过零双门限协作频谱感知算法
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摘要
应用过零双门限协作频谱感知算法估计无线电频谱的占用状态,研究了认知用户个数、计算所用的采样点数、不同信噪比及判决系数对检测概率的影响,并与传统双门限能量检测、差分双门限能量检测算法的检测性能进行了对比研究,发现在信噪比为-5 dB,判决系数为0. 05,虚警概率小于等于0. 8时,过零双门限检测方法单认知用户检测性能明显优于其他2种检测方法;当信噪比均为-5 dB,参与协作感知的认知用户个数小于6时,过零双门限协作检测算法性能明显优于其他2种算法;在虚警概率恒定的情况下,增加计算所用的采样点数或增大判决系数能够明显提高检测概率;在虚警概率恒定情况下,算法检测概率随着信噪比增大而增大,当信噪比为-7 dB时,检测概率趋近于1;在相同的检测条件下,过零双门限协作检测算法的虚警概率要明显低于差分双门限检测的虚警概率。结果表明:过零双门限协作频谱感知算法可以降低系统的虚警概率,有效解决噪声不确定性问题,进一步提高系统感知性能。
The occupation state was studied in radio spectrum by zero-crossing dual-threshold cooperative spectrum sensing algorithm. The effect of the number of cognitive users,the number of sampling points used in the calculation,the different signal-to-noise ratio,and the decision coefficient on the probability of detection was studied. The detection performance of the algorithm was compared with the conventional dual-threshold energy detection algorithm and dual-threshold spectrum sensing algorithm based on differential energy detection. It is found that when the signal-to-noise ratio is-5 dB,the decision coefficient is 0. 05,and the false alarm probability is less than or equal to 0. 8,the single-user detection performance of the zero-crossing dual-threshold detection method is obviously better than that of other two detection algorithms. When the signal-to-noise ratio is-5 dB and the number of cognitive users participating in cooperative sensing is less than 6,the performance of the zero-crossing dualthreshold detection algorithm is obviously better than that of other two algorithms. When the false alarmprobability is constant,increasing the number of sampling points used in the calculation or increasing the decision coefficient can significantly increase the detection probability. When the false alarm probability is constant,the detection probability of the algorithm increases with the increase of SNR; when the SNR is-7 dB,the detection probability approaches 1. Under the same detection conditions,the false alarm probability of the zero-crossing dual-threshold cooperative detection algorithm is obviously lower than the false alarm probability of the dual-threshold spectrum sensing algorithm based on differential energy detection. The results indicate that zero-crossing dual-threshold cooperative spectrum sensing algorithm can reduce the false alarm probability of the system,effectively solve the problem of noise uncertainty,and further improve the system's perceived performance.
The occupation state was studied in radio spectrum by zero-crossing dual-threshold cooperative spectrum sensing algorithm. The effect of the number of cognitive users,the number of sampling points used in the calculation,the different signal-to-noise ratio,and the decision coefficient on the probability of detection was studied. The detection performance of the algorithm was compared with the conventional dual-threshold energy detection algorithm and dual-threshold spectrum sensing algorithm based on differential energy detection. It is found that when the signal-to-noise ratio is-5 dB,the decision coefficient is 0. 05,and the false alarm probability is less than or equal to 0. 8,the single-user detection performance of the zero-crossing dual-threshold detection method is obviously better than that of other two detection algorithms. When the signal-to-noise ratio is-5 dB and the number of cognitive users participating in cooperative sensing is less than 6,the performance of the zero-crossing dualthreshold detection algorithm is obviously better than that of other two algorithms. When the false alarmprobability is constant,increasing the number of sampling points used in the calculation or increasing the decision coefficient can significantly increase the detection probability. When the false alarm probability is constant,the detection probability of the algorithm increases with the increase of SNR; when the SNR is-7 dB,the detection probability approaches 1. Under the same detection conditions,the false alarm probability of the zero-crossing dual-threshold cooperative detection algorithm is obviously lower than the false alarm probability of the dual-threshold spectrum sensing algorithm based on differential energy detection. The results indicate that zero-crossing dual-threshold cooperative spectrum sensing algorithm can reduce the false alarm probability of the system,effectively solve the problem of noise uncertainty,and further improve the system's perceived performance.
引文
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[17]刘会衡,陈伟,刘克中.一种基于能量检测的双门限协作频谱感知技术[J].武汉理工大学学报,2011(4):144-148.LIU Hui-heng,CHEN Wei,LIU Ke-zhong. A dualthreshold cooperative spectrum sensing technology based on energy detection[J]. Journal of Wuhan University of Technology,2011(4):144-148.
[18] Liu S Q,Hu B J,Wang X Y. Hierarchical cooperative spectrum sensing based on dual thresholds energy detection[J]. Communications Letters IEEE,2012,16(7):1096-1099.
[19] Detection M F,Detection E. Two-stage detectors with multiple energy detectors and adaptive dual threshold in cognitive radio networks[J]. International Journal of Distributed Sensor Networks,2013,2013(9):172-180.
[20]张学军,鲁友,田峰,等.基于信任度的双门限协作频谱感知算法[J].物理学报,2014,63(7):78401.ZHANG Xue-jun,LU You,TIAN Feng,et al. Dualthreshold cooperative spectrum sensing for cognitive radio based on trust[J]. Acta Physica Sinica,2014,63(7):78401.
[21]张学军,严金童,田峰,等.基于差分能量检测的双门限协作频谱感知算法[J].仪器仪表学报,2014,35(6):1325-1330.ZHANG Xu-jun,YAN Jin-tong,TIAN Feng,et al. Dual-threshold cooperative spectrum sensing algorithm based on differential energy detection[J]. Chinese Journal of Scientific Instrument,2014,35(6):1325-1330.
[22] Kedem B. Spectral analysis and discrimination by zerocrossings[J]. Proceedings of the IEEE,1986,74(11):1477-1493.
[23] ZHANG L L,HUANG J G,Tang C K. Novel energy detection scheme in cognitive radio[C]//IEEE International Conference on Signal Processing,Communications and Computing. IEEE,2011:1-4.
[24] Welch B L. On linear combinations of several variances[J]. Journal of the American Statistical Association,1956,51(273):132-148.
[25] SHEN Lei,WANG H,ZHANG W,et al. Blind spectrum sensing for cognitive radio channels with noise uncertainty[J]. IEEE Transactions on Wireless Communications,2011,10(6):1721-1724.
[2] Yang J. Spatial channel characterization for cognitive radios[D]. Berkeley:University of California,2004.
[3] ZHAO Qing,Sadler B M. A survey on dynamic spectrum access:signal processing,networking,and regulatory policy[J]. IEEE Signal Processing Magazine,2007,24(3):79-89.
[4] Stotas S,Nallanathan A. On the throughput and spectrum Sensing enhancement of opportunistic spectrum access cognitive radio networks[J]. IEEE Transactions on Wireless Communications,2012,11(1):97-107.
[5] Mitola J,Maguire G Q. Cognitive radio:Making software radios more personal[J]. IEEE Personal Communications,1999,6(4):13-18.
[6] Sofotasios P C,Rebeiz E,Zhang L,et al. Energy detection based spectrum sensing over and extreme fading channels[J]. IEEE Transactions on Vehicular Technology,2013,62(3):1031-1040.
[7] Yucek T,Arslan H. A survey of spectrum sensing algorithms for cognitive radio applications[J]. IEEE Communications Surveys and Tutorials,2009,11(1):116
[8]黄川,梁步林,许力,等.认知无线电网络中基于动态信誉机制的频谱分配策略研究[J].信号处理,2014(11):1339-1344.HUANG Chuan,LIANG Bu-lin,XU Li,et al. Research on dynamic reputation mechanism based spectrum allocation strategy in cognitive radio network[J]. Signal Processing,2014(11):1339-1344.
[9]弥寅,卢光跃.基于特征值极限分布的合作频谱感知算法[J].通信学报,2015,36(1):84-89.MI Yin,LU Guang-yue. Cooperative spectrum sensing algorithm based on limiting eigenvalue distribution[J].Journal on Communications,2015,36(1):84-89.
[10]陈长兴,符辉,牛德智,等.基于双门限能量检测的协作频谱感知算法[J].系统工程与电子技术,2013,35(8):1742-1746.CHEN Chang-xing,FU Hui,NIU De-zhi,et al. Cooperative spectrum sensing algorithm based on doublethreshold energy detection[J]. Systems Engineering and Electronics,2013,35(8):1742-1746.
[11]申滨,王舒,黄琼,等.基于Gerschgorin圆盘理论的认知无线电宽带频谱感知[J].通信学报,2014(4):1-10.SHEN Bin,WANG Shu,HUANG Qiong,et al. Gerschgorin disk theorem based spectrum sensing for wideband cognitive radio[J]. Journal on Communications,2014(4):1-10.
[12]贾琼,李兵兵.基于局部方差的MIMO频谱感知算法研究[J].电子与信息学报,2015,37(7):1525-1530.JIA Qiong,LI Bing-bing. MIMO spectrum sensing method based on the local variance[J]. Journal of Electronics and Information Technology,2015,37(7):1525-1530.
[13]张莹,滕伟,韩维佳,等.认知无线电频谱感知技术综述[J].无线电通信技术,2015,41(3):12-16.ZHANG Ying,TENG Wei,HAN Wei-jia,et al. Review of spectrum sensing techniques in cognitive radio networks[J]. Radio Communications Technology,2015,41(3):12-16.
[14]孙梦巍,赵龙,许巧春,等.动态时变衰落信道下的频谱感知算法[J].通信学报,2014,35(7):63-69.SUN Meng-wei,ZHAO Long,XU Qiao-chun,et al. New spectrum sensing method under time-variant flat fading channels[J]. Journal on Communications,2014,35(7):63-69.
[15]卢光跃,叶迎晖,孙宇,等.克服噪声不确定性的拟合优度检验频谱感知算法[J].电讯技术,2016,56(1):26-31.LU Guang-yue,YE Ying-hui,SUN Yu,et al. A novel anti-noise-uncertainty spectrum sensing method using goodness of fit test[J]. Telecommunication Engineering,2016,56(1):26-31.
[16]王海莲,张士兵,郭莉莉.基于可信度的加权协作频谱检测算法[J].数据采集与处理,2014,29(3):472-477.WANG Hai-lian,ZHANG Shi-bing,GUO Li-li. Reliability-based weighted cooperative spectrum sensing algorithm[J]. Journal of Data Acquisition and Processing,2014,29(3):472-477.
[17]刘会衡,陈伟,刘克中.一种基于能量检测的双门限协作频谱感知技术[J].武汉理工大学学报,2011(4):144-148.LIU Hui-heng,CHEN Wei,LIU Ke-zhong. A dualthreshold cooperative spectrum sensing technology based on energy detection[J]. Journal of Wuhan University of Technology,2011(4):144-148.
[18] Liu S Q,Hu B J,Wang X Y. Hierarchical cooperative spectrum sensing based on dual thresholds energy detection[J]. Communications Letters IEEE,2012,16(7):1096-1099.
[19] Detection M F,Detection E. Two-stage detectors with multiple energy detectors and adaptive dual threshold in cognitive radio networks[J]. International Journal of Distributed Sensor Networks,2013,2013(9):172-180.
[20]张学军,鲁友,田峰,等.基于信任度的双门限协作频谱感知算法[J].物理学报,2014,63(7):78401.ZHANG Xue-jun,LU You,TIAN Feng,et al. Dualthreshold cooperative spectrum sensing for cognitive radio based on trust[J]. Acta Physica Sinica,2014,63(7):78401.
[21]张学军,严金童,田峰,等.基于差分能量检测的双门限协作频谱感知算法[J].仪器仪表学报,2014,35(6):1325-1330.ZHANG Xu-jun,YAN Jin-tong,TIAN Feng,et al. Dual-threshold cooperative spectrum sensing algorithm based on differential energy detection[J]. Chinese Journal of Scientific Instrument,2014,35(6):1325-1330.
[22] Kedem B. Spectral analysis and discrimination by zerocrossings[J]. Proceedings of the IEEE,1986,74(11):1477-1493.
[23] ZHANG L L,HUANG J G,Tang C K. Novel energy detection scheme in cognitive radio[C]//IEEE International Conference on Signal Processing,Communications and Computing. IEEE,2011:1-4.
[24] Welch B L. On linear combinations of several variances[J]. Journal of the American Statistical Association,1956,51(273):132-148.
[25] SHEN Lei,WANG H,ZHANG W,et al. Blind spectrum sensing for cognitive radio channels with noise uncertainty[J]. IEEE Transactions on Wireless Communications,2011,10(6):1721-1724.
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