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论文:2016,Vol:34,Issue(2):262-267 |
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引用本文： |
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刘宁, 史浩山, 刘利平, 杨博. 基于随机矩阵的新型频谱盲感知方法[J]. 西北工业大学学报 |
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Liu Ning, Shi Haoshan, Liu Liping, Yang Bo. A Novel Blind Spectrum Sensing Algorithm Based on Random Matrix[J]. Northwestern polytechnical university |
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| 基于随机矩阵的新型频谱盲感知方法 |
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| 刘宁1,2, 史浩山2, 刘利平3, 杨博1 |
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1. 西北工业大学 无人机特种技术重点实验室, 陕西 西安 710065;
2. 西北工业大学 电子信息学院, 陕西 西安 710072;
3. 中兴西安研究所, 陕西 西安 710065 |
| 摘要: |
| 针对传统频谱感知算法需要预先估计噪声方差且当存在噪声不确定度时,检测性能降低的特点,提出一种基于随机矩阵的改进型频谱盲感知算法(M-CMME)。该算法通过分析协方差矩阵最大特征值极限分布特性,分析并利用采样协方差矩阵特征值与信号平均能量的关系,推导设定虚警概率条件下判决门限的闭式表达式。该算法不需要预先知道授权用户信号的先验知识,且能够有效克服噪声不确定度的影响。仿真结果显示,当噪声方差估计存在偏差的情况下,该算法具有较强的鲁棒性,且在较少采样点、低信噪比、较少阵元数情况下能够获得比CMME更优的检测性能。 |
| 关键词:
频谱感知
特征值
噪声不确定度
随机矩阵理论
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| A Novel Blind Spectrum Sensing Algorithm Based on Random Matrix |
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| Liu Ning1,2, Shi Haoshan2, Liu Liping3, Yang Bo1 |
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1. Science and Technology on UAV Laboratory, Northwestern Polytechnical University, Xi'an 710065, China;
2. Department of Electronics and Engineering, Northwestern Polytechnical University, Xi'an 710072, China;
3. Xi'an Institute of ZTE, Xi'an 710065, China |
| Abstract: |
| In order to improve the detection performance of traditional spectrum sensing under low SNR, a spectrum sensing algorithm (M-CMME) is proposed. The proposed algorithm analyzes the characteristic of limiting eigenvalue distribution, analyzes and utilizes the relation of energy and eigenvalues of sample matrix and then deduces the form expression of decision threshold under constant false alarm ratio. The algorithm, we believe, does not need estimating the noise power and exhibits a good robustness against noise uncertainty. Simulation results show preliminarily that, when there is a deviation of the noise estimation, the algorithm can obtain strong robustness and this algorithm can get better detection performance than CMME with fewer samples, lower SNR and fewer antennas. |
| Key words:
algorithm
antenna array
computer simulation
covariance matrix
eigenvalues and eigen functions
estimation
matrix algebra
Matlab
Monte Carlo methods
wavelength
blind spectrum sensing
Constant false alarm ratio
CMME
CDF(cumulative distribution function)
ED
MDE
MME(maxim minimum eigenvalue detection)
PU
RMT(random matrix theory)
Wishart random matrix
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| 收稿日期: 2015-10-20
修回日期:
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| DOI: |
| 基金项目: 2012航天科技支撑基金(2012HTXGD)与西北工业大学基础研究基金(3102014KYJD014)资助 |
| 通讯作者:
Email： |
| 作者简介: 刘宁(1976-),女,西北工业大学工程师、博士研究生,主要从事通信工程与信号处理、数据链仿真及电磁兼容环境适应性技术研究。
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| 相关功能 |
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| 作者相关文章 |
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| 刘宁 在本刊中的所有文章 |
| 史浩山 在本刊中的所有文章 |
| 刘利平 在本刊中的所有文章 |
| 杨博 在本刊中的所有文章 |
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参考文献: |
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[1] Mitola J, Maguire G Q. Cognitive Radios:Making Software Radios More Personal[J]. IEEE Personal Communications, 1999, 6(4):13-18
[2] Digham F F, Alouini M S, Simon M K. On the Energy Detection of Unknown Signals over Fading Channels[J]. IEEE Trans on Wireless Communication, 2007, 55(1):21-24
[3] Cardoso L S, Debbah M, Bianchi P, et al. Cooperative Spectrum Sensing Using Random Matrix Theory[C]//International Symposium on Wireless Pervasive Computing, Santorini, 2008:334-338
[4] Zeng Y H, Koh C L, Liang Y CH. Maximum Eigenvalue Detection:Theory and Application[C]//IEEE International Conference on Communications, Beijing, 2008:4160-4164
[5] 曹开田, 杨震. 基于最小特征值的合作频谱感知新算法[J]. 仪器仪表学报, 2011, 32(4):736-741 Cao Kaitian, Yang Zhen. Novel Cooperative Spectrum Sensing Algorithm Based on the Smallest Eigenvalue[J]. Chinese Journal of Scientific Instrument, 2011, 32(4):736-741(in Chinese)
[6] Zeng Yonghong, Liang Yingchang. Eigenvalue-Based Spectrum Sensing Algorithms for Cognitive Radio[J]. IEEE Trans on Communications, 2009, 57(6):1784-1793
[7] Zeng Yonghong, Liang Yingchang. Maximum-Minimum Eigenvalue Detection for Cognitiv Radio[C]//The 18th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, 2007:1-5
[8] 王磊, 郑宝玉, 李雷. 基于随机矩阵的协作频谱感知[J]. 电子与信息学报, 2009, 31(8):1925-1929 Wang Lei, Zheng Baoyu, Li Lei. Cooperative Spectrum Sensing Based on Random Matrix Theory[J]. Journal of Electronocs & Information Technolgy, 2009, 31(8):1925-1929(in Chinese)
[9] Tulino A M, Verdu S. Random Matrix Theory and Wireless Communications[M]. Hanover,USA:Now Publisher Inc, 2004:3-73
[10] By Iain M. Johnstone On the Distribution of the Largest Eigenvalue in Principle Components Analysis[J]. Annals Statistics, 2001,29(2):295-327
[11] Johansson K. Shape Fluctuations and Random Matrices[J]. Commun Math Phys, 2000, 209(2):437-476 |
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