Systolic architectures for adaptive multichannel least squares lattice filters

A family of systolic array architectures for adaptive multichannel least squares lattice (MLSL) filters is presented. These architectures are based on a recently developed algorithm that provides an efficient, numerically sound, and well-structured set of recursions for realizing MLSL filters. The algorithm is based on the recursive QR decomposition of the forward and backward error correlation matrices. Form input channels andp filter taps,O(pm ²) computations are required per time step. Numerous space-time tradeoffs are available in mapping the algorithm's recursions to systolic architectures, leading to the architectural family presented here.Los Alamos National Laboratory is operated by the University of California for the United States Department of Energy under contract W-7405-ENG-36.     

A new algorithm for linear-phase paraunitary filter banks with pairwise mirror-image frequency responses

Subband filter banks have attracted much attention during the past few years. In this paper, an efficient design algorithm, which leads to linear-phase paraunitary filter banks with pairwise mirror-image frequency responses, is revisited and further studied. New lattice structures are presented to extend the algorithm to the case where the number (M) of channels is odd. Design examples of filter banks with 3 and 5 channels are presented.     

Performance of the variable-length stochastic gradient lattice filter in adaptive noise cancellation of nonstationary signals—A simulation case study

The variable-length filter for adaptive noise cancellation of nonstationary signals is introduced. The optimum length of number of filter stages is shown to be chosen in terms of the algorithm noise. It is shown that such an optimal filter can always act positively even when the cross-correlation between the input channels is close to zero. The performance of the variable-length stochastic gradient (SG) lattice filter is theoretically studied for a given nonstationary (time variable) system simulated on a computer. The results of the simulation are then compared with theory. It is shown that, for nonstationary signals, the variable-length filter yields a better noise reduction than the conventional LMS (Widrow et al., 1976) and lattice filters.     

Adaptive joint maximum‐likelihood detection and minimum‐mean‐square error with successive interference canceler over spatially correlated multiple‐input multiple‐output channels

We develop an efficient hard detector for multiple‐input multiple‐output (MIMO) channels, which adaptively combines maximum‐likelihood detection (MLD) and minimum‐mean‐square error with a successive interference canceler together. Unlike the conventional joint combination scheme, which may suffer from considerable degradation in bit‐error‐rate (BER) performance over correlated channels and where only one data stream is detected by MLD, our proposed scheme adaptively controls the number of data streams to be detected by MLD based on an analytical characterization of reliability for the detection. Simulation results illustrate that near‐optimal BER performance can be obtained at much lower computational complexity by the proposed method as compared with existing techniques, regardless of the spatial correlation of the MIMO channels. Copyright © 2012 John Wiley & Sons, Ltd.     

Multichannel ARMA modeling by least squares circular latticefiltering

The paper makes an attempt to develop least squares lattice algorithms for the ARMA modeling of a linear, slowly time-varying, multichannel system employing scalar computations only. Using an equivalent scalar, periodic ARMA model and a circular delay operator, the signal set for each channel is defined in terms of circularly delayed input and output vectors corresponding to that channel. The orthogonal projection of each current output vector on the subspace spanned by the corresponding signal set is then computed in a manner that allows independent AR and MA order recursions. The resulting lattice algorithm can be implemented in a parallel architecture employing one processor per channel with the data flowing amongst them in a circular manner. The evaluation of the ARMA parameters from the lattice coefficients follows the usual step-up algorithmic approach but requires, in addition, the circulation of certain variables across the processors since the signal sets become linearly dependent beyond certain stages. The proposed algorithm can also be used to estimate a process from two correlated, multichannel processes adaptively allowing the filter orders for both the processes to be chosen independently of each other. This feature is further exploited for ARMA modeling a given multichannel time series with unknown, white input     

Robust design of envelope-constrained filters in the presence ofinput uncertainty

The maximum robustness design of envelope-constrained filters with uncertain input (ECUI) is formulated as a minimax optimization problem in which the set of feasible filters is characterized by nonsmooth matrix inequalities. An efficient design algorithm is developed to solve this problem by use of a newly developed transformation technique. The attractive feature of this algorithm is that the ECUI filter thus designed can allow for the greatest uncertainty in the input signal while still achieving the acceptable filter performance     

引入双边滤波器优化的彩色滤波阵列插值

基于彩色滤波阵列(CFA)的图像传感器在每个像素 位置获得三原色红(R)、绿(G)和蓝(B)中的一种分量 ,其缺失 分量需要根据周围像素插值得到。目前提出的许多种插值算法,绝大部分采用Bayer排列模 式。本文在色 差恒定假设基础上,提出一种基于双边滤波器的自适应Bayer模型插值算法,对G通道的估计采 用自适应滤波器进行插值,对R和B通道的插值采用双边滤波器。算法利用待插值像素 与不同距离像 素相关性不同的思想,根据图像边缘自适应设定滤波模板,能较准确估计G、B和R、G通 道之间的色差值。 实验结果表明,对比多尺度色差梯度算法和边缘强度滤波等算法,插值后的图像不仅 主观视觉, 且客观评价指标(彩色峰值信噪比,CPSNR)均优于这些算法。     

Synthesis of One-Input M-Output Optical FIR Lattice Circuits

This paper presents a one-input M-output (1 x M)configuration and a synthesis algorithm for realizing an optical finite impulse response (FIR) lattice filter having M output channels (M ges 2). The circuit configuration has a multilayer structure consisting of multiple Mach-Zehnder interferometers with delay time differences of zero or Deltatau. It is a natural extension of the conventional two-port optical FIR lattice circuit (M = 2) . The proposed synthesis algorithm is based on factorizations of the paraunitary total transfer matrix. It realizes output responses having highest orders equal to the number of stages for all output channels. It is shown that such a synthesis algorithm maximizes the degrees of freedom for designing output responses. Two kinds of five-channel interleave filters are demonstrated as synthesized examples: one has a flat group delay response while the other has an inclined group delay response.     

基于Bayesian-Fisher 混合模型的强跟踪当前统计模型

针对当前统计模型(CS)不能自适应调节机动参数,导致对弱机动以及强机动目标跟踪性能下降的问题,提出了一种基于Bayesian-Fisher 混合模型的新方法。首先,通过引入Bayesian-Fisher 混合模型,将机动加速度均值作为未知的确定性输入增广到状态变量中,实现了对加速度均值的在线自适应估计;其次,根据强跟踪滤波器(STF)的思想,引入时变渐消因子,增强算法对突变状态的适应能力。仿真结果表明,该算法不仅提高了对弱机动和强机动目标的跟踪精度,也削弱了对初始机动参数的依赖。     

Binomial distribution based grey wolf optimization algorithm for channel estimation in wireless communication system

Several input high-data-rate transmissions over broadband wireless channels are possible using multiple input multiple output (MIMO) systems paired with orthogonal frequency division multiplexing (OFDM) technology. Channel estimation is an essential technique and a necessary component of MIMO-OFDM systems. However, the noise will be there in MIMO-OFDM due to the environment. As a result, the wireless system performs degrades in terms of bit error rate (BER). The suggested method offers a better pilot pattern strategy for MIMO-OFDM and an efficient power allocation to address this issue. The binomial distribution-based grey wolf optimization (BDGWO) algorithm is proposed to identify the optimal pilot patterns. The power is then adaptively distributed to each transmit antenna to increase the spectral efficiency and maximum channel capacity through an adaptive neuro-fuzzy inference system with a sigmoid membership function (SMFANFIS). The best pilot patterns in PDGSIP (pilot design with generalized shift invariant property) were determined using the BDGWO algorithm based on the binomial distribution. According to the simulation results, the proposed BDGWO established pilot design with generalized shift invariant property (BDGWO-DGSIP) achieves higher performance compared other existing approaches such as PDGSIP, TPDGSIP, and LS in terms of NMSE, BER, and SER. Compared to the PDGSIP technique, the proposed PDGSIP-BDGWO system minimizes NMSE at 10%, BER at about 12%, and SER at 15%.     

二阶Volterra变数据块长LMS算法

二阶Volterra数据块LMS算法利用当前时刻及其以前时刻更多输入信号和误差信号的信息提高了算法的收敛速度,但由于其固定数据块长取值的不同导致了算法的收敛速度和稳态误差此消彼长。针对这个问题,本文提出一种二阶Volterra变数据块长LMS算法,通过时刻改变输入信号数据块长度提高算法性能。本算法首先采用两个并行的二阶Volterra滤波器,其输入信号数据块长差值始终保持一个单位;然后将其各自的输出误差信号同时输入到数据块长判决器,通过判决器得到下一时刻各个滤波器输入信号的数据块长度;最后以第1个二阶Volterra滤波器的输出作为整个滤波系统的输出,从而改善了算法性能。将本算法应用于非线性系统辨识,计算机仿真结果表明,高斯噪声背景下本算法的收敛速度和稳态性能都得到了明显的提高。      

An Efficient Method for Evaluating Information Outage Probability and Ergodic Capacity of OSTBC System

Several numerical methods have been suggested in the past to compute the outage probability and the ergodic capacity of an orthogonal space-time block coding system. In this paper we add to this body of work by describing a simpler yet general method that relies on a more efficient Fixed-Talbot algorithm for numerical Laplace inversion. The framework developed can be applied to a wide range of fading distributions (including Rice, Nakagami-m, Nakagami-Hoyt and Weibull stochastic channel models) with unequal channel gains and also to independent and non-identically distributed (i.n.d) multiple input multiple output channels.     

An efficient algorithm to design weighted minimax perfectreconstruction quadrature mirror filter banks

An efficient algorithm is presented to design lattice structure two-channel perfect reconstruction quadrature mirror filter (PR-QMF) banks. We formulate the filter bank design problem as an unconstrained weighted least squares problem with respect to the coefficients of the lattice structure. The proposed iterative algorithm optimizes the lattice coefficients and provides flexible control of the filters' stopband ripple profiles. Typically, only a few iterations of the algorithm are needed to obtain an optimal solution in the weighted minimax sense. We include a set of practical design rules for use with our algorithm. These rules allow very good estimation of important filter bank characteristics, such as the filter length and the number of signed digits for quantization of the lattice coefficients into canonic signed digit representation, to meet a given set of PR-QMF bank specifications     

An unwindowed multichannel lattice filter with orthogonal channels

An unwindowed (or covariance) multichannel lattice filter for recursive least-squares estimation is derived. The channels are orthogonalized to eliminate the need for matrix inversion. The channel-orthogonalization process leads to forward-propagating and backward-propagating blocks in both the lattice filter and the model-parameter construction algorithm. These blocks are particularly suitable for array processing, as illustrated by arrays presented in the paper     

M滤波的自适应背景抑制算法

提出了一种M滤波的自适应背景抑制算法.该算法将目标和观测噪声作为图像背景的混合干扰,依据M估计原理自适应的估计真实背景.算法具有较好的稳健性能,能够自适应的低抗高强度的干扰.仿真和实验表明,与均值滤波(MF)、中值滤波(ModF)以及Wiener滤波(WF)相比,该算法能够更有效地从混合噪声环境下估计背景,增强目标信噪比(SNR).     

智能反射面辅助MU-MISO系统宽带信道估计算法

为适应移动通信系统的宽带化应用,针对智能反射面（Intelligent Reflecting Surface,IRS）辅助多用户多输入单输出系统信道估计问题,提出了一种基于稀疏矩阵分解的改进正交匹配追踪（Orthogonal Matching Pursuit,OMP）算法。首先,考虑基站导频约束及IRS相移约束,建立一个压缩感知模型。然后,通过自适应地细化变换矩阵的分辨率,避免稀疏信号的细节丢失;再利用信道在不同子载波处共享的公共稀疏性,对多个子频带进行联合估计。最后利用级联信道的双结构稀疏性,将信道估计扩展至多用户场景。仿真结果表明,与传统压缩感知算法相比,所提算法能以较小的导频开销获得更高的准确性。     

Design of Multiplierless Lattice QMF: Structure and Algorithm Development

In this brief, efficient multiplierless design of lattice quadrature mirror filter bank is presented. Previous work by the authors has shown that splitting each lattice stage into cascade of subrotations results in larger stopband attenuation of filter than the conventional direct quantization. This brief extends the work further by exploiting the subrotations which yield more flexible sum of signed powers-of-two quantization. This enables us to find more possible discrete representations, and hence to reduce the quantization error. Also, an algorithm for the efficient gathering of candidate discrete coefficients is developed, based on the trellis-based searching approach. It substantially alleviates the overheads of optimization program, especially when the wordlengths and the number of nonzero digits are large. Several design examples are provided to show that the proposed structure with the candidate gathering algorithm provides improved frequency response.     

Cascade lattice IIR adaptive filters

The feedback lattice filter forms, including the two-multiplier form and the normalized form, are examined with respect to their relationships to the feedback direct form filter. Specifically, the transformation matrix between the lattice forms and the direct form is derived; parameter and state relationships between the lattice forms and the direct form are therefore obtained. An IIR filter structure-the cascade lattice IIR structure-is constructed. Based on this structure, three IIR adaptive filtering algorithms in the two-multiplier form can then be developed following the gradient approach, the Steiglitz-McBride approach and the hyperstability approach. Convergence of these algorithms is theoretically analyzed using either the ODE approach or the hyperstability theorem. These algorithms are then simplified into forms computationally as efficient as their corresponding direct form algorithms. Relationships of the simplified algorithms to the direct form algorithms are also studied, which disclose a consistency in algorithm structure regardless of the filter form. Three normalized lattice algorithms can also be derived from the two-multiplier lattice algorithms. Experimental results show much improved performance of the normalized lattice algorithms over the two-multiplier lattice algorithms and the direct form algorithms     

A stable and distortion-free IIR echo and howling canceler

The authors propose a configuration for an infinite impulse response (IIR) adaptive echo and howling canceller, which consists of a two-channel maximum entropy lattice filter and its inverse filter. The echo is canceled by the adaptive lattice filter, while the signal distortion is eliminated by the inverse lattice. With stability guaranteed without the necessity of testing, the structure costs O (N) multiplications per sampling period. The algorithm can also be greatly simplified for white input cases     

Tree-structured piecewise linear adaptive equalization

The use of a tree-structured piecewise linear filter as an adaptive equalizer is proposed. In the tree equalizer, each node in a tree is associated with a linear filter restricted to a polygonal domain, and each subtree is associated with a piecewise linear filter. A training sequence is used to adaptively update the filter coefficients and domains at each node, and to select the best subtree and corresponding piecewise linear filter. The tree-structured approach offers several advantages. First, it makes use of standard linear adaptive filtering techniques at each node to find the corresponding conditional linear filter. Second, it allows for efficient selection of the subtree and corresponding piecewise linear filter of appropriate complexity. Overall, the approach is computationally efficient and conceptually simple. Numerical experiments are performed to show the advantages of tree-structured piecewise linear and piecewise decision feedback equalizers over linear, polynomial, and decision feedback equalizers for the equalization of channels with severe intersymbol interference