A wide-band radial basis function decision feedbackequalizer-assisted burst-by-burst adaptive modem

The performance of radial basis function-based decision feedback equalized (RBF DFE) burst-by-burst adaptive quadrature amplitude modulation (AQAM) is presented for transmissions over dispersive wide-band mobile channels. This scheme is shown to give a significant improvement in terms of the mean bit error rate (BER) and bits per symbol (BPS) performance compared to that of the individual fixed modulation modes. The structural equivalence of the RBF DFE to the optimal Bayesian equalizer enables it to potentially outperform the conventional Kalman-filtered AQAM DFE scheme     

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.     

运用误差反馈的判决反馈均衡器的性能分析

判决反馈均衡器（Decision Feedback Equalizer，DFE）能补偿具有严重符号间干扰（Inter Symbol Interference，ISI）的信道，且不存在线性均衡器增强噪声的影响。而在其基础上改进的运用误差反馈的DFE，可利用误差反馈滤波器来减少传统DFE中存在的误差信号的相关性，同时其硬件实现的复杂度没有明显提高。理论分析和仿真表明，这种方法比传统的DFE更有效，特别是针对信道有严重符号间干扰的情况。     

Decision feedback equalization

As real world communication channels are stressed with higher data rates, intersymbol interference (ISI) becomes a dominant limiting factor. One way to combat this effect that has recently received considerable attention is the use of a decision feedback equalizer (DFE) in the receiver. The action of the DFE is to feed back a weighted sum of past decision to cancel the ISI they cause in the present signaling interval. This paper summarizes the work in this area beginning with the linear equalizer. Three performance criteria have been used to derive optimum systems; 1) minimize the noise variance under a "zero forcing" (ZF) constraint i.e., insist that all intersymbol interference is cancelled, 2) minimize the mean-square error (MMSE) between the true sample and the observed signal just prior to the decision threshold, and 3) minimize the probability of error (Min Pe). The transmitter can be fixed and the receiver optimized or one can obtain the joint optimum transmitter and receiver. The number of past decisions used in the feedback equalization can be finite or infinite. The infinite case is easier to handle analytically. In addition to reviewing the work done in the area, we show that the linear equalizer is in fact a portion of the DFE receiver and that the processing done by the DFE is exactly equivalent to the general problem of linear prediction. Other similarities in the various system structures are also shown. The effect of error propagation due to incorrect decisions is discussed, and the coaxial cable channel is used as an example to demonstrate the improvement available using DFE.     

An adaptive RAM-DFE for storage channels

A modification of the decision feedback equalizer (DFE), RAM-DFE, is presented and analyzed for use in channels with trailing nonlinear intersymbol interference, especially binary saturation-recording channels. In the RAM-DFE, a look-up table, which can be easily implemented with random access memory, (RAM), replaces the transversal filter feedback section of the DFE. The feedforward section of the equalizer remains linear. A general nonlinear Markov (or finite-state machine) model is used to model the nonlinear intersymbol interference (ISI) channel. With this Markov model, a method is introduced for computing the minimum-mean-squared-error settings of the feedforward filter coefficients and the feedback filter and look-up table contents for the linear DFE and the RAM-DFE, respectively. RAM-DFE with these settings can be significantly better than the linear DFE for channels with trailing nonlinear ISI. Globally convergent gradient-type algorithms for updating the feedforward section coefficients and the contents of the feedback table are introduced and analyzed. Results based on data taken from disk storage units are discussed     

基于多用户反馈的判决反馈均衡器的研究

本文提出的一种新颖的基于多用户反馈的判决反馈均衡器,解决了在CDMA多用户检测中传统自适应判决反馈均衡器误码率高、系统容量小的缺点.它由具有误差反馈滤波器的判决反馈均衡器(Decision Feedback Equalizer with Error Feedback Filter,DFE-EFF)构成,并在判决后反馈多用户数据抵消多址干扰(多用户反馈干扰抵消).文中给出其结构图,分析各种判决反馈均衡算法.理论证明,具有误差反馈滤波器的多用户反馈干扰抵消判决反馈均衡器(多用户反馈干扰抵消DFE-EFF)较各种判决反馈均衡器为最优,它能同时有效处理ISI,MAI和噪声的干扰.仿真结果表明,在误码率性能和系统容量两方面,多用户反馈干扰抵消DFE-EFF比DFE、DFE-EFF均有较大改善.     

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     

A quadratic sigmoid neural equalizer for nonlinear digital magneticrecording channels

A new neural equalizer is proposed in order to compensate for intersymbol interference and to mitigate nonlinear distortions in digital magnetic recording systems. The proposed equalizer uses the quadratic sigmoid function as the activation function. The performance of the proposed equalizer is compared to those of a decision-feedback equalizer (DFE) and a neural decision feedback equalizer (NDFE) in terms of bit-error rate in nonlinear digital magnetic recording channels. Simulation results demonstrate that the proposed equalizer outperforms both DFE and NDFE     

Adaptive Decision Feedback Space–Time Equalization With Generalized Sidelobe Cancellation

In wireless communications, cochannel interference (CCI) and intersymbol interference (ISI) are two main factors that limit system performance. Conventionally, a beamformer is used to reduce CCI, whereas an equalizer is used to compensate for ISI. These two devices can be combined into one as space–time equalizer (STE). A training sequence is usually required to train the STE prior to its use. In some applications, however, spatial information corresponding to a desired user is available, but the training sequence is not. In this paper, we propose an adaptive decision feedback STE to cope with this problem. Our scheme consists of an adaptive decision feedback generalized sidelobe canceller (DFGSC), a blind decision feedback equalizer (DFE), and a channel estimator. Due to the feedback operation, the proposed DFGSC is not only superior to the conventional generalized sidelobe canceller but also robust to multipath channel propagation and spatial signature error. Theoretical results are derived for optimum solutions, convergence behavior, and robustness properties. With the special channel-aided architecture, the proposed blind DFE can reduce the error propagation effect and be more stable than the conventional blind DFE. Simulation results show that the proposed STE is effective in mitigating both CCI and ISI, even in severe channel environments.      

Adaptive interference cancellation for DS-CDMA systems using neuralnetwork techniques

The objective of this study is to apply and investigate a neural network-based decision feedback scheme for interference suppression in direct sequence code division multiple access (DS-CDMA) wireless networks. It is demonstrated that a decision feedback functional link equalizer (DFFLE) in combination with an eigenvector network can closely approximate a Bayesian receiver with significant advantages, such as improved bit-error ratio (BER) performance, adaptive operation, and single-user detection in a multiuser environment. It is assumed that the spreading codes of the interfering users will be unknown to the receiver. This detector configuration is appropriate for downlink communication between a base station and a mobile user in a digital wireless network. The BER performance in the presence of interfering users is evaluated. The improved performance of such a DFFLE receiver for CDMA is attributed to the nonlinear decision boundary it evaluates for the desired user. The receiver structure is also capable of rapid adaptation in a dynamic communications scenario for which there is entry/exit of users and imperfect power control. The convergence performance and error propagation of the DFFLE receiver are also considered and exhibit reasonable promise for third generation wireless DS-CDMA networks     

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 equalizer with channel estimator for mobile radiocommunication

For unknown mobile radio channels with severe intersymbol interference (ISI), a maximum likelihood sequence estimator, such as a decision feedback equalizer (DFE) having both feedforward and feedback filters, needs to handle both precursors and postcursors. Consequently, such an equalizer is too complex to be practical. This paper presents a new reduced-state, soft decision feedback Viterbi equalizer (RSSDFVE) with a channel estimator and predictor. The RSSDFVE uses maximum likelihood sequence estimation (MLSE) to handle the precursors and truncates the overall postcursors with the soft decision of the MLSE to reduce the implementation complexity. A multiray fading channel model with a Doppler frequency shift is used in the simulation. For fast convergence, a channel estimator with fast start-up is proposed. The channel estimator obtains the sampled channel impulse response (CIR) from the training sequence and updates the RSSDFVE during the bursts in order to track changes of the fading channel. Simulation results show the RSSDFVE has nearly the same performance as the MLSE for time-invariant multipath fading channels and better performance than the DFE for time-variant multipath fading channels with less implementation complexity than the MLSE. The fast start-up (FS) channel estimator gives faster convergence than a Kalman channel estimator. The proposed RSSDFVE retains the MLSE structure to obtain good performance and only uses soft decisions to subtract the postcursor interference. It provides the best tradeoff between complexity and performance of any Viterbi equalizers     

Efficient bad equalizer in two-ray multipath fading channels

An efficient bidirectional arbitrated decision feedback (BAD) equalizer is presented in single-carrier block transmission system in the Two-Ray multipath fading channels, where the output from the bidirectional equalizers are combined together directly using maximal ratio combining (MRC) rule to improve the signal-to-noise ratio (SNR) before demodulation. The computational complexity of the BAD equalizer presented is linear with the channel length, which is the same as conventional decision feedback equalizer (DFE) and is significantly lower than that of conventional BAD equalizer as well as the maximum likelihood (ML) algorithm. While the performance of the new scheme depends on the specific channel characteristics, it is shown by simulation results that the performance of the new BAD can surpass the one of DFE dramatically in the minimum or non-minimum phase Two-Ray multipath fading channels.     

On the equivalence of the simultaneous and separate MMSEoptimizations of a DFE FFF and FBF

There is great interest in the use of decision feedback equalization (DFE) to mitigate the effects of intersymbol interference (ISI) on wireless multipath fading channels. The coefficients of a DFE feedforward filter (FFF) and feedback filter (FBF) are usually adjusted based on the minimum mean square error (MMSE) criterion. The equalizer coefficients can be calculated by recursive adaptation or by direct computation based on a channel estimate. The equivalence of the simultaneous and separate MMSE optimization of the FFF and FBF of a finite-length DFE is established     

Iterative Equalization using Improved Block DFE for Synchronous CDMA Systems

Iterative equalization using optimal multiuser detector and optimal channel decoder in coded CDMA systems improves the bit error rate (BER) performance tremendously. However, given large number of users employed in the system over multipath channels causing significant multiple-access interference (MAI) and intersymbol interference (ISI), the optimal multiuser detector is thus prohibitively complex. Therefore, the sub-optimal detectors such as low-complexity linear and non-linear equalizers have to be considered. In this paper, a novel low-complexity block decision feedback equalizer (DFE) is proposed for the synchronous CDMA system. Based on the conventional block DFE, the new method is developed by computing the reliable extrinsic log-likelihood ratio (LLR) using two consecutive received samples rather than one received sample in the literature. At each iteration, the estimated symbols by the equalizer is then saved as a priori information for next iteration. Simulation results demonstrate that the proposed low-complexity block DFE algorithm offers good performance gain over the conventional block DFE.     

Polynomial perceptrons and their applications to fading channelequalization and co-channel interference suppression

This paper investigates the behaviors of polynomial perceptrons and introduces a fractionally spaced recursive polynomial perceptron with low complexity and fast convergence rate. The nonlinear mapping ability of the polynomial perceptron is analyzed. It is shown that a polynomial perceptron with degree L(⩾4) satisfies the Stone-Weierstrass theorem and can approximate any continuous function to within a specified accuracy. Moreover, the nonlinear mapping ability of a polynomial perceptron with degree L is similar to that of the three-layer perceptron with one hidden layer for time same number of neurons in the input layer. The nonlinear mapping ability of the fractionally spaced recursive polynomial perceptron is also presented. Applications of polynomial perceptrons for fading channel equalization and co-channel interference suppression in a 16-level quadrature amplitude modulation receiver system are considered. Computer simulations are used to evaluate and compare the performance of polynomial perceptron (PP) and fractionally spaced bilinear perceptron (FSBLP) with that of the synchronous decision feedback multilayer perceptron (SDFMLP), fractionally spaced decision feedback multilayer perceptron (FSDFMLP), and the conventional decision feedback equalizer (DFE). The results show that the performance of the fractionally spaced bilinear perceptron is clearly superior to that of the other structures     

Performance of a hybrid decision feedback equalizer structure forCAP-based DSL systems

We study the performance of a class of derision feedback equalizer (DFE) structures for high-speed digital transmission systems. We first present mathematical formulation of minimum mean-square error (MMSE) and the optimum tap coefficients for various finite-length phase-splitting equalizers over the loop in the presence of colored noise, such as near-end crosstalk (NEXT) and far-end crosstalk (FEXT). The performance of the equalizers is also analyzed in the presence of narrowband interference and the channel reflections introduced by bridged taps. The hybrid-type DFE (H-DFE) is presented as a practical equalizer structure for these applications. The results of analysis show that the H-DFE has advantages in the performance and/or in the implementation complexity as compared with the existing DFE structures. An additional advantage of the H-DFE is in the transmission systems that employ the precoding technique. The precoding for the H-DFE allows the system to track small changes in the channel     

无人机数据链判决反馈均衡器的FPGA实现

从无人机数据链的需求出发,使用现场可编程门阵列(FPGA)实现判决反馈均衡器(DFE),以消除无人机数据链中的码间干扰。文中利用System Generator对判决反馈均衡器进行建模,将模型转换为硬件,并通过硬件协调仿真在Xilinx virtex5 XC5VSX50T芯片上验证。仿真结果表明,在不同信道条件下,判决反馈均衡器能很好地克服码间干扰,适用于无人机信道。本文为无人机高速数据链均衡器的实现打下基础。     

Asymptotic Bayesian decision feedback equalizer using a set of hyperplanes

We present a signal space partitioning technique for realizing the optimal Bayesian decision feedback equalizer (DFE). It is known that when the signal-to-noise ratio (SNR) tends to infinity, the decision boundary of the Bayesian DFE is asymptotically piecewise linear and consists of several hyperplanes. The proposed technique determines these hyperplanes explicitly and uses them to partition the observation signal space. The resulting equalizer is made up of a set of parallel linear discriminant functions and a Boolean mapper. Unlike the existing signal space partitioning technique of Kim and Moon (1998), which involves complex combinatorial search and optimization in design, our design procedure is simple and straightforward, and guarantees to achieve the asymptotic Bayesian DFE.     

Adaptive algorithms for channel equalization with soft decisionfeedback

A new approach based on joint entropy maximization (JEM) is taken and adaptive algorithms are developed for channel equalization with a decision feedback equalizer (DFE). The proposed work generalizes the existing algorithms for DFE with a hard decision device. Previous research has shown that when the hard decisions in a DFE are replaced with soft decisions, the performance of the adaptive algorithms [e.g., minimum mean square error (MMSE)] improves dramatically. The soft decisions can be introduced naturally via the viewpoint taken here. Additionally, constant modulus and other (blind) algorithms for DFE with soft decisions can be derived from this JEM approach