Direction-of-arrival estimation via exploitation ofcyclostationary-a combination of temporal and spatial processing

Many modulated communication signals exhibit a cyclostationarity (or periodic correlation) property, corresponding to the underlying periodicity arising from carrier frequencies or band rates. By exploiting cyclostationarity, i.e. evaluating the cyclic correlations of the received data at certain cycle frequencies, one can extract the cyclic correlations of only signals with the same cycle frequency and null out the cyclic correlations of stationary additive noise and all other cochannel interferences with different cycle frequencies. Thus, the signal detection capability can be significantly improved. An approach for exploiting cyclostationarity that is asymptotically exact for either narrowband or broadband sources, unlike previous methods, is proposed. The method also has significant implementational advantages over the earlier techniques. The simulation results indicate a significantly better performance in some environments     

An improved cyclic beamforming method for signal DOA estimation

Modulated signals used in telecommunication are cyclostationary. This property can be exploited to improve the direction of arrival (DOA) estimation performance. In this work, we propose an improved cyclic beamforming algorithm exploiting cyclostationarity. The proposed method exploits the information of both cyclic correlation matrix and cyclic conjugate correlation matrix with different cyclic frequencies. Compared with the existing methods, the simulation results show that proposed method improves substantially the signal selectivity; also it allows an increase in resolution power.     

基于改进的循环互相关MUSIC算法的波达方向估计

给出了基于循环互相关运算的信号模型，根据该信号模型，运用改进的循环互相MUSIC算法得到了对具有循环平稳特性的空间源信号波达方向进行估计的有效方法——ICCC-MUSIC算法；定性的分析和仿真实验均表明该方法具有较好的抑制噪声和选择信号的能力，为利用天线阵列提取具有循环平稳特性的源信号提供了较好的实现方法。     

宽带谱相关时空DOA矩阵方法

本文提出了一种新的基于信号时空特征结构的二维DOA估计方法－－宽带谱相关时空DOA矩阵方法。该方法利用信号的循环平稳特性实现了对宽带信号的有效处理,同时通过空时变换将传统的一维空域处理拓展到了二维空间处理,更充分地利用了信号的时域特征,从而大大简化了阵列结构,提高了算法的性能。理论分析与仿真结果表明,该方法既继承了循环平稳方法在谱估计方面的优势,又具有原DOA矩阵方法无需二维谱峰搜索和参数配对的特点。     

一种基于多循环频率的韧性时延与多普勒频移联合估计算法

本文提出了一种基于分数低阶循环模糊函数的多循环频率时延与多普勒频移联合估计算法.该方法将分数低阶矩与循环平稳特性相结合,能够在SαS(Symmetric α Stable)脉冲噪声条件下检测信号的循环平稳特性.算法充分利用了信号的循环频率信息,具备较强的抑制干扰能力.仿真结果表明,在脉冲噪声和干扰环境中本文提出的算法均...     

基于四阶循环平稳的STBC-OFDM信号盲识别

针对非理想信道环境下多输入单输出(MISO)通信系统中STBC-OFDM信号的盲识别问题,提出了一种基于四阶循环平稳的STBC-OFDM信号盲识别算法。该方法首先对MISO通信系统中STBC-OFDM信号进行建模;然后利用STBC-OFDM信号编码矩阵的相关性,结合四阶循环平稳特性,推导了不同时延向量下接收信号块的四阶循环矩;最后根据有无尖峰盲识别空时分组码的类型。该方法采用分层识别的思想,无需信道系数、噪声功率和调制方式等先验信息,适合非合作通信场所。仿真结果表明:算法适应于低信噪比的环境,且不受调制方式、相位噪声和多普勒频移影响,实用性很强。      

一种新的近场源距离及到达角联合估计算法

该文提出一种基于三阶循环矩的近场源距离以及到达角联合估计算法。该算法充分利用了信号的循环平稳特性以及其空、时域信息,通过构造时空矩阵并进行特征分解获得二维参数的闭式估计。该方法计算简单,无需谱峰搜索,而且二维参数自动配对。与现有的方法相比,该文算法并不要求阵列具有中心对称结构,因此避免了阵列孔径的损失;此外该算法对任意分布的加性平稳噪声以及具有不同循环频率的干扰信号有较好的抑制能力。计算机仿真实验验证了该方法的有效性。     

Minimum-redundancy linear arrays for cyclostationarity-based sourcelocation

The problem of designing minimum-redundancy linear arrays (MRLAs) and appropriate augmentation techniques to be utilized with cyclostationarity-exploiting (cyclic) methods for source location is addressed. The MRLA geometries proposed in the literature for the conventional case, which apply equally well when the signals of interest exhibit cyclostationarity are not appropriate when they exhibit conjugate cyclostationarity. In this case, the problem of finding optimal MRLAs is restated as the problem of number theory that is commonly referred to as the postage stamp problem. Results of computer simulations show that in densely crowded environments, the use of cyclic methods with MRLA geometries and appropriate matrix augmentation techniques can offer a significant performance improvement on cyclic methods that do not resort to matrix augmentation techniques     

基于二阶循环累积量的多载波信号频谱检测

针对认知无线电系统中多载波信号OFDM/OQAM进行循环谱特征检测预处理要求严格的问题,提出一种以二阶循环累积量的循环频率为特征,结合循环平稳性检测的频谱感知改进算法.算法无需各种参数估计以及同步等预处理过程,理论推导及仿真结果证明,该算法能够实现低信噪比下主用户信号的有效感知,且相比于能量检测法能达到更好的检测性能.     

Linear suppression of wideband data-like interference in DS/SS communications

In this paper, a linear receiver is proposed and its performance is analyzed for direct-sequence spread-spectrum communications with wideband data-like interference. Two groups of communicators employing generalized random spreading are considered, and the signals are assumed to have harmonically related cyclostationarity periods. First, the output signal-to-interference ratio (SIR) of a general correlation receiver is derived in the frequency domain, and the key system parameters that affect the structure of the interference are identified. Then, a linear interference suppression scheme based on the maximum SIR (MSIR) criterion is proposed, and a receiver structure similar to the cyclic Wiener filter is derived. Numerical results show that the proposed linear MSIR receiver significantly outperforms the conventional correlation receiver by effectively suppressing the wideband data-like interference.     

有效扩展阵列孔径的伪快拍构造

许多通信信号具有循环平稳特性。针对广义信号模型和窄带信号模型，利用前后向循环相关函数分别构造出一种新的伪快拍，由此获得了一个孔径扩展一倍的虚拟阵列。对这两种伪快拍应用传统的MUSIC算法时，可分别比SC-SSF和cy-clic-MUSIC算法检测多一倍的信号和获得更高的估计分辨率。仿真结果证明了该结论。     

一种α稳定分布噪声下OFDM信号调制识别与参数估计算法

正交频分复用（OFDM,Orthogonal Frequency Division Multiple）信号的调制识别与参数估计是非协作通信领域的重要研究内容.为了解决α稳定分布噪声下OFDM信号调制识别与参数估计困难的问题,提出一种广义循环平稳的盲处理算法.该算法首先对接收信号进行非线性变换,推导出接收信号的广义循环自相关函数表达式,分析了单载波调制信号与OFDM信号的广义循环自相关函数特性,并给出了OFDM信号的广义循环自相关函数与待估参数之间的关系.然后,基于分析结论,利用广义循环自相关函数构造调制识别特征完成OFDM信号与单载波信号的调制方式自动分类;最后,针对OFDM信号的调制参数估计问题,提出了一种基于广义循环自相关函数的调制参数估计算法.理论分析与仿真结果表明,在α稳定分布噪声环境下,该算法可以有效实现OFDM信号调制识别与参数估计,且算法不依赖接收信号的先验信息,可以直接对中频接收信号进行处理.     

Blind adaptive spatiotemporal filtering for wide-bandcyclostationary signals

An algorithm that blindly adapts spatiotemporal filters to extract from sensor array data one or more desired signals having known cyclostationarity properties is presented. This method, referred to as the spectral self-coherence restoral (SCORE) method, can accommodate multiple signals of interest, multiple interferers, and unknown noise, does not require complicated searches, and requires knowledge of only a cycle frequency of the desired signal. The SCORE method is reinterpreted using the framework of canonical correlation analysis and extended to accommodate wide-band received data that do not adhere to the narrow-band assumption. Background information on cyclostationarity is presented, and canonical correlation analysis is explained briefly. The SCORE method for wide-band array data is from the perspective of canonical correlation analysis. Results of computer simulations are presented to illustrate the performance of the method and to compare it with that of the minimum-variance distortionless response beamformer     

Cyclostationarity-based filtering for narrowband interferencesuppression in direct-sequence spread-spectrum systems

This paper addresses the problem of narrowband interference suppression in direct-sequence spread-spectrum (DS/SS) techniques, which have been adopted to implement code division multiple access (CDMA) systems for wireless mobile communications. The theory of cyclic Wiener filtering, based on the cyclostationarity assumption for the signals involved in the reception problem, is applied to design single-channel adaptive frequency-shift filters which exploit both temporal and spectral correlation properties, i.e., the correlation between time- and frequency-shifted versions of the received signal. The numerical results show that receiving structures based on the proposed cyclostationarity-based interference suppression schemes largely outperform receivers that utilize conventional linear time-invariant suppressors, when they operate in highly contaminated interference environments     

Blind channel identification and equalization withmodulation-induced cyclostationarity

Recent results have pointed out the importance of inducing cyclostationarity at the transmitter for blind identification and equalization of communication channels. This paper addresses blind channel identification and equalization relying on the modulation-induced cyclostationarity, without introducing redundancy at the transmitter. It is shown that single-input single-output channels can be identified uniquely from output second-order cyclic statistics, irrespective of the location of channel zeros, color of additive stationary noise, or channel order overestimation errors, provided that the period of modulation-induced cyclostationarity is greater than half the channel length. Linear, closed-form, nonlinear correlation matching, and subspace-based approaches are developed for channel estimation and are tested using simulations. Necessary and sufficient blind channel identifiability conditions are presented. A Wiener cyclic equalizer is also proposed     

调制指数为整数和半整数的连续相位调制信号的盲检测

根据调制指数为整数和半整数的连续相位调制(CPM)信号的循环平稳特性,该文提出一种在未知编码序列、载频、码元宽度及峰值频率偏移等参数的情况下对CPM信号的盲检测方法。该方法是对传统循环谱分析器的改进。仿真实验证明该方法具有良好的检测性能并容易实现,具有广阔的工程应用前景。     

基于小波—循环谱的新型识别技术

在通信系统中经常遇到的许多非平稳信号都具有循环平稳特性,可以用循环谱的方法来识别.但当信号本身的频谱结构比较复杂、噪声成分过大或噪声本身也具有循环平稳特性时,解调效果就不是很理想.针对循环谱识别信号的这一局限性,文中在介绍循环谱原理和识别特性的基础上,研究了几种典型通信信号的谱相关性,并提出了基于小波包与循环谱的识别技术,即先采用小波包进行软阈值消噪,再结合各自不同的循环谱特性进行识别.通过大量实验仿真表明,该方法具有很好的噪声抑制能力,能达到较好的识别效果.     

射频干扰环境下OFDM系统的盲信号干扰噪声比估计

基于OFDM信号的循环平稳特性,提出一种在射频干扰环境下OFDM系统的盲信号干扰噪声比估计方法。通过分析发送信号,射频干扰信号以及高斯白噪声的周期自相关函数能量分布规律,选取合适的延时变量和循环频率在功率谱域能有效分离信号功率和干扰加噪声功率分量,从而估计出信号干扰噪声比值。计算机仿真结果表明,和经典的二阶四阶矩(M2M4, second-order and fourth-order moments)盲信号干扰噪声比估计方法相比,新方法不仅能够有效估计射频干扰环境下OFDM系统的信号干扰噪声比值,而且无论是估计性能还是复杂度都优于M2M4方法;同时在快衰落Rayleigh信道下,新方法也能有效的估计出信号干扰噪声比值。进一步,所提方法具有对射频干扰信号密度不敏感的优点。     

Adaptive multistage beamforming using cyclic higher orderstatistics (CHOS)

A new blind beamforming algorithm for signals that exhibit higher order cyclostationarity is presented. Exploiting some previous theoretical developments, we show how cyclic cumulants of the received signals can be used to obtain the weights of the beamformer that perform blind extraction. The method is based on a spatial interpretation of a deconvolution procedure known as the super-exponential algorithm. The basic block processing algorithm is made fully adaptive using an adaptive URV scheme and applied to a typical mobile communications scenario where several cochannel interferers corrupt the signals of interest     

基于信号共轭周期平稳特性的MIMO信道估计方法

MIMO系统中,由于各天线间干扰以及码间干扰等问题的存在,信道估计性能成为影响系统性能的决定性因素。直接利用接收信号的二阶统计特性进行信道估计是目前比较通用的方法之一。本文基于信号的二阶共轭周期平稳特性。提出了一种适用于MIMO系统的信道估计方法,该方法直接利用接收信号的共轭周期自相关函数间的关系,消除了系统的码间干扰(ISI)和信道间的互扰(CCI),分离出信道矩阵的各个元素分别加以估计。该估计算法不需要事先知道信道的准确阶数,整个估计结果不受信道阶数过估计的影响。由于一般的信号不具有共轭周期平稳特性,因而本文同时还提出了一种在MIMO系统中构造和处理二阶共轭周期平稳特性信号的方法。本文最后给出的仿真结果显示所提的估计方法具有良好的估计性能。