2015, 11(4): 1393-1408. doi: 10.3934/jimo.2015.11.1393

Adjustable admission control with threshold in centralized CR networks: Analysis and optimization

1. 

School of Information Science and Engineering, Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province, Yanshan University, Qinhuangdao 066004, China

2. 

Department of Intelligence and Informatics, Konan University, Kobe 658-8501

Received  February 2014 Revised  October 2014 Published  March 2015

In order to enhance the Quality of Service (QoS) for the secondary users (SUs) in Cognitive Radio (CR) networks reasonably, in this paper, we propose an adjustable admission control scheme considering an access threshold under a centralized architecture. We assume that a buffer is set for all the SUs. On the arrival instant of an SU packet, if the number of SU packets already in the buffer is equal to or greater than the access threshold that is set in advance, this SU packet will be admitted to join the system with an adjustable access probability, which is inversely proportional to the total number of packets in the system. Based on the adjustable admission control scheme proposed in this paper, considering the priority of the primary users (PUs) in CR networks, we build a preemptive priority queueing model. Aiming to comply with the digital nature of modern networks, we establish a two-dimensional discrete-time Markov chain (DTMC) and construct the transition probability matrix of the Markov chain. Accordingly, we provide the formulas for several performance measures, such as the blocking rate, the throughput and the average latency of the SU packets. With numerical results, we show the influence of the access threshold on different performance measures for the SU packets. Finally, taking into account the trade-off between different performance measures, we build a net benefit function to find the optimal access threshold with an optimization algorithm.
Citation: Yuan Zhao, Shunfu Jin, Wuyi Yue. Adjustable admission control with threshold in centralized CR networks: Analysis and optimization. Journal of Industrial & Management Optimization, 2015, 11 (4) : 1393-1408. doi: 10.3934/jimo.2015.11.1393
References:
[1]

A. S. Alfa, Queueing Theory for Telecommunications: Discrete Time Modelling of a Single Node System,, Springer, (2010). doi: 10.1007/978-1-4419-7314-6.

[2]

B. Benmammar, A. Amraoui and F. Krief, A survey on dynamic spectrum access techniques in cognitive radio networks,, International Journal of Communication Networks and Information Security, 5 (2013), 68.

[3]

C. Ding, K. Wang and S. Lai, Channel coordination mechanism with retailers having fairness preference-An improved quantity discount mechanism,, Journal of Industrial and Management Optimization, 9 (2013), 967. doi: 10.3934/jimo.2013.9.967.

[4]

C. T. Do, N. H. Tran, C. S. Hong and S. Lee, Finding an individual optimal threshold of queue length in hybrid overlay/underlay spectrum access in cognitive radio networks,, IEICE Transactions on Communications, E95-B (2012), 1978. doi: 10.1587/transcom.E95.B.1978.

[5]

A. Greenbaum, Iterative Methods for Solving Linear Systems,, Society for Industrial and Applied Mathematics (SIAM), (1997). doi: 10.1137/1.9781611970937.

[6]

S. Jin, Y. Zhao, W. Yue and Z. Saffer, Performance analysis and optimization of an adaptive admission control scheme in cognitive radio networks,, Mathematical Problems in Engineering, 2013 (2013). doi: 10.1155/2013/727310.

[7]

H. Li and Z. Han, Socially optimal queuing control in cognitive radio networks subject to service interruptions: To queue or not to queue?,, IEEE Transactions on Wireless Communications, 10 (2011), 1656.

[8]

J. Marinho and E. Monteiro, Cognitive radio: Survey on communication protocols, spectrum decision issues, and future research directions,, Wireless Networks, 18 (2012), 147. doi: 10.1007/s11276-011-0392-1.

[9]

A. Turhan, M. Alanyali and D. Starobinski, Optimal admission control of secondary users in preemptive cognitive radio networks,, Proceedings of the 10th International Symposium on Modeling and Optimization in Mobile, (2012), 138.

[10]

F. Wang, J. Huang and Y. Zhao, Delay sensitive communications over cognitive radio networks,, IEEE Transactions on Wireless Communications, 11 (2012), 1402. doi: 10.1109/TWC.2012.020812.110133.

[11]

X. Wang, A. V. Vasilakos, M. Chen, Y. Liu and T. T. Kwon, A survey of green mobile networks: Opportunities and challenges,, Mobile Networks and Applications, 17 (2012), 4. doi: 10.1007/s11036-011-0316-4.

[12]

Y. Zhao, S. Jin and W. Yue, Performance evaluation of a dynamic channel allocation strategy with access threshold in CRNs,, Proceedings of the 14th International Symposium on Knowledge and Systems Sciences, (2013), 181.

show all references

References:
[1]

A. S. Alfa, Queueing Theory for Telecommunications: Discrete Time Modelling of a Single Node System,, Springer, (2010). doi: 10.1007/978-1-4419-7314-6.

[2]

B. Benmammar, A. Amraoui and F. Krief, A survey on dynamic spectrum access techniques in cognitive radio networks,, International Journal of Communication Networks and Information Security, 5 (2013), 68.

[3]

C. Ding, K. Wang and S. Lai, Channel coordination mechanism with retailers having fairness preference-An improved quantity discount mechanism,, Journal of Industrial and Management Optimization, 9 (2013), 967. doi: 10.3934/jimo.2013.9.967.

[4]

C. T. Do, N. H. Tran, C. S. Hong and S. Lee, Finding an individual optimal threshold of queue length in hybrid overlay/underlay spectrum access in cognitive radio networks,, IEICE Transactions on Communications, E95-B (2012), 1978. doi: 10.1587/transcom.E95.B.1978.

[5]

A. Greenbaum, Iterative Methods for Solving Linear Systems,, Society for Industrial and Applied Mathematics (SIAM), (1997). doi: 10.1137/1.9781611970937.

[6]

S. Jin, Y. Zhao, W. Yue and Z. Saffer, Performance analysis and optimization of an adaptive admission control scheme in cognitive radio networks,, Mathematical Problems in Engineering, 2013 (2013). doi: 10.1155/2013/727310.

[7]

H. Li and Z. Han, Socially optimal queuing control in cognitive radio networks subject to service interruptions: To queue or not to queue?,, IEEE Transactions on Wireless Communications, 10 (2011), 1656.

[8]

J. Marinho and E. Monteiro, Cognitive radio: Survey on communication protocols, spectrum decision issues, and future research directions,, Wireless Networks, 18 (2012), 147. doi: 10.1007/s11276-011-0392-1.

[9]

A. Turhan, M. Alanyali and D. Starobinski, Optimal admission control of secondary users in preemptive cognitive radio networks,, Proceedings of the 10th International Symposium on Modeling and Optimization in Mobile, (2012), 138.

[10]

F. Wang, J. Huang and Y. Zhao, Delay sensitive communications over cognitive radio networks,, IEEE Transactions on Wireless Communications, 11 (2012), 1402. doi: 10.1109/TWC.2012.020812.110133.

[11]

X. Wang, A. V. Vasilakos, M. Chen, Y. Liu and T. T. Kwon, A survey of green mobile networks: Opportunities and challenges,, Mobile Networks and Applications, 17 (2012), 4. doi: 10.1007/s11036-011-0316-4.

[12]

Y. Zhao, S. Jin and W. Yue, Performance evaluation of a dynamic channel allocation strategy with access threshold in CRNs,, Proceedings of the 14th International Symposium on Knowledge and Systems Sciences, (2013), 181.

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