基于功率谱对消的时域相关认知跳频谱检测算法

doi:10.3969/j.issn.1000-1093.2017.09.012

摘要/Abstract

摘要： 认知跳频技术将认知无线电运用到跳频通信中，通过检测认知跳频频谱中的“频谱空穴”来更新跳频点集，避免频点碰撞，提高频谱利用率。针对频谱检测中的时域相关算法因噪声和授权信号的存在，导致频谱空穴的判定门限难以确定，从而使占用信号的检测概率较低的问题，提出了一种基于功率谱对消的时域相关算法来检测跳频谱。与未经过功率谱对消运算的传统时域相关算法相比，该算法能有效提高信号的检测概率，具有实时性好、克服白噪声不确定性、抑制授权信号干扰的优点。理论分析与仿真结果表明，基于功率谱对消的时域相关算法优于传统时域相关算法。

关键词: 通信技术, 认知跳频, 功率谱对消, 时域相关

Abstract: Cognitive frequency hopping technology is to apply cognitive radio to frequency hopping communication. The spectrum hole in cognitive frequency hopping spectrum can be detected effectively to avoid the collision of frequency points and improve the spectral efficiency to update the frequency hopping points. The time-domain correlation algorithm in spectrum detection technology for cognitive radio has some defects in anti-interference, universality and real-time performance due to the existence of noise and primary signals. A time-domain correlation algorithm based on power spectrum cancellation is proposed to detect the cognitive frequency hopping spectrum. The proposed algorithm can be used to improve the detection probability of signals. Moreover, it can overcome the noise uncertainty and restrain the primary signals. Theoretical analysis and computer simulation demonstrate that the time-domain correlation algorithm based on power spectrum cancellation is superior to traditional time-domain correlation algorithm. Key

Key words: communicationtechnology, cognitivefrequencyhopping, powerspectrumcancellation, time-domaincorrelation

中图分类号:

TN925⁺.92

李彤，苗成林，吕军. 基于功率谱对消的时域相关认知跳频谱检测算法[J]. 兵工学报, 2017, 38(9): 1754-1760.

LI Tong, MIAO Cheng-lin, LYU Jun. Time-domain Correlation Algorithm of Cognitive Frequency Hopping Based on Power Spectrum Cancellation[J]. Acta Armamentarii, 2017, 38(9): 1754-1760.

参考文献

［1］仇帅, 陈西宏, 王澈. 认知无线电在跳频通信中的应用研究［J］. 现代防御技术, 2013, 41(5):64-69.
QIU Shuai, CHEN Xi-hong, WANG Che. Application of cognitive radio in frequency hopping com-munication［J］. Modern Defence Technology, 2013, 41(5):64-69. (in Chinese)
［2］ Wang T, Song L, Saad W, et al. Cooperative spectrum sensing in cognitive radio［J］. Frequenz, 2017, 67(3/4):93-98.
［3］ Shobana S, Saravanan R, Muthaiah R. Matched filter based spectrum sensing on cognitive radio for OFDM WLANs［J］. International Journal of Engineering & Technology, 2013, 5(1):142-146.
［4］ Ling X, Wu B, Wen H, et al. Adaptive threshold control for energy detection based spectrum sensing in cognitive radios［J］. IEEE Wireless Communication Letters, 2011, 1(5):1-5.
［5］熊辉，王鹰，张颖光，等. 基于延迟相乘和能量累积的DSSS信号参数估计算法［J］. 系统工程与电子技术, 2010, 32(10): 2227-2232.
XIONG Hui，WANG Ying，ZHANG Ying-guang，et al. Parameter estimation of DSSS using delay-multiply and energy accumulation［J］. Journal of Systems Engineering and Electronics, 2010, 32(10): 2227-2232. (in Chinese)
［6］马彬, 方源, 谢显中. 一种基于信号循环平稳特征的抵御恶意模仿主用户攻击协作频谱检测算法［J］. 中国科学:信息科学, 2016,46(6):789-799.
MA Bin, FANG Yuan, XIE Xian-zhong. Robust cooperative spectrum sensing against primary user emulation attacks based on cyclostationarity［J］. Scientia Sinica : Informationis, 2016,46(6):789-799. (in Chinese)
［7］ Chung C D，Polydoros A . Parameter estimation of random FH signals using autocorrelation techniques ［J］. IEEE Transactions on Communications, 1995，43(2):1097-1106.
［8］高宪军, 李德鑫, 李娜,等. 基于功率谱对消的跳频信号检测算法［J］. 吉林大学学报：信息科学版, 2008, 26(3):238-243.
GAO Xian-jun, LI De-xin, LI Na, et al. Algorithm for frequency-hopping signals detection based on suppressing power spectrum［J］. Journal of Jilin University: Information Science Edition, 2008, 26(3):238-243. (in Chinese)
［9］方志, 贾峰. 复杂电磁环境下跳频信号检测及拼接算法［J］. 无线电工程, 2010, 40(8):13-15.
FANG Zhi, JIA Feng. Detection and mosaic algorithm of frequency-hopping signals in complicated electromagnetic environment［J］. Radio Engineering of China, 2010, 40(8):13-15. (in Chinese)

［10］齐佩汉, 司江勃, 李赞. 新型抗噪声不确定度谱分段对消频谱感知算法［J］. 西安电子科技大学学报:自然科学版, 2013, 40(6):19-24.
QI Pei-han, SI Jiang-bo, LI Zan. Novel anti-noise uncertainty spectrum sensing algorithm based on power spectral density segment cancellation［J］. Journal of Xidian University:Natural Science, 2013, 40(6):19-24. (in Chinese)
［11］齐佩汉, 司江勃, 李赞. 基于功率谱分段对消频谱感知算法研究及性能分析［J］. 电子与信息学报, 2014, 36(4): 769-774.

QI Pei-han, SI Jiang-bo, LI Zan. Research and performance analysis of spectrum sensing algorithm based on the power spectral density segment cancellation［J］. Journal of Electronics & Information Technology, 2014, 36(4): 769-774. (in Chinese)
［12］赵知劲, 吕曦, 郑仕链. 基于功率谱密度中段平均的频谱感知算法［J］. 电信科学, 2016, 32(7):53-60.
ZHAO Zhi-jin, LYU Xi, ZHENG Shi-lian. Spectrum sensing algorithm based on average value of middle part of power spectral density［J］. Telecommunications Science, 2016, 32(7):53-60. (in Chinese)
［13］赵树杰, 赵建勋. 信号检测与估计理论［M］. 北京：电子工业出版社, 2013.
ZHAO Shu-jie, ZHAO Jian-xun. Signal detection and estimation theory［M］. Beijing: Publishing House of Electronics Industry, 2013. (in Chinese)

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