Noise Analysis and Simulation Method for a Single-Slope ADC With CDS in a CMOS Image Sensor

Many mixed-signal circuits are nonlinear time-varying systems whose noise estimation cannot be obtained from the conventional frequency domain noise simulation (FNS). Although the transient noise simulation (TNS) supported by a commercial simulator takes into account nonlinear time-varying characteristics of the circuit, its simulation time is unacceptably long to obtain meaningful noise estimation results. Since the single-slope analog-to-digital converter with correlated double sampling (CDS/SS-ADC) in a CMOS image sensor (CIS) is composed of several operation phases in which the circuit topologies are different from each other, the noise cannot be estimated by the conventional FNS. This paper presents a noise estimation method for the CDS/SS-ADC that uses the FNS results while the transient noise behavior is taken into account. The proposed method provides noise estimation results closer to that of the TNS than the conventional FNS, whereas the simulation time is about the same as that of the FNS.      

Self-tuning distributed measurement fusion Kalman estimator for the multi-channel ARMA signal

For the multisensor multi-channel autoregressive moving average (ARMA) signal with white measurement noises and a common disturbance measurement white noise, when the model parameters and the noise variances are all unknown, a multi-stage information fusion identification method is presented, where the consistent fused estimates of the model parameters and noise variances are obtained by the multi-dimension recursive instrumental variable (RIV) algorithm, correlation method and Gevers-Wouters algorithm with a dead band. Substituting these estimates into the optimal distributed measurement fusion Kalman signal estimator, a self-tuning distributed measurement fusion Kalman signal estimator is presented. Its convergence is proved by the dynamic error system analysis (DESA) method, so that it has asymptotical global optimality. In order to reduce computational load, a fast recursive inversion algorithm for a high-dimension matrix is presented by the inversion formula of partitioned matrix. Especially, when the process and measurement noise variance matrices are all diagonal matrices, the inversion formula of a high-dimension matrix is presented, which extends the formula of the inverse of Pei-Radman matrix. Applying the proposed inversion algorithm, the computation of the fused measurement and fused noise variance is simplified and their computational burden is reduced. A simulation example shows effectiveness of the proposed method.     

Fast ICA应用于雷达抗主瓣干扰算法研究

压制干扰信号从主瓣进入雷达天线,会严重影响雷达的性能。通常的副瓣抗干扰技术难以奏效。本文首先给出了盲源分离应用于雷达主瓣抗干扰的信号模型,在此基础上提出了均匀噪声环境中,基于负熵最大化的快速固定点独立成分分析(Fast ICA)盲源分离算法,并用其分离接收到的干扰混合信号,最后脉压找出目标信号。仿真验证了算法用于主瓣抗干扰的有效性,并对其抗干扰性能进行了评价。仿真结果表明了算法良好的抗干扰性能,以及在分离效率上较明显的优势      

开关柜局部放电信号降噪与缺陷识别研究

文中采用暂态地电压法(TEV)进行检测,设计了四种典型的缺陷模型并搭建试验平台,分别对局部放电缺陷模型进行了实验。由于变电站现场环境复杂,需要对采集的信号进行信号降噪。针对以往小波降噪都是按照经验采取固定的分解层数的问题,提出一种Mallat算法结合最优分解层数自适应算法对含噪信号进行分离与重构,结果显示该算法可以很好地滤除噪声。对重构后的局放信号提取八种时域特征参数,并采用BP神经网络对开关柜局部放电的类型进行识别,当误差准确率δ=0.002时,放电类型的识别正确率最高,能够达到97%。     

有色噪声下基于神经-模糊网络的滤波器

提出了一种基于神经-模糊网络的自适应滤波器,它具有非线性映射和自学习能力,能够用于噪声信号的非线性建模。它不仅能够获取信号的最佳估计,并且能够克服信号处理中存在的模型和有色噪声的不确定性、不完备性。通过对仿真结果分析表明,提出的算法具有可靠、计算简便、快速等特点,模型滤波精度较高,并可实现实时滤波,具有一定的理论价值和实用价值。     

Optimal detection of coded differentially encoded QAM and PSKsignals with diversity reception in correlated fast Rician fadingchannels

The optimal sequence estimator for digital signals received over Λ different channels is derived. Each of these channels corrupts the transmitted signal by a mixture of additive white Gaussian noise (AWGN) and frequency-nonselective, correlated, fast Rician fading. By analysis it is shown that for the lth (1⩽l⩽Λ) diversity channel, the basic hardware structure of the optimal receiver consists of a combination of envelope, multiple differential, and coherent detectors. In order to reduce the overall implementation complexity, suboptimal, e.g., having a small number of differential detectors and equal combining diversity structures, versions of the optimal receivers are proposed and evaluated. Two modulation schemes are chosen in order to evaluate the overall performance of the proposed reduced-complexity diversity receivers: the π/4-shift 8-DQAM (differential quadrature amplitude modulation) and the 8-DPSK (differential phase shift keying). Bit-error-rate (BER) performance evaluation results are given. By means of computer simulation, the effect of correlation between the fading processes on the Λ diversity channels is investigated     

Experimental Investigation of Signal Sensing with Overlapped FFT Based Energy Detection

Overlapped FFT based energy detection has been proposed as a signal detection scheme in dynamic spectrum access. The overlapped FFT scheme increases the number of FFT frames to reduce the variance of squared noise and improve the detection probability. This paper evaluates the performance of the energy detection with overlapped FFT through experiments. In the experiments, different from the assumption in computer simulation of previous researches, a fixed distortion component caused by a direct current offset is observed. It is shown that the overlapped FFT scheme also works effectively under the existence of the fixed distortion. Numerical results obtained through the experiments show that the overlapped FFT scheme improves the detection probability by up to 0.15 with the noise and the fixed distortion component. The variance of the squared noise also reduces with the overlapped FFT scheme as it is expected in theoretical analysis when the fixed distortion is negligible.     

高耦合系数层叠结构片上变压器的频率无关等效电路

针对高耦合系数层叠结构的片上变压器提出了一个新型2-Ⅱ集总元件等效电路模型.主要基于解析公式提取了该模型的元件参数.由于该模型中伞部元件取值均与工作频率无关,因此该模型完全可以用于射频集成电路设计中的时域瞬态仿真及噪声分析.为了验证该模型的精度,采用台湾半导体制造有限公司(TSMC)提供的0.13μm混合信号/射频CMOS工艺实际制作了一个高耦合系数层叠结构片上变压器,并使用Agilent E8363B矢量网络分析仪测量了其S参数.测量结果表明该模型在高于两倍自谐振频率范围内均能够与测试结果很好地符合.     

Threshold-Extended FM Demodulator for Black and White Video Signal

In frequency demodulation threshold noise appears in the form of pulses of various amplitude and width. When a TV signal is transmitted these pulses can be detected at the outputs of a line-by-line subtractor, since their amplitude is in general much greater than the amplitude of the noise and of the residual video signal. Based on this principle a threshold noise suppressor (TNS) has been applied at the output of a phase-lock loop (PLL) demodulating a video signal. The TNS consists of two 64-μs delay lines and a simple logic that detects the spikes and substitutes for the signal the average between the previous and following line when a spike is present. The major and practically unique limit to the operation of the TNS is due to spikes interference, i.e., the simultaneous appearance of two pulses at the input of either line-by-line subtractor. The comparison could be made in principle between more lines with better results. However with the device consisting of only two delay lines the original threshold is lowered at least 3 dB. The same principle is also applicable to a color video signal. In the paper, details of the theory, the implementation, and the limits of the TNS are given together with experimental results.     

A new and efficient approach for estimating the accurate time-domain response of single and capacitive coupled distributed RC interconnects

This paper describes a novel yet highly efficient approach for estimating the time-domain response of capacitive coupled distributed RC interconnects. By using this method, the voltage signal at any particular point in such wires can be accurately and quickly obtained with very low computational cost. The proposed model exhibits a very good agreement with HSPICE simulations with worst-case error less than 3% and can be readily implemented in CAD analysis tools. This paper also presents an efficient model to estimate the capacitive crosstalk in high-speed very large scale integration (VLSI) circuits. Experimental results show that the maximum error of our peak noise predictions is less than 2.5%. In addition, this work presents an efficient artificial neural network (ANN)-based technique for modeling the time-domain response of interconnects and crosstalk noise. While existing fast noise estimation metrics may overestimate or underestimate the coupling noise, the simulation results demonstrate the ability of this approach to successfully predict coupling noise with a very good accuracy as compared to HSPICE in modest CPU times. Thereby, the proposed models and techniques can be used to predict the signal integrity for designing high-speed and high-density VLSI circuits.     

Combined simplified maximum likelihood and sphere decoding algorithm for MIMO system

In this article, a new system model for sphere decoding （SD） algorithm is introduced. For the 2 × 2 multipleinput multiple-out （MIMO） system, a simplified maximum likelihood （SML） decoding algorithm is proposed based on the new model. The SML algorithm achieves optimal maximum likelihood （ML） performance, and drastically reduces the complexity as compared to the conventional SD algorithm. The improved algorithm is presented by combining the sphere decoding algorithm based on Schnorr-Euchner strategy （SE-SD） with the SML algorithm when the number of transmit antennas exceeds 2. Compared to conventional SD, the proposed algorithm has low complexity especially at low signal to noise ratio （SNR）. It is shown by simulation that the proposed algorithm has performance very close to conventional SD.     

一种采用刀切法的单通道信源数估计算法

针对现有信源数估计算法不能直接用于单通道接收模型且抑噪能力较差的问题,提出了一种采用刀切法的单通道信源数估计算法。该算法首先通过间隔抽样实现了单通道接收信号多维数的转换,得到矢量化空间;然后采用刀切法将此组空间重构多个协方差矩阵,经酉变换后结果取平均;最后通过循环迭代得到最优信源数。理论分析和仿真结果表明,该算法在白、色噪声环境下能有效抑制噪声,且在低信噪比及采样点较少时能更准确估计信源数,相较于传统的估计算法,显著提高了检测性能。     

含噪语音压缩感知自适应快速重构算法

本文针对含噪语音压缩感知在低信噪比时重构性能差的问题,提出了一种自适应快速重构算法。该算法将行阶梯观测矩阵与一种新型的快速重构算法结合,并根据含噪语音信号的信噪比自适应选择最佳重构参数,使得在重构语音的同时提高了重构信噪比。算法实现简单快速,且不需要预先计算信号的稀疏度。实验结果表明,自适应快速重构算法重构性能优于基追踪算法和自适应共轭梯度投影算法以及快速重构算法,重构速度略慢于快速重构算法,但快于基追踪算法和自适应共轭梯度投影算法。      

基于和声搜索的稀布线阵旁瓣电平优化*

采用和声搜索算法研究了带约束条件的稀布线阵峰值旁瓣优化问题.探讨了稀布阵综合中的天线口径、阵元数目以及峰值旁瓣的关系,并拟合了三者的数学模型.仿真结果表明,与现有优化算法相比,改进的和声搜索算法具有更快的收敛速度;在峰值旁瓣优化中,不同阵元数目可获得最佳的天线口径;而在固定天线口径条件下,少量的阵元可获得更佳的峰值旁瓣.天线口径、阵元数目以及峰值旁瓣的相互关系可为稀布线阵的优化设计提供参考和借鉴.     

基于新型TNS启用机制的高效音频编码方法

时域噪声整型能有效地抑制由量化带来的时域上的前回音（Pre-echo）现象。提出了一种结合时域与频域，利用Levinson-Durbin及检测前回音的双重标准作为TNS的启用机制。提出了一种基于TNS启用机制的编码策略来替代计算复杂的心理模型中动态窗的算法，并验证了其在存储和计算上的开销。     

一种新的变步长LMS自适应算法及其在自适应噪声对消中的应用

许多时变步长(VSS)自适应算法已经提出用来完善标准LMS算法的性能,但实验表明这些算法容易受噪声干扰.本文介绍了一种新的变步长LMS自适应算法,这种算法保证了较小的失调,同时使算法在自适应初始阶段有较快的收敛速度.该算法的优越性在于它不受已经存在的不相关噪声的干扰.本文对该算法的收敛性和稳定性进行了分析,并将该算法应用于自适应噪声对消的仿真实验中,给出了计算机的仿真结果.     

Optimal Timing at the Relay in OFDM Based Two Way Relay Systems

In amplify and forward (AF) two way relay networks (TWRN), two sources are allowed to transmit simultaneously in the multiple access time slot. Signal misalignment at the relay occurs due to the inaccurate time slot synchronization and different propagation delay. In broadband wireless communications, the misalignment could cover several symbol intervals. In orthogonal frequency division multiplexing (OFDM) based TWRN, such signal misalignment raises question on how to choose the fast Fourier transform (FFT) window at the relay node in order to minimize the interference which will be forwarded to the sources. In this paper, the timing issue of the received superimposed signal at the relay for both sources in OFDM based AF–TWRN is investigated. The optimal timing that minimizes the total interference power at the relay is studied. The imperfect timing induced interference power at each timing point is derived. An efficient estimator is proposed for the relay to decide where to establish the FFT window boundary in order to introduce the minimum interference plus noise power based on the superimposed training block from the two source nodes. The estimator is a sliding window estimator measuring the total interference plus noise power at each timing position, and the timing position which minimizes the metric function is the optimal position to establish the FFT window. Finally, the performance of the proposed estimator is evaluated by computer simulation in the presence of different amount of signal misalignment.     

子空间投影的频谱感知算法研究

为了发现空间中的“频谱空洞”而加以利用以使频谱利用率最大化,频谱感知技术得到了广泛关注。已有基于特征矢量的频谱感知算法因涉及大量特征值分解运算导致算法运算量大,不适应实时检测。本文提出的频谱感知算法利用信号子空间和噪声子空间之间的正交性,将次用户接收信号分别投影到上述子空间,根据投影值的差异实现快速频谱感知。理论分析和仿真结果表明本文提出的算法与已有算法相比有效降低了运算量,检测性能不受噪声不确定度影响、不需要预知主用户先验知识和噪声方差,且低信噪比、小采样情况下有更优越的检测性能。      

GSVD-based optimal filtering for single and multimicrophone speech enhancement

A generalized singular value decomposition (GSVD) based algorithm is proposed for enhancing multimicrophone speech signals degraded by additive colored noise. This GSVD-based multimicrophone algorithm can be considered to be an extension of the single-microphone signal subspace algorithms for enhancing noisy speech signals and amounts to a specific optimal filtering problem when the desired response signal cannot be observed. The optimal filter can be written as a function of the generalized singular vectors and singular values of a speech and noise data matrix. A number of symmetry properties are derived for the single-microphone and multimicrophone optimal filter, which are valid for the white noise case as well as for the colored noise case. In addition, the averaging step of some single-microphone signal subspace algorithms is examined, leading to the conclusion that this averaging operation is unnecessary and even suboptimal. For simple situations, where we consider localized sources and no multipath propagation, the GSVD-based optimal filtering technique exhibits the spatial directivity pattern of a beamformer. When comparing the noise reduction performance for realistic situations, simulations show that the GSVD-based optimal filtering technique has a better performance than standard fixed and adaptive beamforming techniques for all reverberation times and that it is more robust to deviations from the nominal situation, as, e.g., encountered in uncalibrated microphone arrays.