一种适用于认知超宽带的CUSUM频谱感知算法

doi:10.3969/j.issn.1001-2400.2011.06.029

J4 ›› 2011, Vol. 38 ›› Issue (6): 173-178.doi: 10.3969/j.issn.1001-2400.2011.06.029

一种适用于认知超宽带的CUSUM频谱感知算法

宋晓鸥1;向新1;毕笃彦1;陈顺方2

(1. 空军工程大学工程学院，陕西西安 710038；
2. 航空电子系统综合技术国防科技重点实验室，上海 200233)

收稿日期:2011-05-23 出版日期:2011-12-20 发布日期:2011-11-29
通讯作者: 宋晓鸥
作者简介:宋晓鸥(1984-)，女，空军工程大学博士研究生，E-mail: e_miracle@163.com
基金资助:
航空科学基金资助项目(20095596014)

Novel CUSUM spectrum sensing algorithm in cognitive UWB

SONG Xiao'ou^1;XIANG Xin¹;BI Duyan¹;CHEN Shunfang²

(1. Engineering College, Air Force Eng. Univ., Xi'an 710038， China;
2. National Key Lab. of Sci. and Tech. on Avionics System Integration, Shanghai 200233， China)

Received:2011-05-23 Online:2011-12-20 Published:2011-11-29
Contact: SONG Xiao'ou

摘要/Abstract

摘要：

提出了一种新的认知超宽带频谱感知算法，该算法适合检测低平均信噪比、低占空比的超宽带脉冲信号，且具有复杂度低、检测延迟性能优越的特点．论文根据超宽带脉冲信号特性，给出形式统一的低占空比接收信号概率密度函数表达式，并采用累加和(CUSUM)算法实施检测．仿真结果表明，该算法对低占空比信号具有良好的适应性，有效克服了能量检测的信噪比门限效应，且检测延迟性能优越．

关键词: 认知超宽带, 频谱感知, 累加和, 检测延迟

Abstract:

A novel Cognitive UWB spectrum sensing algorithm is proposed and evaluated, which enables the detection of the low average SNR and low duty ratio signal with low complexity and small detection delay. An uniform probability density function of the low duty ratio received signal is constructed based on the characteristic of the UWB pulse signal. CUSUM test is introduced to implement the detection. Theoretical analysis indicates that the proposed algorithm is suitable for low duty ratio signal detection. Compared with the energy detection algorithm, the proposed algorithm conquers the SNR wall phenomenon, with superior detection delay performance. Furthermore, the theoretical analysis results are proved by simulations.

Key words: cognitive UWB (CUWB), spectrum sensing, cumulate sum (CUSUM), detection delay

中图分类号:

TN92

宋晓鸥;向新;毕笃彦;陈顺方. 一种适用于认知超宽带的CUSUM频谱感知算法[J]. J4, 2011, 38(6): 173-178.

SONG Xiao'ou;XIANG Xin;BI Duyan;CHEN Shunfang. Novel CUSUM spectrum sensing algorithm in cognitive UWB[J]. J4, 2011, 38(6): 173-178.

参考文献

［1］ Lansford J. Cognitive UWB Radio: a Smarter Radio for Smarter Products ［C］//Proceeding of Systems, Man and Cybernetics: 36. San Antonio: IEEE SMC, 2009: 2293-2296.
［2］ Agrawal T, Lakkundi V, Griffin A. Compressed Sensing for OFDM UWB Systems ［C］//Proc of Radio and Wireless Symposium. Phoenix: IEEE, 2011: 190-193.
［3］ Anis M, Ortmanns M, When N. RF Spectrum Sensing Technique for Cognitive UWB Radio Network ［C］//IEEE International Conference on Electronic, Circuits ＆ Systems. Jounie Lebanon: IEEE, 2010: 506-509.
［4］丁汉清, 杨家玮, 赵志远. 认知无线电中自适应分步合并协作频谱感知算法［J］. 西安电子科技大学学报, 2010, 37(4): 665-670.
Ding Hanqing, Yang Jiawei, Zhao Zhiyuan. Adaptive Step by Step Combination Cooperative Spectrum Sensing in Cognitive Radio Systems ［J］. Journal of Xidian University, 2010, 37(4): 665-670.
［5］赵树杰, 赵建勋. 信号检测与估计理论［M］. 北京: 清华大学出版社, 2009: 250-267.
［6］ Tandra R, Sahai A. SNR Walls for Signal Detection［C］//Proc of Special Topics in Signal Processing: 2. San Luis Obispo: California Polytechnic and State University, 2008: 4-17.
［7］ Zhang Wu, Mei Yang. A CUSUM Chart Using Absolute Sample Values to Monitor Process Mean and Variance［C］//Proc of Industrial Engineering Management. Hong Kong: IEEE, 2009: 414-418.
［8］ Lai Lifeng, Fan Yijia, Poor H V. Quickest Detection in Cognitive Radio: A Sequential Change Detection Framework ［C］//Proc of GLOBECOM. New Orleans: IEEE, 2008: 1-6.
［9］ Li H, Li C, Dai H. Quickest Spectrum Sensing in Cognitive Radio ［C］//Proc Conf on Information Science and Systems. Princeton: IEEE, 2008: 203-208.
［10］ Jin B, Zhang S. Serial Compressed Sensing Communication System for UWB Impulse Radio in Bursty Applications ［J］. Eletronics Letters, 2011(28): 412-414.

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一种适用于认知超宽带的CUSUM频谱感知算法

Novel CUSUM spectrum sensing algorithm in cognitive UWB

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