Compressive wideband spectrum blind detection based on high-order statistics

doi:10.11772/j.issn.1001-9081.2015.11.3261

Journal of Computer Applications ›› 2015, Vol. 35 ›› Issue (11): 3261-3264.DOI: 10.11772/j.issn.1001-9081.2015.11.3261

• Network and communications • Previous Articles Next Articles

Compressive wideband spectrum blind detection based on high-order statistics

CAO Kaitian^1,2, CHEN Xiaosi¹, ZHU Wenjun³

1. College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing Jiangsu 210003, China;
2. Key Laboratory of Broadband Wireless Communication and Sensor Network Technology of the State Education Ministry, Nanjing University of Posts and Telecommunications, Nanjing Jiangsu 210003, China;
3. College of Overseas Education, Nanjing University of Posts and Telecommunications, Nanjing Jiangsu 210023, China

Received:2015-05-31 Revised:2015-07-05 Published:2015-11-13

基于高阶统计量的压缩宽带频谱盲检测方法

曹开田^1,2, 陈晓思¹, 朱文俊³

1. 南京邮电大学通信与信息工程学院, 南京 210003;
2. 南京邮电大学宽带无线通信与传感网技术教育部重点实验室, 南京 210003;
3. 南京邮电大学海外教育学院, 南京 210023

通讯作者: 曹开田(1978-),男,湖北武汉人,副教授,博士,主要研究方向:无线通信、网络信号处理、压缩感知、多输入多输出无线通信网络.
作者简介:陈晓思(1991-),女,湖北荆州人,硕士研究生,主要研究方向:无线通信、网络信号处理; 朱文俊(1994-),男,江苏常州人,主要研究方向:信号检测.
基金资助:
国家973计划项目(2011CB302903); 国家自然科学基金资助项目(61201161); 江苏省博士后基金资助项目(1301002B).

Abstract

Abstract: In cognitive radio network, wideband spectrum sensing is faced with the technical restrictions of high-speed Analog-to-Digital Converter (ADC). To cope with this issue, the probability distribution of high-order decision statistics for wideband spectrum sensing fed by compressed observations based on Compressive Sampling (CS) theory was deduced, and then a High-Order Statistics (HOS)-based Compressive Wideband Spectrum Blind Detection (HOS-CWSBD) scheme with theses compressive measurements was proposed in this paper. The proposed algorithm need neither the prior acknowledge of the transmitted signal, nor the signal recovery. Both theoretical analyses and simulation results show that the proposed scheme has lower computational complexity and more robustness to the noise uncertainty compared to the traditional spectrum sensing schemes based on CS requiring the signal recovery and the HOS-based spectrum sensing scheme with Nyquist samples.

Key words: High-Order Statistics (HOS), Compressive Sampling (CS), compressive signal processing, blind detection

摘要： 针对认知无线网络中宽带频谱感知受到高速模数转换器(ADC)器件的技术限制,利用压缩感知理论(CS),采用压缩信号处理技术,直接对压缩观测数据进行分析,推导出宽带频谱检测的高阶判决统计量的概率分布特性,并在此基础上提出了一种基于高阶统计量的压缩宽带频谱盲检测算法(HOS-CWSBD).该算法无需任何有关主用户(PU)信号的先验知识、也无需事先重构出原信号就能实现宽带频谱检测.理论分析和仿真结果均表明,与传统的基于压缩感知理论且需要信号重构的压缩频谱感知算法以及基于Nyquist采样数据的非压缩宽带频谱感知算法相比,该算法具有计算复杂度低、感知性能稳定等优点.

关键词: 高阶统计量, 压缩采样, 压缩信号处理, 盲检测

CLC Number:

TN92

CAO Kaitian, CHEN Xiaosi, ZHU Wenjun. Compressive wideband spectrum blind detection based on high-order statistics[J]. Journal of Computer Applications, 2015, 35(11): 3261-3264.

曹开田, 陈晓思, 朱文俊. 基于高阶统计量的压缩宽带频谱盲检测方法[J]. 计算机应用, 2015, 35(11): 3261-3264.

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Compressive wideband spectrum blind detection based on high-order statistics

基于高阶统计量的压缩宽带频谱盲检测方法

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