Mitigating Error Propagation in Decision Feedback Equalizers for VSB-Based DTV Receivers

The central theme is the study of error propagation effects in decision feedback equalizers (DFEs). The thesis contains: a stochastic analysis of error propagation in a tuned DFE; an analysis of the effects of error propagation in a blindly adapted DFE; a deterministic analysis of error propagation through input-output stability ideas; and testing procedures for establishing correct tap convergence in blind adaptation. To a lesser extent, the decision directed equalizer (DDE) is also treated. Characterizing error propagation using finite state Markov process (FSMP) techniques is first considered. We classify how the channel and DFE parameters affect the FSMP model and establish tight bounds on the error probability and mean error recovery time of a tuned DFE. These bounds are shown to be too conservative for practical use and highlight the need for imposing stronger hypotheses on the class of channels for which a DFE may be effectively used. In blind DFE adaptation we show the effect of decision errors is to distort the adaptation relative to the use of a training sequence. The mean square error surface in a LMS type setting is shown to be a concatenation of quadratic functions exposing the possibility of false tap convergence to undesirable DFE parameter settings. Averaging analysis and simulation are used to verify this behaviour on some examples. Error propagation in a tuned DFE is also examined in a deterministic setting. A finite error recovery time problem is set up as an input-output stability problem. Passivity theory is invoked to prove that a DFE can be effectively used on a channel satisfying a simple frequency domain condition. These results give performance bounds which relate well with practice. Testing for false tap convergence in blind adaptation concludes our study. Simple statistic output tests are shown to be capable of discerning correct operation of a DDE. Similar tests are conjectured for the DFE, supported by proofs for the low dimensional cases.

Severe intersymbol interference (ISI) is one of the main obstacles for reliable signal reception in ATSC DTV systems. Decision feedback equalizers (DFEs) are commonly used to suppress the ISI. However, DFEs may suffer from error propagation due to incorrect symbol decisions from the symbol slicer. This phenomenon deteriorates the performance even more when the post-cursor ISI is strong. In order to reduce error propagation, we present a novel hybrid equalization scheme for ATSC channels. The proposed scheme consists of an adaptive decision feedback sparsening filter (DFSF), and an iterative maximum a posteriori (MAP) equalizer based on the belief propagation (BP) algorithm. In the first stage, instead of removing all the ISI from post cursors, the DFSF employs a modified feedback filter which leaves the strongest post-cursor ISI taps uncorrected. As a result, a long ISI channel is equalized to a sparse channel having only a small number of nonzero taps. In the second stage, a belief propagation algorithm is applied to mitigate the residual ISI. Since the channel is typically time-varying and suffers from Doppler fading, the DFSF is adapted using the least mean square (LMS) algorithm, such that the amplitude and the locations of the nonzero taps of the equalized sparse channel appear to be fixed. As such, the channel appears to be static during the second stage of equalization which consists of the BP detector. Simulation results demonstrate that the proposed scheme outperforms the traditional DFE in symbol error rate, under both static channels and dynamic ATSC channels.

Decision feedback equalizers (DFE) employing energy constraints have been successfully used to limit the feedback of wrong decisions that lead to the well known error propagation phenomenon. This paper extends the energy constraint formulation proposed for the scalar DFE, to the class of block memoryless DFE structures that employ zero-padding transmission redundancy. We further show how to make use of fast order recursive relations in order to obtain the filters efficiently. Computer simulations verify the improved BER performance of the proposed scheme over its unconstrained block DFE counterpart.

Intersymbol interference (ISI) of the radio propagation through multipath fading channels is a major factor that limits the performance of mobile communication systems. Blind decision feedback equalization (DFE) is one of major methods for channel equalization. We propose a new method, based on a Hammerstein filter instead of DFE filters, for enhancing the performance of DFE, hence, blind HDFE. In this paper, we show the bit error rate (BER) performance of blind DFE and blind HDFE, in order to prove the superiority of BHDFE.

This paper investigates the performance of compromise Viterbi algorithm (VA) and standard equalization techniques by computation and simulation over band-limited channels using fourlevel vestigial sideband (VSB) modulation. Linear channel characteristics from the published telephone channel survey were used as examples of band-limited data transmission channels. One of the principal conclusions drawn from the study is that at data rates of 9600 bits/s and less, the linear characteristics of these channels do not limit performance even with linear equalization. It was found that at this data rate, receivers based on linear equalization are very sensitive to timing and carrier phase over some channels. Thus at 9600 bits/s the decision feedback equalizer was found to be a better choice because it is relatively insensitive to carrier phase and timing considerations. Moreover, at 9600 bits/s no problem with error propagation was encountered with the decision feedback equalizer. As the data rate was increased beyond 9600 bits/s the decision feedback tap gains became large enough to cause severe error propagation. The compromise VA receiver structure was effective at higher data rates and was almost unaffected by channel bandwidth up to 12 000 bits/s.

Addresses problems related to the conceptual design of a fully digital synchronous DFE (decision feedback equalizer) and investigates the effects of the necessary quantization of the input signals and coefficients on DFE performance in static and dynamic operation. The analysis is performed taking into account the following topics: the influence of the dynamic range and quantization levels of the input signal and coefficients: the tracking and acquisition algorithm capabilities; comparison of DFE structures; and the extension of robust algorithms to DFEs. An experimental setup including a digital baseband equalizer is described. Results are reported for two kinds of DFE structures and a 16-AQM (quadrature amplitude modulation) modulation format. Specific problems related to the operation of DFEs in digital radio modems are discussed. It is established that the DFE structure is able to track continuous minimum-phase to nonminimum-phase transitions and vice versa without getting out of lock. This is an important result since the DFE outperforms current linear equalizers. >

As the data rate has been increased over 10 Gb/s with copper interconnect, the intersymbol interference (ISI) caused from the channel loss should be compensated. While a decision feedback equalizer (DFE), which is widely used in the receiver can compensate the ISI, its ability to enhance the signal-to-noise ratio (SNR) is limited especially for high frequency data patterns (alternating data patterns). Even a DFE with a large number of taps, which has powerful compensation capacity for ISI, can improve only limited amount of SNR. To improve SNR, this brief presents a 1/4th baud-rate continuous-time linear equalizer (CTLE) and a two-tap DFE. The 1/4th baud-rate CTLE recovers data to be adequate for the DFE, and remaining ISI is removed by the DFE. To boost the high frequency gain of the DFE, exclusive or merged adders are introduced, so the proposed equalizer is more tolerant against channel noise. It compensates 21.7-dB channel loss and operates with 11.5-Gb/s data rate as it consumes 25.35 mW from 1.3 V supply in a 110-nm CMOS technology.

A decision-feedback equalizer (DFE) is the basis of a recent development of a quadruple diversity troposcatter modem which can operate up to a data rate of 12.6 Mbit/s in a 99% bandwidth of 15 MHz. In this paper a theoretical approach is developed for the calculation of average bit error rate (ABER), including the effects of intersymbol interference due to multipath and the finiteness of the transversal filters used to realize the DFE. By omitting the intersymbol interference effect, the calculation provides a lower bound which can be used to assess the intersymbol interference penalty for a particular DFE structure. The paper includes calculations of a DFE configuration which has a three tap forward filter with tap spacing equal to one-half a symbol interval. Measured performance results from fading channel simulator tests of a three tap forward filter DFE are presented for data rates from 1.5 to 12.6 Mbit/s and for a wide range of multipath statistical conditions. The results for this DFE configuration show (1) excellent agreement between calculated and measured ABER, (2) a small intersymbol interference penalty when the 2σ multipath spread is less than approximnately one-half the data symbol interval, and (3) successful operation at values of multipath spread up to twice the data symbol interval. In a sequel to this paper, the results of a field test of the DFE modem are presented. These live links test results are consistent with both the calculated and simulator measured data presented here.

By embedding a decision-feedback equalizer (DFE) into the structure of a maximum-likelihood sequence estimator (MLSE), an adaptive combined DFE/MLSE scheme is proposed. In this combined DFE/MLSE, the embedded DFE has three functions: (i) prefiltering the received signals and truncating the equivalent channel response into the desired one, (ii) compensating for channel distortions, and (iii) providing the MLSE detector with predicted values of input signals. Since the embedded MLSE detector operates on the predicted signals the detected symbols at the output of the DFE/MLSE do not suffer any delay and can be directly fed back into the embedded DFE so that the error propagation, which usually takes place in a conventional DFE, can be greatly reduced. Analytical and simulation results indicate that the performance is significantly improved by the DFE/MLSE compared to the conventional DFE while its computation complexity is much less than that of the conventional MLSE receiver. The combined DFE/MLSE can use different adaptive structures (block-updating, sliding window updating or symbol-by-symbol updating) to meet different performance objectives. Moreover, the proposed DFE/MLSE provides a trade-off between performance and complexity with a parameter m representing the MLSE detection depth as well as the number of predicting steps of the embedded DFE. For some particular values of m, this scheme is capable of emulating the conventional DFE, MLSE-VA, adaptive LE-MLSE equalizer, adaptive DDFSE, and adaptive BDFE without detection delay.

This paper introduces the decision feedforward equalizer (DFFE), a new low complexity iterative equalization architecture for high speed receivers used on channels with large intersymbol interference (ISI). The decision feedback equalizer (DFE) is one of the preferred receivers for high ISI channels. The high data and symbol rate of current communications systems often require parallel processing receiver implementations [1]. Unfortunately, the complexity of parallel architectures of the DFE grows exponentially with the channel memory [2] and limits their application to low ISI channels. The DFFE avoids the exponential growth of the DFE by using tentative decisions to iteratively cancel the ISI. We show that the DFFE can achieve performance similar to the DFE. These benefits make it an excellent choice for high-speed receivers required to operate over highly dispersive channels.

In this work, we base on multi-layered perceptron neural networks with backpropagation algorithm (MLP/BP) to construct multi-input multi-output (MIMO) decision feedback equalizers (DFEs). The proposal is used to recover distorted quadrature phase-shift keying (QPSK) signal. From the simulations, we note that the proposed scheme can recover severe distorted signals as well as suppress intersymbol interference (ISI), adjacent channel interference (ACI) and background additive white Gaussian noise (AWGN). The better bit-error-rate (BER) and packet-error-rate (PER) performance as compared to a set of least-mean-square (LMS) DFEs is achieved. The presented MLP/BP-based MIMO DFE under the severe ISI channels with ACI and AWGN can improve over 1.5dB at PER=10-1 and BER=10-3.

In this work, we base on multi-layered perceptron neural networks with backpropagation algorithm (MLP/BP) to construct soft decision feedback equalizers (DFEs). The proposal is used to recover distorted 16-point quadrature amplitude modulation (16-QAM) signal. For better performance, error control codes (ECC) are applied to enhance the accuracy of the transmitted data. From the simulations, we note that the MLP/BP-based soft DFEs with bit-interleaved TCM can recover severe distorted 16-QAM data as well as suppress intersymbol interference (ISI) and background additive white Gaussian noise (AWGN). As compared with the LMS DFE, the proposed scheme can provide better bit-error-rate (BER) and packet-error-rate (PER) performance.

This paper considers a combined coding and equalization technique applied to the magnetic recording channel. The optimization of the coded-equalization scheme for this channel requires balancing the coding rate with its associated distance gain and equalization loss. A major concern in a coded-equalization scheme using decision feedback equalization (DFE) is error propagation. A new indicator to measure the effect of error propagation when using soft decision decoding is proposed. For medium to high normalized recording densities (S>1.5), it is shown that error propagation significantly degrades the theoretical performance of a detection scheme which combines a partial response DFE and simple trellis codes. In fact, this combined system performs worse than the uncoded one. The addition of delayed decision feedback sequence estimation (DDFSE) to limit the effect of error propagation is then investigated. With a moderate decoding complexity, positive coding gains have been achieved at such densities when choosing the partial response polynomial according to the derived indicator.

The paper investigates the application of the multilayer perceptron structure to the packet wise adaptive decision feedback equalization of a M-ary QAM signal through a TDMA indoor radio channel in the presence of intersymbol interference (ISI) and additive Gaussian noise. Since the multilayer neural networks are capable of producing complex decision regions with arbitrarily nonlinear boundaries, this would greatly improve the performance of conventional decision feedback equalizer (DFE), where the decision boundaries of conventional DFE's are linear. Nevertheless, the applications of the traditional multilayer neural networks have been limited to real valued signals. To tackle this difficulty, a neural based DFE is proposed to deal with the complex QAM signal over the complex valued fading multipath radio channel without performing time consuming complex valued backpropagation training algorithms, while maintaining almost the same computational complexity as the original real valued training algorithm. Moreover, this neural based DFE trained by packet wise backpropagation algorithm would approach an ideal equalizer after receiving a sufficient number of packets. Results 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.

Decision feedback equalization (DFE) is a very effective receiver component that cancels intersymbol interference without inducing noise amplification. However, it suffers from error propagation in the start-up phase and when the environment undergoes a sudden change. For DS-CDMA wireless systems, we develop robust measures to mitigate the catastrophic error propagation effect using appropriate constraints on the receiver weight vectors. These constraints are constructed from the spreading codes of the desired user to preserve its output energy. By doing so, a desirable level of signal output power is maintained to keep the error probability low, thus preventing decision errors from occurring or propagating. Moreover, the introduction of signal-preserving constraints offers capacity of multiple access interference suppression. Efficient adaptive implementations are developed, and simulations performed to verify the effectiveness of the proposed constrained DFE detectors. It is demonstrated that the constructed constraints can eliminate the training overhead, offering complete blind implementations for multiuser decision-directed DFE filters.