A decision-feedback equalizer with pattern-dependent feedback formagnetic recording channels

A new nonlinear equalizer for high-density magnetic recording channels is presented. It has a structure of the decision-feedback equalizer (DFE) with a nonlinear model at the feedback section and a dynamic threshold detector. The feedback nonlinear model is a sequence of look-up tables (LUTs) indexed by time, and each table is addressed by a transition pattern formed by one future and ν past transitions. We call this new nonlinear equalizer the pattern-dependent DFE (PDFE). The feedback nonlinear model cancels the trailing nonlinear intersymbol interference (ISI), and then the data decision is made by considering the precursor nonlinear ISI caused by one future symbol. We propose a tap optimization criterion SNR_d for the PDFE which in effect tries to maximize the output signal to noise ratio, and derive a closed-form solution for the tap values. We compare the detection performance of PDFE with that of the DFE and the RAM-DFE on experimental channels. The RAM-DFE is a DFE with one large LUT at its feedback section. The results show that the PDFE yields a significant performance improvement over the DFE and the RAM-DFE. Also the PDFE derived in this paper achieves a superior performance compared with the PDFE derived by the minimum mean-square-error criterion     

A new adaptive functional-link neural-network-based DFE forovercoming co-channel interference

A new approach for the decision feedback equalizer (DFE) based on the functional-link neural network is described. The structure is applied to the problem of adaptive equalization in the presence of intersymbol interference (ISI), additive white Gaussian noise, and co-channel interference (CCI). It is shown through simulation results for a severe amplitude distorted co-channel system that the decision feedback functional-link equalizer (DFFLE) provides significantly superior bit-error rate (BER) performance characteristics compared to the conventional DFE, the linear transversal equalizer (LTE), the nonlinear radial basis function (RBF) neural-network-based structures and the feed-forward functional-link equalizer (FFLE)-based structures. The DFFLE is also shown to have a significantly simpler computational requirement relative to the RBF and the FFLE     

Functional link neural network cascaded with Chebyshev orthogonal polynomial for nonlinear channel equalization

Nonlinear intersymbol interference (ISI) leads to significant error rate in nonlinear communication and digital storage channel. In this paper, therefore, a novel computationally efficient functional link neural network cascaded with Chebyshev orthogonal polynomial is proposed to combat nonlinear ISI. The equalizer has a simple structure in which the nonlinearity is introduced by functional expansion of the input pattern by trigonometric polynomial and Chebyshev orthogonal polynomial. Due to the input pattern and nonlinear approximation enhancement, the proposed structure can approximate arbitrarily nonlinear decision boundaries. It has been utilized for nonlinear channel equalization. The performance of the proposed adaptive nonlinear equalizer is compared with functional link neural network (FLNN) equalizer, multilayer perceptron (MLP) network and radial basis function (RBF) along with conventional normalized least-mean-square algorithms (NLMS) for different linear and nonlinear channel models. The comparison of convergence rate, bit error rate (BER) and steady state error performance, and computational complexity involved for neural network equalizers is provided.     

An adaptive analog noise-predictive decision-feedback equalizer

In this paper, an adaptive noise-predictive decision-feedback equalizer (NPDFE) is presented. The NPDFE architecture and its implementation are described. The NPDFE consists of an analog finite-impulse-response (FIR) forward equalizer, a recursive analog equalizer for noise prediction, and a decision-feedback equalizer (DFE). The recursive equalizer reduces noise enhancement and improves the signal-to-noise ratio (SNR) at the decision slicer input. The prototype targets a magnetic recording channel modeled by a Lorentzian impulse response. Measured results show that compared to a conventional DFE with FIR forward equalizer, the NPDFE achieves a SNR improvement of about 2 dB with PW₅₀=2.5T. The NPDFE consumes 130 mW at a data rate of 100 Mb/s and occupies 1.3 mm² of die area in a 0.5-μm CMOS process     

应用于10 Gbit/s光通信及背板传输的自适应均衡器设计

描述了一种既可用于背板传输也可用于光纤通信的高速串行收发器前端均衡器的设计。为适应光信号在传播中的色散效应,使用前馈均衡器(FFE)加判决反馈均衡器(DFE)的组合,取代了背板通信中常用的连续时间线性均衡器(CTLE)和DFE的组合。设计使用3 pre-tap、3 post-tap和1个main tap的抽头组合方式,兼顾pre-cursor和post-cursor的信号失真,有效补偿范围为15 dB。补偿系数采用完全自适应算法调整,对FFE采用模拟MSE算法调整,DFE引擎采用1/16速率数字sign-sign最小均方差(LMS)算法实现。芯片使用UMC 28 nm工艺流片,输入信号频率为10 Gbit/s。     

Adaptive noncoherent DFE for MDPSK signals transmitted over ISIchannels

A novel noncoherent decision-feedback equalization (NDFE) scheme for M-ary differential phase shift-keying signals transmitted over intersymbol interference channels is presented. A suboptimum version with lower computational complexity and a noncoherent linear equalizer (NLE) are derived from the original NDFE scheme. Furthermore, the relation of the novel NLE to a previously proposed NLE is investigated. In contrast to known NDFE schemes, the novel scheme can approach the performance of coherent minimum mean-squared error decision-feedback equalization. For adaptation of the feedforward and feedback filters, efficient novel modified least mean-square and recursive least squares algorithms are presented. Finally, it is shown that the proposed adaptive NDFE scheme is robust against frequency offset     

针对判决反馈均衡器的部分ⅡR提前结构及其应用

给出一种可以用于高速数字接收的特殊的判决反馈均衡器结构。为减少FIR内多径传播影响到ⅡR内的多径响应，而将部分ⅡR提前于FIR，以得到更快的系数收敛速度。在此基础上的数据仿真，比较了提前结构同普通结构的性能差异，验证了该结构可以使均衡器在严重畸变的信道条件下得到更快的收敛速度。最后，介绍了提前结构的最新的高清晰度电视8VSB接收机中的应用。     

自适应均衡算法在信道均衡技术中的应用研究

文中描述了两种非线性均衡器分别为判决反馈均衡器(DFE)和最大似然序列估计(MLSE)均衡器.所用信道模型为加性白高斯噪声信道,在DFE和线性均衡器(LE)中都是使用递归最小二乘(RLS)算法和最小均方(LMS)算法对数据进行分块处理.MLSE均衡器中使用了维特比最佳译码算法.就误比特性能来做以比较,DFE远好于LE,MLSE均衡器又明显优于DFE,并且它能达到几乎最优的性能.     

基于非单点模糊支持向量机的判决反馈均衡器

该文提出了一种具有较强抗突发干扰能力的非单点模糊支持向量机判决反馈均衡器。该方法以支持向量机为框架,采用具有前置滤波特性的非单点模糊高斯核函数,利用梯度下降法调整核函数中的可调参数。通过仿真实验,并与支持向量机判决反馈均衡器和传统判决反馈均衡器进行比较,结果证明该方法具有优良的非线性均衡能力和抗突发干扰能力。     

A nonlinear electrical equalizer with decision feedback for OOK optical communication systems

In this paper we introduce a nonlinear equalizer using the Radial Basis Function (RBF) network with decision feedback equalizer (DFE) for electronic dispersion compensation in optical communication systems with on-off-keying and a direct detection receiver. The RBF method introduces a non-linear equalization technique suitable for optical communication direct detection systems that include nonlinear transformation at the photodetector. A bit error rate performance comparison shows that the RBF with DFE out performs the RBF without DFE and achieves similar results provided by maximum likelihood sequence estimator.     

滑动窗快速横向滤波的自适应判决反馈均衡器算法

本文提出了一种基于滑动窗广义多路快速横向滤波（ＳＷＦＴＦ）的自适应判决反馈均衡器（ＤＦＦ）算法，它具有快速跟踪性能，故可用于快速时变多径衰落的信道。文中推导了ＳＷＦＴＦ－ＤＦＥ算法。在数字移动通信信道模型上，利用计算机模拟，在均方误差和误码率特性方面与其它均衡器算法进行了比较。     

Adaptive decision feedback equalization for digital satellitechannels using multilayer neural networks

This paper introduces an adaptive derision feedback equalization using the multilayer perceptron structure of an M-ary PSK signal through a TDMA satellite radio channel. The transmission is disturbed not only by intersymbol interference (ISI) and additive white Gaussian noise, but also by the nonlinearity of transmitter amplifiers. The conventional decision feedback equalizer (DFE) is not well-suited to detect the transmitted sequence, whereas the neural-based DFE is able to take into account the nonlinearities and therefore to detect the signal much better. Nevertheless, the applications of the traditional multilayer neural networks have been limited to real-valued signals. To overcome this difficulty, a neural-based DFE is proposed to deal with the complex PSK signal over the complex-valued nonlinear MPSK satellite channel without performing time-consuming complex-valued back-propagation training algorithms, while maintaining almost the same computational complexity as the original real-valued training algorithm. Moreover, a modified back-propagation algorithm with better convergence properties is derived on the basis of delta-bar-delta rule. Simulation results for the equalization of QPSK satellite channels show that the neural-based DFE provides a superior bit error rate performance relative to the conventional mean square DFE, especially in poor signal-to-noise ratio conditions     

SCFNN-Based Decision Feedback Equalization Robust to Frequency Offset and Phase Noise

This paper proposes a self-constructing fuzzy neural network-based decision feedback equalizer (SCFNN DFE). An online learning algorithm containing the structure and parameter learning phases is employed in training the SCFNN DFE. Specifically, the feedforward input vector classification and a gradient-descent method are both used in this online learning algorithm. We show by simulations that the proposed SCFNN DFE offers improvement compared to the traditional DFE methods in the presence of frequency offset and phase noise.     

Decision Feedback Equalization for Multipath Induced Interference in Digital Microwave LOS Links

The performance of a 49-QPRS, 90 Mbit/s digital radio receiver equipped with a decision feedback equalizer (DFE) to counter multipath fading is investigated via computer simulation. The simulation includes the transmitted data, multipath fade model, receiver model, and DFE. The results indicate that a DFE equipped with five forward and five feedback taps can adequately compensate a 40 dB minimum-phase fade anywhere in the receiver passband. The study is extended to other receiver configurations including the use of space diversity and/or slope equalizers and the use of a transversal equalizer (TE) with the same delay-span in place of the DFE. The results indicate that the DFE equipped receiver outperforms the TE receiver and that still better performance may be achieved using a combination of space diversity and DFE.     

Combined trellis coding and DFE through Tomlinson precoding

The authors propose and evaluate a receiver architecture which combines the power of a decision feedback equalizer (DFE) with trellis coding, while allowing for minimal decoding delay in such a way that the total gain of the system is additive. The system is based on a structure that transposes the feedback filter of the DFE into the transmitter and, for high-order constellations, provides negligible increase in transmitter power. The first known hardware realization of a high bit rate digital subscriber line (HDSL) system that achieves the coding gain provided by a trellis code in addition to the equalization gain provided by the DFE is presented. A system whose complexity of implementation is comparable to that of a typical DFE and an independent Viterbi decoder is proposed     

Cyclostationary crosstalk suppression by decision feedbackequalization on digital subscriber loops

Interference from digital signals in multipair cables has been shown to be cyclostationary under some conditions. This work evaluates the performance of a decision feedback equalizer (DFE) in the presence of cyclostationary interference (CI), intersymbol interference (ISI), and additive white noise (AWN). A comparison between a DFE with CI and one with stationary interference (SI) shows the ability of the DFE to substantially suppress CI. Fractionally spaced and symbol-rate DFE equalizers are also compared and the former is found to yield better performance, especially in the presence of CI. The use of a symbol-rate DFE using an adaptive timing technique that finds the receiver's best sampling phase is proposed for when the fractionally spaced DFE cannot be used because of its complexity. The results also demonstrate the potential benefits of synchronizing central office transmitter clocks, if a fractionally spaced DFE is used at the receiver     

Pole-zero decision feedback equalization with a rapidly convergingadaptive IIR algorithm

A decision feedback equalizer (DFE) containing a feedback filter with both poles and zeros is proposed for high-speed digital communications over the subscriber loop. The feedback filter is composed of a relatively short FIR filter that cancels the initial part of the channel impulse response, which may contain rapid variations due to bridge taps, and a pole-zero, or IIR, filter that cancels the smoothly decaying tail of the impulse response. Modifications of an adaptive IIR algorithm, based on the Steiglitz-McBride (1965) identification scheme, are proposed to adapt the feedback filter. A measured subscriber loop impulse response is used to compare the performance of the adaptive pole-zero DFE, assuming a two-pole feedback filter, with a conventional DFE having the same number of coefficients. Results show that the pole-zero DFE offers a significant improvement in mean squared error relative to the conventional DFE. The speed convergence of the adaptive pole-zero DFE is comparable to that of the conventional DFE using the standard least mean square (LMS) adaptive algorithm     

A mixed-signal decision-feedback equalizer that uses a look-aheadarchitecture

A mixed-signal decision-feedback equalizer (DFE) that uses a look-ahead architecture is described. The parallelism in the look-ahead DFE (LA DFE) achieves an increase in the data rate over a conventional DFE with a small increase in area. Fully differential analog circuits perform the convolution operation in the LA DFE, and the coefficient adaption is carried out by digital circuits. The LA DFE occupies 23 mm ² in a 2-μm CMOS process and operates at 50 Mb/s while dissipating 260 mW     

Electrical equalization for advanced optical communication systems

We investigate equalizers for electronic dispersion compensation (EDC) of dispersion limited optical fibre communication links in combination with different modulation formats. We show that the performance of conventional equalizers including feedforward equalizer (FFE) and decision feedback equalizer (DFE) are fundamentally limited by the nonlinearity of square-law detection of the photodiode in direct detection systems. Advanced modulation formats such as differential phase shift keying (DPSK) and optical duobinary further enhance this kind of nonlinearity and degrade further FFE/DFE performance. However, nonlinear FFE–DFE and maximum likelihood sequence estimation (MLSE) take into account the mitigation of nonlinear inter symbol interference (ISI) and hence can achieve much better performance. We show that in contrast to other modulation formats, optical single sideband modulation results in approximately linear distortions after detection and thus a simple linear FFE equalizer can achieve good compensation.     

A 35 Mb/s mixed-signal decision-feedback equalizer for disk drivesin 2-μm CMOS

A 35 Mb/s mixed-signal adaptive decision-feedback equalizer (DFE) has been implemented in a 2-μm CMOS technology. The DFE has four feedback taps for cancelling intersymbol interference (ISI) and one tap for cancelling dc offset. The ISI is cancelled using fully differential analog circuits. Coefficient adaptation is digital, and two adaptation rates are available. The DFE occupies 24 mm² and dissipates 165 mW