Cooperative spectrum sensing algorithm based on minimum detecting overhead

被引:0
作者
Qin, Zhen [1 ]
Zhou, Jiangang [2 ]
Xue, Feng [3 ]
机构
[1] School of Electronic Engineering, Xidian Univ., Xi'an
[2] School of Manufacturing Science and Engineering, Sichuan Univ., Chengdu
[3] Hubei Radio Management Committee, Wuhan
来源
Xi'an Dianzi Keji Daxue Xuebao/Journal of Xidian University | 2015年 / 42卷 / 02期
关键词
Cognitive radio; Cooperative spectrum sensing; Energy detection; Minimum detecting overhead;
D O I
10.3969/j.issn.1001-2400.2015.02.034
中图分类号
学科分类号
摘要
In the limited resource wireless cognitive radio networks, the application of the cooperative spectrum sensing technique improves system performance, but also results in the increase of channel detecting overhead. In this context, selecting appropriate system parameters can effectively minimize the detecting overhead. After analyzing the models of single-user and multi-user spectrum sensing systems based on energy detection, we proposed a cooperative spectrum sensing algorithm based on minimum detecting overhead. The main ideas of the algorithm and implementation steps are given. In addition, we have derived a detecting overhead formula, and theoretically proved the existence of the minimum of detection overhead. Furthermore, simulation results verify effectiveness of system parameter optimization and reliability of the algorithm. ©, 2015, Science Press. All right reserved.
引用
收藏
页码:206 / 212
页数:6
相关论文
共 18 条
[1]  
Wu J., Dai Y., Zhao Y., Effective Channel Assignments in Cognitive Radio Networks, Computer Communications, 36, 4, pp. 411-420, (2013)
[2]  
Liu X., Jia M., Tan X., Threshold Optimization of Cooperative Spectrum Sensing in Cognitive Radio Networks, Radio Science, 48, 1, pp. 23-32, (2013)
[3]  
Zhang N., Cheng N., Lu N., Et al., Risk-aware Cooperative Spectrum Access for Multi-channel Cognitive Radio Networks, IEEE Journal on Selected Areas in Communications, 32, 3, pp. 516-527, (2014)
[4]  
Kim H., Shin K.G., In-band Spectrum Sensing in Cognitive Radio Networks: Energy Detection or Feature Detection, Proceedings of the 14th Annual International Conference on Mobile Computing and Networking, pp. 14-25, (2008)
[5]  
Zhang W., Mallik R.K., Letaief K.B., Cooperative Spectrum Sensing Optimization in Cognitive Radio Networks, IEEE International Conference on Communications, pp. 3411-3415, (2008)
[6]  
Maleki S., Chepuri S.P., Leus G., Optimization of Hard Fusion Based Spectrum Sensing for Energy-constrained Cognitive Radio Networks, Physical Communication, 9, pp. 193-198, (2013)
[7]  
Min A.W., Shin K.G., An Optimal Sensing Framework Based on Spatial RSS-profile in Cognitive Radio Networks, 6th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, pp. 1-9, (2009)
[8]  
Lee W.Y., Akyildiz I.F., Optimal Spectrum Sensing Framework for Cognitive Radio Networks, IEEE Transactions on Wireless Communications, 7, 10, pp. 3845-3857, (2008)
[9]  
Gismalla E.H., Alsusa E., On the Performance of Energy Detection Using Bartlett's Estimate for Spectrum Sensing in Cognitive Radio Systems, IEEE Transactions on Signal Processing, 60, 7, pp. 3394-3404, (2012)
[10]  
Ding G., Wu Q., Zou Y., Et al., Joint Spectrum Sensing and Transmit Power Adaptation in Interference-aware Cognitive Radio Networks, Transactions on Emerging Telecommunications Technologies, 25, 2, pp. 231-238, (2014)