基于周期平稳的盲信噪比估计方法

过采样和成型滤波引入了信号的周期平稳性。基于对信号的周期平稳统计量的分析，提出了一种高斯白噪声信道下的盲信噪比估计方法。对信号的调制方式没有要求，也不需要发送端发送已知数据。蒙特卡罗仿真结果证明，在较宽的信噪比范围内，该方法的性能优于二阶四阶矩方法（M2M4）、信号方差比（SVR）方法等其他经典的盲信噪比估计方法。分析了估计的克拉美-罗下界，作为估计的绝对性能的参照。     

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     

On channel identification based on second-order cyclic spectra

Gardener (1991) presented an interesting use of cyclostationarity for channel identification in PAM data communication systems. The present paper presents new results that address the identification of linear rational channels with higher than minimum bandwidth based on the use of second-order cyclic statistics. Unlike the approach taken by Gardener, the present authors show that channel identification is achievable for a class of linear channels without the need for a pilot tone or training periods. Moreover, channel identification based on cyclic statistics does not preclude Gaussian or near-Gaussian inputs     

Support vector method for robust ARMA system identification

This paper presents a new approach to auto-regressive and moving average (ARMA) modeling based on the support vector method (SVM) for identification applications. A statistical analysis of the characteristics of the proposed method is carried out. An analytical relationship between residuals and SVM-ARMA coefficients allows the linking of the fundamentals of SVM with several classical system identification methods. Additionally, the effect of outliers can be cancelled. Application examples show the performance of SVM-ARMA algorithm when it is compared with other system identification methods.     

Blind wideband spatio-temporal filtering based on higher-order cyclostationarity properties

In this paper, a new method for blind minimum mean-square error (MMSE) spatio-temporal signal filtering is proposed. To obtain a blind version of the MMSE filter, the proposed method utilizes the signal selectivity property of the higher order cyclostationary statistics (HOCS) exhibited by the signal of interest. An accurate estimate of the transfer function of the MMSE filter is obtained also in the presence of strong frequency-overlapped interfering signals, which would render standard stationarity-based techniques ineffective. The method is useful when the desired signal cannot be accurately extracted by exploiting its second-order cyclostationarity properties because they are too weak and/or they are shared by the interference and noise signals as well. The performance analysis, which is carried out by computer simulations in the case of quadrature amplitude modulated (QAM)-modulated signals with partially overlapping bands, substantiates the effectiveness of the proposed method.     

基于GPS循环平稳特性的盲波束形成算法改进

在卫星导航自适应阵列抗干扰中,为避免先验信息误差和阵列误差对自适应波束形成性能的影响,可采用基于正交投影和导航信号循环平稳特性的盲波束形成算法(OCAB)。针对GPS信号,采用周期延迟信号处理的OCAB算法(CDOCAB)时,由于数据长度有限,噪声循环自相关函数估计量不为零,因此将影响循环平稳方法的性能,而采用解重扩数据辅助的OCAB算法(DS-OCAB)可以避免噪声估计误差的影响。将两种算法进行仿真比较,仿真结果表明,DS-OCAB算法可在少数据量的情况下保证算法性能不下降,提高算法的稳健性。     

Blind MIMO FIR channel identification based on second-order spectra correlations

We consider a problem of identifying a multiple-input multiple-output (MIMO) finite impulse response (FIR) system excited by colored inputs with known statistics. We propose a new, nonlinear optimization-based method that involves the power spectra and cross-spectra of the system output. The proposed algorithm is tested for the case of cyclostationary inputs (CDMA scenario) and stationary inputs (SDMA scenario). Simulation results indicate that the proposed scheme works well, even for large order systems, and is robust to noise and channel length mismatch.     

Blind channel identification based on second-order statistics: afrequency-domain approach

In this communication, necessary and sufficient conditions are presented for the unique blind identification of possibly nonminimum phase channels driven by cyclostationary processes. Using a frequency domain formulation, it is first shown that a channel can be identified by the second-order statistics of the observation if and only if the channel transfer function does not have special uniformly spaced zeros. This condition leads to several necessary and sufficient conditions on the observation spectra and the channel impulse response. Based on the frequency-domain formulation, a new identification algorithm is proposed     

利用调制引入循环平稳的CDMA盲信道估计

针对CDMA系统给出了一种新颖的盲辨识方法.它利用了恒模复序列调制产生的循环平稳性,其特色是,在接收机上可以根据循环统计量的支撑的不同,将各个用户的二阶循环统计量分离开来,每个用户形成自己的小规模子空间.采用已成熟的子空间方法,可以识别出不同的用户各自的片率传输信道,以便于均衡和检测.文中给出了自己的信道可辨识性的条件和证明,提出了辨识算法,并对算法进行了模拟.方法简单明了,适合于CDMA上行链路信道.     

脉冲噪声环境下改进的顽健循环时延估计算法

研究了脉冲噪声环境下循环平稳信号的时延估计问题,针对脉冲噪声环境中基于传统二阶谱相关函数的时延估计方法性能退化问题,提出了基于分数低阶循环谱的改进顽健算法。相对于传统算法,新算法对脉冲噪声、高斯噪声、干扰信号都具有较好的抑制作用。仿真结果证明了算法的有效性和顽健性。     

基于ARMA的风电功率预测

风电场风电功率预测对优化电网调度,提高风电场容量系数具有重要意义。对采样时间为15 min的风电功率时间序列建立自回归移动平均模型,并对风电场输出功率分别进行短期和中长期预测,同时分别分析了4台风电机组和58台风电机组的汇聚对预测结果的误差影响等。研究结果表明,利用ARMA模型在预测短期及中长期风电功率时的日前预测平均相对误差为0.087 1,实时预测误差为0.15,同时4台风电机组和58台风电机组的汇聚的平均相对误差为0.293 1和0.194 3,风电机组在集中开发方式下风电功率预测误差减小。     

Blind two-input-two-output FIR channel identification based onfrequency domain second-order statistics

We present an analytical solution to the two-input-two-output blind crosswise mixture identification based on eigenvalue decomposition of second-order spectra correlations. The sources are independent and non-white, but otherwise, we consider their statistics to be unknown. We show that the cross channels cannot be uniquely determined by the analysis of the frequency domain covariance alone due to the unknown eigenvector permutations. However, the problem can be attacked with the help of two invariant indices that are immune to these permutations. Using these indices together with standard reconstruction-from-phase techniques, we show that the channels can be uniquely determined. Our theoretical results lead to a novel frequency domain second-order algorithm that identifies the unknown channels     

一种基于循环自相关分析的雷达编队目标架次估计

在研究编队目标回波多普勒频率变化的基础上,提出一种基于循环自相关分析的编队目标架次估计新方法.该方法利用编队目标回波可近似看作多个频率相近、幅度恒定、调频系数相等的LFM信号叠加的特点,采用循环自相关估计回波信号的调频系数,再利用分数阶傅立叶变换对编队目标架次进行估计.该方法计算简单,易于工程实现,相对Fourier变换和WVD具有较高的分辨能力.实测数据实验表明了方法的有效性,实现了较短数据长度下的雷达编队目标架次的有效估计.     

基于累积量和循环平稳参量的OFDM信号盲检测

为解决正确检测和识别OFDM信号的问题,提出一种新的OFDM盲检测方案.该方案在缺乏先验知识的条件下,充分利用OFDM时域包络渐近高斯性分布的特点,对已有基于累积量的识别特征参量提取进行改进,有效的抑制了瑞利衰落及高斯噪声对接收端信号调制模式识别性能的影响.在此基础上,为改善现有累积量算法无法区分OFDM与高斯信号的不足,应用二阶循环平稳性分析分选OFDM及高斯信号,构成OFDM信号检测的总体方案.仿真实验评估了该方案的有效性:验证该方案可在瑞利衰落信道下正确识别OFDM调制模式并在多径信道及较低信噪比下分选出OFDM信号.     

基于PID控制算法的二阶惯性纯滞后系统设计

工业控制过程中的大滞后现象会增加控制系统的风险和管理难度,而传统控制系统设计在控制响应的稳定性输出和积分绝对误差方面都难以满足工业控制的基本需求,为此提出一种基于改进PID控制算法的二阶惯性纯滞后系统设计。详细分析了二阶惯性纯滞后抑制系统的硬件构成,在控制器芯片的选择方面,采用基于ARM和FPGA的双芯片设计,以提高系统的稳定性;在算法设计方面,对传统的PID控制算法进行了优化和改进,开发了一种信息传递函数,并求解出函数的相频特征与幅频特征,最后给出基于改进PID算法的完整控制流程。仿真数据结果表明,提出的控制系统设计在响应曲线的输出方面更接近于系统设计值,在ISE值的控制方面也优于传统控制系统设计。     

ARMA spectral estimation based on partial autocorrelations

This paper presents a new method for estimating the coefficients of autoregressive moving-average parameters of stationary time series. The method is based on computing the sample autocorrelations of the given time series and fitting an ARMA model so as to approximate the partial autocorrelations in a least-squares sense. When the given time series are characterized by spectral zeroes near the unit circle, they tend to have relatively long sequences of nonzero partial autocorrelations; hence the new method is especially effective in such cases. This paper contains a derivation of all necessary mathematical details, as well as several numerical examples illustrating the performance.     

Efficient channel blind estimator for multiuser system with conjugate cyclostationarity

The problem of blind channel identification in a multiuser system is considered in this article. For this purpose, a blind identification algorithm is proposed based on the conjugate cyclostationarity of the received signal. The new approach contains a two-stage identification procedure. First, the separation technique in the cyclic domain is used to separate the second-order cyclic statistics for each user. Second, a subspace algorithm based on the rational subspace theory is exploited to estimate the desired channel. Theoretical analysis and simulation results show that this algorithm is suitable for a multiuser system. Compared with other methods, the algorithm shows good performance even in a bad situation when the number of users is large and the diversity condition is unavailable.     

Key distribution system based on identification information

A key distribution system (KDS) based on identification information (ID-based KDS) is presented. The system is founded on the Diffie-Hellman public key distribution scheme and has an identity authentication function. It uses an individual user's identification information instead of the public file used in the Diffie-Hellman scheme. It does not require any services of a center to distribute work keys or users to keep directories of key-encrypting keys. Therefore, key management in cryptosystems can be simplified by adopting the ID-based KDS. Two kinds of identity-based key distribution system are proposed and applied to actual communication networks. One uses two-way (interactive) communication to distribute work keys, while the other uses one-way communication. Modular exponentiations of large numbers, used in the systems, are implemented with digital signal processors.<>     

Operation data prediction algorithm of information system based on discrete second-order difference

Wireless Networks - This study proposes an algorithm for predicting the running data of information systems based on discrete second-order difference clustering. The wide stationary time series...     

Blind identification of ARMA channels with periodically modulatedinputs

Previous results have pointed out the importance of inducing cyclostationarity at the transmitter for blind identification of FIR communication channels. The present paper considers the blind identification problem of an ARMA (p,q) channel by exploiting the cyclostationarity induced at the transmitter through periodic encoding of the input. It is shown that causal and stable ARMA (p,q) channels can be uniquely identified from the output second-order cyclic statistics, irrespective of the location of channel poles and zeros and color of additive stationary noise, provided that the cyclostationary input has at least q+1 nonzero cycles