PRP M/G/m Queuing Theory Spectrum Handoff Model Based on Classified Secondary Users

MA Bin; CHENG Shuangguo; XIE Xianzhong

doi:10.11999/JEIT171117

Volume 40 Issue 8

Aug. 2018

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2018 > 40(8): 1963-1970

MA Bin, CHENG Shuangguo, XIE Xianzhong. PRP M/G/m Queuing Theory Spectrum Handoff Model Based on Classified Secondary Users[J]. Journal of Electronics & Information Technology, 2018, 40(8): 1963-1970. doi: 10.11999/JEIT171117

Citation:

MA Bin, CHENG Shuangguo, XIE Xianzhong. PRP M/G/m Queuing Theory Spectrum Handoff Model Based on Classified Secondary Users[J]. Journal of Electronics & Information Technology, 2018, 40(8): 1963-1970. doi: 10.11999/JEIT171117

Citation:

PDF( 1027 KB)

PRP M/G/m Queuing Theory Spectrum Handoff Model Based on Classified Secondary Users

doi: 10.11999/JEIT171117

Funds:

The National Natural Science Foundation of China (61471076, 61601070), The Foundation and Advanced Research Program of Chongqing (cstc2015jcyjA40047, cstc2016 jcyjA0455), The Doctoral Start-up Fund of Chongqing University of Posts and Telecommunications (A2015-16)

Received Date: 2017-11-28
Rev Recd Date: 2018-03-07
Publish Date: 2018-08-19

Abstract

Abstract

In order to meet different delay requirements of secondary users and improve the channel utilization, a PRP M/G/m queuing theory spectrum handoff model based on classified secondary user is proposed. Firstly, according to different delay requirements of the main service, secondary users are classified into delay-sensitive and non-delay-sensitive users. The delay-sensitive users have higher priority to access the channel. Secondly, PRP M/G/m queuing theory is adopted to establish the spectrum handoff model. Meanwhile, the extended data delivery time of secondary users with different priorities is deduced and analyzed. Then the adaptive spectrum handoff strategy for secondary users is proposed. Simulation results suggest that the proposed model can reduce the handoff delay and extended data delivery time, which can effectively ensure the QoS of high- priority secondary users and improve the overall performance.
- Cognitive Radio (CR),
- Spectrum handoff,
- Queuing theory

FullText(HTML)

References(16)

References

KUMAR K, PRAKASH A, and TRIPATHI R. Spectrum handoff in cognitive radio networks: A classification and comprehensive survey[J]. Journal of Network and Computer Applications, 2016, 61(8): 161-188. doi: 10.1016/j.jnca.2015. 10.008.

MITOLA J and MAGUIRE G Q. Cognitive radio: Making software radios more personal[J]. IEEE Personal Communications, 1999, 6(4): 13-18. doi: 10.1109/98.788210.

HAYKIN S. Cognitive radio: Brain-empowered wireless communications[J]. IEEE Journal on Selected Areas in Communications, 2005, 23(2): 201-220. doi: 10.1109/JSAC. 2004.839380.

WANG Beibei and LIU K J R. Advances in cognitive radio networks: A survey[J]. IEEE Journal of Selected Topics in Signal Processing, 2011, 5(1): 5-23. doi: 10.1109/JSTSP.2010. 2093210.

CHRISTIAN I, MOH S, CHUNG I, et al. Spectrum mobility in cognitive radio networks[J]. IEEE Communications Magazine, 2012, 50(6): 114-121. doi: 10.1109/MCOM.2012. 6211495.

SALAMEH O, TURCK K D, BRUNEEL H, et al. Analysis of secondary user performance in cognitive radio networks with reactive spectrum handoff[J]. Telecommunication System, 2017, 65(3): 1-12. doi: 10.1007/s11235-016-0250-7.

WANG Lichun and WANG Chunwang. Analysis of reactive spectrum handoff in cognitive radio networks[J]. IEEE Journal on Selected Areas in Communications, 2012, 30(10): 2016-2028. doi: 10.1109/JSAC.2012.121116.

WU Yan, YANG Qinghai, LIU Xuefang, et al. Delay- constrained optimal transmission with proactive spectrum handoff in cognitive radio networks[J]. IEEE Transactions on Communications, 2016, 64(7): 2767-2779. doi: 10.1109/ TCOMM.2016.2561936.

TAYEL A F, RABIA S I, and ABOUELSEOUD Y. An optimized hybrid approach for spectrum handoff in cognitive radio networks with non-identical channels[J]. IEEE Transactions on Communications, 2016, 64(11): 4487-4496. doi: 10.1109/TCOMM.2016.2607741.

马彬, 包小敏, 谢显中. 认知无线网络中基于混合频谱切换的最优目标信道选择算法[J]. 电子与信息学报, 2017, 39(1): 31-37. doi: 10.11999/JEIT160268. MA Bin, BAO Xiaomin, and XIE Xianzhong. Optimal target channel selection algorithm based on hybrid spectrum handoffs in cognitive radio networks[J]. Journal of Electronics Information Technology, 2017, 39(1): 31-37. doi: 10.11999/ JEIT160268.

WANG Lichun, WANG Chungwei, and CHANG Chungju. Modeling and analysis for spectrum handoffs in cognitive radio networks[J]. IEEE Transactions on Mobile Computing, 2012, 11(9): 1499-1513. doi: 10.1109/TMC.2011.155.

ZAHED S, AWAN I, and CULLEN A. Analytical modeling for spectrum handoff decision in cognitive radio networks[J]. Simulation Modelling Practice and Theory, 2013, 38(1): 98-114. doi: 10.1016/j.simpat.2013.07.003.

ZHANG Lei, SONG Tiecheng, WU Ming, et al. Traffic- adaptive proactive spectrum handoff stategy for graded secondary users in cognitive radio networks[J]. Chinese Journal of Electronics, 2015, 24(4): 844-851. doi: 10.1049/cje. 2015.10.030.

ZAKARIYA A Y and RABIA S I. Analysis of an interruption-based priority for multi-class secondary users in cognitive radio networks[C]. IEEE International Conference on Communications, Kuala Lumpur, Malaysia, 2016: 1-6. doi: 10.1109/ICC.2016.7511542.

杨小龙, 谭学治, 关凯. 认知无线电网络中基于抢占式排队论的频谱切换模型[J]. 物理学报, 2015, 64(10): 379-388. doi: 10.7498/aps.64.108403. YANG Xiaolong, TAN Xuezhi, and GUAN Kai. Spectrum handoff model based on preemptive queuing theory in cognitive radio networks[J]. Acta Physica Sinica, 2015, 64(10): 379-388. doi: 10.7498/aps.64.108403.

ZHANG Yun, JIANG Tao, ZHANG Lei, et al. Analysis on the transmission delay of priority-based secondary users in cognitive radio networks[C]. International Conference on Wireless Communications and Signal Processing, Hangzhou, China, 2013: 1-6. doi: 10.1109/WCSP.2013.6677133.

Relative Articles

Supplements(0)

Cited By

Proportional views