

[14]

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

[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.

[1]

Yuan Zhao, Wuyi Yue. Performance evaluation and optimization of cognitive radio networks with adjustable access control for multiple secondary users. Journal of Industrial & Management Optimization, 2019, 15 (1) : 1-14. doi: 10.3934/jimo.2018029

[2]

Yuan Zhao, Wuyi Yue. Cognitive radio networks with multiple secondary users under two kinds of priority schemes: Performance comparison and optimization. Journal of Industrial & Management Optimization, 2017, 13 (3) : 1449-1466. doi: 10.3934/jimo.2017001

[3]

Yuan Zhao, Wuyi Yue. Performance analysis and optimization for cognitive radio networks with a finite primary user buffer and a probability returning scheme. Journal of Industrial & Management Optimization, 2017, 13 (5) : 1-16. doi: 10.3934/jimo.2018195

[4]

Hyeon Je Cho, Ganguk Hwang. Optimal design for dynamic spectrum access in cognitive radio networks under Rayleigh fading. Journal of Industrial & Management Optimization, 2012, 8 (4) : 821-840. doi: 10.3934/jimo.2012.8.821

[5]

Shunfu Jin, Wuyi Yue, Zsolt Saffer. Analysis and optimization of a gated polling based spectrum allocation mechanism in cognitive radio networks. Journal of Industrial & Management Optimization, 2016, 12 (2) : 687-702. doi: 10.3934/jimo.2016.12.687

[6]

Seunghee Lee, Ganguk Hwang. A new analytical model for optimized cognitive radio networks based on stochastic geometry. Journal of Industrial & Management Optimization, 2017, 13 (4) : 1883-1899. doi: 10.3934/jimo.2017023

[7]

Kazuhiko Kuraya, Hiroyuki Masuyama, Shoji Kasahara. Load distribution performance of super-node based peer-to-peer communication networks: A nonstationary Markov chain approach. Numerical Algebra, Control & Optimization, 2011, 1 (4) : 593-610. doi: 10.3934/naco.2011.1.593

[8]

Shengzhu Jin, Bong Dae Choi, Doo Seop Eom. Performance analysis of binary exponential backoff MAC protocol for cognitive radio in the IEEE 802.16e/m network. Journal of Industrial & Management Optimization, 2017, 13 (3) : 1483-1494. doi: 10.3934/jimo.2017003

[9]

Jae Deok Kim, Ganguk Hwang. Cross-layer modeling and optimization of multi-channel cognitive radio networks under imperfect channel sensing. Journal of Industrial & Management Optimization, 2015, 11 (3) : 807-828. doi: 10.3934/jimo.2015.11.807

[10]

Zhanqiang Huo, Wuyi Yue, Naishuo Tian, Shunfu Jin. Performance evaluation for the sleep mode in the IEEE 802.16e based on a queueing model with close-down time and multiple vacations. Journal of Industrial & Management Optimization, 2009, 5 (3) : 511-524. doi: 10.3934/jimo.2009.5.511

[11]

Shiva Moslemi, Abolfazl Mirzazadeh. Performance evaluation of four-stage blood supply chain with feedback variables using NDEA cross-efficiency and entropy measures under IER uncertainty. Numerical Algebra, Control & Optimization, 2017, 7 (4) : 379-401. doi: 10.3934/naco.2017024

[12]

Anupam Gautam, Selvamuthu Dharmaraja. Selection of DRX scheme for voice traffic in LTE-A networks: Markov modeling and performance analysis. Journal of Industrial & Management Optimization, 2019, 15 (2) : 739-756. doi: 10.3934/jimo.2018068

[13]

Samuel N. Cohen, Lukasz Szpruch. On Markovian solutions to Markov Chain BSDEs. Numerical Algebra, Control & Optimization, 2012, 2 (2) : 257-269. doi: 10.3934/naco.2012.2.257

[14]

Zhanyou Ma, Wuyi Yue, Xiaoli Su. Performance analysis of a Geom/Geom/1 queueing system with variable input probability. Journal of Industrial & Management Optimization, 2011, 7 (3) : 641-653. doi: 10.3934/jimo.2011.7.641

[15]

B. Fernandez, E. Ugalde, J. Urías. Spectrum of dimensions for Poincaré recurrences of Markov maps. Discrete & Continuous Dynamical Systems - A, 2002, 8 (4) : 835-849. doi: 10.3934/dcds.2002.8.835

[16]

Shunfu Jin, Wuyi Yue, Zhanqiang Huo. Performance evaluation for connection oriented service in the next generation Internet. Numerical Algebra, Control & Optimization, 2011, 1 (4) : 749-761. doi: 10.3934/naco.2011.1.749

[17]

Shunfu Jin, Wuyi Yue, Chao Meng, Zsolt Saffer. A novel active DRX mechanism in LTE technology and its performance evaluation. Journal of Industrial & Management Optimization, 2015, 11 (3) : 849-866. doi: 10.3934/jimo.2015.11.849

[18]

Keiji Tatsumi, Masashi Akao, Ryo Kawachi, Tetsuzo Tanino. Performance evaluation of multiobjective multiclass support vector machines maximizing geometric margins. Numerical Algebra, Control & Optimization, 2011, 1 (1) : 151-169. doi: 10.3934/naco.2011.1.151

[19]

Tuan Phung-Duc, Wouter Rogiest, Sabine Wittevrongel. Single server retrial queues with speed scaling: Analysis and performance evaluation. Journal of Industrial & Management Optimization, 2017, 13 (4) : 1927-1943. doi: 10.3934/jimo.2017025

[20]

Shunfu Jin, Haixing Wu, Wuyi Yue, Yutaka Takahashi. Performance evaluation and Nash equilibrium of a cloud architecture with a sleeping mechanism and an enrollment service. Journal of Industrial & Management Optimization, 2017, 13 (5) : 1-18. doi: 10.3934/jimo.2019060

2017 Impact Factor: 0.994

Metrics

  • PDF downloads (5)
  • HTML views (0)
  • Cited by (3)

[Back to Top]