A Unifying Study of Robust Decision Feedback Equalisers

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.

In this paper, a cyclic-prefixed (CP) system with pulse amplitude modulation (PAM) for uplink transmission in light-fidelity (LiFi) is discussed. LiFi supports bi-directional transmission, i.e., downlink and uplink transmissions. However, there have been only a few studies on uplink LiFi despite the fact that the uplink traffic demand increases due to frequent use of, for example, video call and live streaming services. The uplink transmission is designed such that a transmitter has a low peak-to-average ratio as well as a lower computational complexity using a CP in conjunction with PAM. We investigate three different schemes, namely linear equalization (LE) where only a feedforward filter is applied, decision feedback equalization (DFE) where a feedback filter is added at the receiver and Tomlinson-Harashima precoder (THP) where a feedback filter is added at the transmitter. Both feedforward and feedback filters are jointly optimized. In addition, we consider an optical wireless channel with reflections, randomly-located and randomly-oriented user equipment, a human body acting as a reflector and a limited linear dynamic range of a light emitting diode. We conclude that a DFE system is suitable in a low spectral efficiency region, where, compared to an LE system, up to 4 dB gain is achieved. A THP system is suitable for a high spectral efficiency region, where up to 5 dB gain compared to the LE and DFE systems is achieved.

In broadband wireless communication systems, single-carrier transmission with frequency domain equalization (SC-FDE) is regarded as an alternative modulation technique to the orthogonal frequency division multiplexing (OFDM). Compared with OFDM systems, SC-FDE has similar implementation complexity and performance. However, SC-FDE with linear equalizer will suffer from serious performance deterioration under deep frequency selective fading channels. An effective method to solve this problem is to introduce non-linear decision feedback equalization (DFE) to SC-FDE. In this paper, a low complexity iterative decision feedback equalizer in the frequency domain for single- carrier systems is proposed. Based on the minimum mean square error (MMSE) criterion, a simplified parameter estimation method is introduced to calculate the coefficients of the feed-forward and feedback filters, which reduces the implementation complexity of the equalizer. Simulations show that the performance of the proposed algorithm is similar to the traditional iterative block DFE (IBDFE) under various multipath fading channels but with lower complexity.

The nonlinear decision feedback equalizer (DFE) provides significantly lower symbol error rates than a linear equalizer, but for the high speed digital transmission systems which shows more serious inter-symbol interference (ISI) the DFE suffers large steady-state mean square error (MSE) and slow convergence rate. So a new DFE is proposed, which consists of a feedforward filter based on T/2 fractionally-spaced structure and a feedback filter based on baud-spaced structure and uses a dual-mode algorithm. The efficiency of the method is proved by computer simulation.

In a companion paper, we have studied the zero-forcing (ZF) transceiver with decision feedback equalizer (DFE) over slowly time-varying narrowband multiinput multioutput (MIMO) channels. The space-time generalized triangular decomposition (ST-GTD) was used for the design of ZF-DFE transceivers. The space-time geometric mean decomposition (ST-GMD) ZF transceiver minimizes both the arithmetic mean square error (MSE) at the feedback detector and the average uncoded bit error rate (BER) in moderate high signal-to-noise ratio (SNR). This paper addresses the design problem of DFE transceiver without zero-forcing constraint. In the first part, a channel independent temporal precoder is superimposed on the conventional block-wise GMD-based minimum mean square error (MMSE) DFE transceiver to take advantage of the temporal diversity. In the second part, ST-GTD is applied for the design of MMSE DFE transceivers. With accurate channel prediction and space-time powerloading, the proposed ST-GMD MMSE transceiver minimizes the arithmetic MSE at the feedack detector, and maximizes Gaussian mutual information. For practical applications, the ST-GTD MMSE transceiver which does not require channel prediction but shares the same asymptotic BER performance with the ST-GMD MMSE system is also developed. In the convex region, our analysis shows that the proposed MMSE transceivers has better BER performance than the conventional GMD-based MMSE transceiver; the average BERs of the proposed systems are nonincreasing functions of the ST-block size. The superior performance of ST-GMD MMSE transceiver over the ST-GMD ZF transceiver is also verified analytically.

An LMI approach to design robust fault detection filter for uncertain LTI systems

The addressed blind decision feedback equalizer (DFE) reverses the classical order of its feed-forward and feedback filters at the beginning of adaptation to achieve the best equalization of the minimum and maximum phase components of a channel transfer function. Although very effective, this blind equalization approach deals with the feedback filter mismatch at the time of its transformation from the front-end all-pole whitener of the received signal to the decision-directed feedback equalizer placed after the feedforward filter. To eliminate this weakness, the adaptive neuron slope is introduced instead of the fixed one into the stochastic gradient whitening algorithm based on the joint entropy maximization cost. The performance of the innovated algorithm is verified by simulating m-QAM (quadrature amplitude modulation) signals transmission over multipath channels. The algorithm with the adaptive neuron slope achieves a better whitening of the received signal spectrum, and, hence, increases the equalization successfulness.

Multiple-input multiple-output (MIMO) digital communication systems have received great attention due to their potential of increasing the overall system throughput. In such systems, MIMO decision feedback equalization (DFE) schemes are often used to mitigate intersymbol interference (ISI) resulting from channel multipath propagation. In this context, the existing computationally efficient methods for exact estimation of the DFE filters under minimum mean-square-error criteria (MMSE-DFE) rely on fast Cholesky decomposition and backsubstitution or Levinson techniques. These methods may still present several difficulties in implementation as the demand on higher transmission rates increases, and thus a simple solution is necessary. In this paper, new procedures for fast computation of the MIMO-MMSE-DFE are presented. The new algorithms are obtained from a simple observation, namely, that the optimal feedforward filter (FFF) is related to the well-known Kalman gain matrix, commonly encountered in fast recursive least squares adaptive algorithms-for which fast recursions exist and are readily applicable. Moreover, the feedback filter can be easily computed via stable fast MIMO convolution techniques. As a result, the proposed method is less complex, more structured, and can be as reliable in finite precision as known approaches in the literature.

We approach the multiple input multiple output (MIMO) decision feedback equalization (DFE) problem in digital communications from an H/sup /spl infin// estimation point of view. Using the standard (and simplifying) assumption that all previous decisions are correct, we obtain an explicit parameterization of all H/sup /spl infin// optimal DFEs. In particular, we show that, under the above assumption, minimum mean square error (MMSE) DFEs are H/sup /spl infin// optimal. The H/sup /spl infin// approach also suggests a method for dealing with errors in previous decisions.

The author proposed soft decision feedback equalisation for orthogonal frequency division multiplexing (OFDM) transmission over doubly selective channels which is used for turbo equalisation. The doubly selective channel is approximated using the basis expansion model (BEM). The decision feedback equaliser (DFE) is obtained and updated for every sub-carrier which results in a per-tone DFE. On the basis of the Gaussian approximation, expressions for the a priori, the a posteriori and the extrinsic information have been derived for quadrature phase shift keying (QPSK) modulation. For turbo equalisation, where iterative joint channel equalisation and channel decoding is executed, in the first iteration, estimates are based on the feed-forward filter which are fed to the channel decoder. These estimates are not reliable and may incur error propagation and poor turbo equalisation performance. For more reliable estimates in the first iteration, the DFE is initialised as a linear minimum mean square error (LMMSE) equaliser. The per-tone LMMSE soft-output equaliser is also derived, and expressions for the a priori, a posteriori and extrinsic information are obtained viewing the LMMSE equaliser as a special case of the DFE. The extrinsic information in both cases was derived based on the Gaussian approximation. Numerical results for bit-error rate performance assuming the BEM channel model and Jakes' channel model are shown to confirm our findings.

Radial basis function (RBF) network based channel equalisers have a close relationship with Bayesian schemes. Decision feedback is introduced in the design of the RBF equaliser in order to reduce its computational complexity. The RBF decision feedback equaliser (DFE) was found to give similar performance to the conventional mean square error (MSE) DFE over Gaussian channels using various quadrature amplitude modulation (QAM) schemes, while requiring a lower feedforward and feedback order. Over Rayleigh-fading channels similar findings were valid for binary modulation, while for higher order modems the RBF based DFE requires increased feedforward and feedback orders in order to outperform the conventional MSE DFE scheme.

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.

Interpolated decision feedback equalization for long intersymbol interference channels

This paper proposes an enhanced decision feedback equalizer (DFE) for filter bank multicarrier (FBMC) systems over offset quadrature amplitude modulation (OQAM) based on a minimal mean square error (MMSE) criterion. For each subcarrier, besides one feedforward (FF) filter and one feedback (FB) filter, we add two intercarrier interference (ICI)-suppressing filters, which feed back detected precursors extracted from neighboring subchannels to enhance ICI suppression in the presence of multipath channels. Our simulation results indicate our proposal makes a considerable improvement comparing with MMSE-DFE under a severe ICI and ISI scenario despite few extra costs in computational complexity.

In order to overcome the MAI and ISI problems in time-varying multipath fading channels, a novel H/sub /spl infin//-subweight algorithm for the decision feedback equalizer (DFE) in a DS-CDMA system is presented. The subweight technique can reduce the computational load of the H/sub /spl infin// algorithm, but dynamic estimation error in subweight partition may degrade performance. The advantage of insensitivity to modeling error of the H/sub /spl infin// algorithm just can mitigate the degradation of the subweight technique. Therefore, the individual advantages of the H/sub /spl infin// algorithm and subweight technique can be successfully integrated. The H/sub /spl infin//-subweight algorithm owns the advantages of low complexity and robustness against modeling error caused by the time-varying multipath channels as well as subweight partition. On the other hand, the RLS-subweight algorithm seriously suffers from the drawback of dynamic estimation error. The reduction of computational complexity by subweight partition is analyzed. Simulation results show that the H/sub /spl infin//-subweight DPE outperforms the RLS-subweight DFE in suppressing equalization error.