Improved blind turbo detector

This paper investigates the performance of various “turbo” receivers for serially concatenated turbo codes transmitted through intersymbol interference (ISI) channels. Both the inner and outer codes are assumed to be recursive systematic convolutional (RSC) codes. The optimum turbo receiver consists of an (inner) channel maximum a posteriori (MAP) decoder and a MAP decoder for the outer code. The channel MAP decoder operates on a “supertrellis” which incorporates the channel trellis and the trellis for the inner error-correcting code. This is referred to as the MAP receiver employing a SuperTrellis (STMAP). Since the complexity of the supertrellis in the STMAP receiver increases exponentially with the channel length, we propose a simpler but suboptimal receiver that employs the predictive decision feedback equalizer (PDFE). The key idea in this paper is to have the feedforward part of the PDFE outside the iterative loop and incorporate only the feedback part inside the loop. We refer to this receiver as the PDFE-STMAP. The complexity of the supertrellis in the PDFE-STMAP receiver depends on the inner code and the length of the feedback part. Investigations with Proakis B, Proakis C (both channels have spectral nulls with all zeros on the unit circle and hence cannot be converted to a minimum phase channel) and a minimum phase channel reveal that at most two feedback taps are sufficient to get the best performance. A reduced-state STMAP (RS-STMAP) receiver is also derived which employs a smaller supertrellis at the cost of performance.

In this paper, we propose a concatenated code by combining a Recursive Systematic Convolutional (RSC) code with a Low-Density Parity-Check (LDPC) code. The proposed concatenated code is encoded in parallel by an RSC encoder and an LDPC encoder without interleavers between them. When decoding the proposed concatenated code, the information bits are decoded by two decoding algorithms, and soft information is exchanged between the RSC decoder and the LDPC decoder. This allows for the elimination of wrong codewords output by each decoder. The use of an LDPC code allows us to halt the decoding process when the valid codeword is obtained. We evaluate the error rate performance of the proposed concatenated code by computer simulations. We show that the proposed concatenated code does not have a high error floor, and achieves better BLock Error Rate (BLER) performance than either conventional LDPC codes or conventional turbo codes in the high Eb/No region. We also show that since the proposed concatenated code can correct wrong codewords output by each decoder, it achieves better BLER than the regular LDPC code at the same Bit Error Rate (BER).

In this paper, we present a semi‐analytical approach for analyzing the serial concatenation (SCC) of a high rate convolutional code and a precoded intersymbol interference (ISI) channel. The significance of the proposed approach is that it can be used to identify, for a given outer high rate code and fixed ISI channel, the precoder that results in the lowest error rate floor. In estimating the bit error performance in the floor region, we use analytical techniques developed for trellis codes to compute the overall system minimum squared Euclidean distance, and then use a semi‐analytical approach to find the corresponding multiplicity. We also demonstrate via simulations that the proposed technique may be extended to fading ISI channels with favorable results. We give examples that support our analysis. Copyright © 2006 John Wiley & Sons, Ltd.

The authors consider the use of multidimensional signaling and block demodulation for digital transmission over intersymbol interference (ISI) channels. As an example, the theory is developed for the unit-memory 1+ alpha z/sup -1/ channel. The authors first explain why multidimensional signals should be used over ISI channels by showing how the minimum Euclidean distance and the cutoff rate R/sub 0/ increase by increasing the dimensionality of the signals transmitted. Two ways of increasing the reliability of transmission over an ISI channel are discussed. The first way consists of increasing the energy associated with the symbols more affected by ISI. The second way uses a coding scheme which selectively protects those symbols. Generalized concatenated-codes are advocated for this purpose. >

We present a novel iterative (turbo) receiver with tunable complexity for reliable detection of (uncoded) payload data transmitted over long intersymbol interference (ISI) channels affected by crosstalk, as those typically encountered in emerging HDSL2 services standardized by ANSI T1.418 recommendation. The proposed receiver combines in an original way "minimum mean square error (MMSE) estimation principle," "turbo-processing principle" and "crosstalk-prediction principle" for achieving both suboptimal maximum a posteriori probability channel equalization and reliable soft-mitigation of ISI tail plus crosstalk. More in detail, according to the turbo-processing principle, at each iteration suitable extrinsic information is extracted from the equalizing and interference-canceling modules and used as "a priori information" for the next iteration. Several simulation results on typical HDSL-like test-loops confirm the superiority of the proposed turbo-detector (TD) over current solutions based on conventional MMSE decision-feedback equalizers and precoders (such as the Tomlinson-Harashima precoder). The numerical tests also point out that performance of the presented TD on typical high bit-rate digital subscriber lines (HDSL) is not limited by error-floor phenomena, even at error-probabilities below 10/sup -7/.

Wiener filter is widely used to equalize the signals over inter-symbol interference (ISI) channels because of its low complexity and optimality in terms of mean square error (MSE). However, Wiener filter is generally not optimal in terms of symbol detection error and thus can exhibit considerable error performance degradation in ISI channels. Recently, to enhance the performance of linear equalizers, lattice reduction (LR) technique is proposed, which shows significant gain for multi-input multi-output systems. In this paper, we propose LR-aided Wiener filter that aims at minimizing the MSE for the symbols in lattice-reduced domain. Simulations show that the LR-aided Wiener filter exhibits significant error performance improvement over the Wiener filter, especially for higher-order modulations.

This paper studies the application of neural networks to Viterbi detection of FTN signals in an intersymbol interference (ISI) channel. The main contribution of this paper is to propose a receiver structure for detecting FTN signals in unknown static ISI channel. In particular, we propose a novel low-complexity neural network structure for calculating the branch metrics, and we explore its suitability for FTN signalling with channel uncertainty. We compare the proposed network, which we call the Metric Net (MetNet), to a benchmark neural network-based technique for metric calculation, the ViterbiNet, which was originally designed for ISI channels. The simulation results confirm that the MetNet outperforms the ViterbiNet, with two orders of magnitude lower complexity, and is much more resilient to channel uncertainty than the traditional Viterbi detector, which uses Euclidean distance for metric calculations. We further show that the MetNet exhibits robustness to being trained at mismatched SNR values and FTN pulse acceleration factors, meaning that the number of trained models required can be significantly reduced. Additionally, the results show that the proposed MetNet remains a favorable alternative at much higher levels of channel uncertainties. The results also reflect that we can generalize the MetNet to work with different channel models defined by different decaying factors. Finally, we show that we succeed in achieving a bandwidth efficiency gain of 33% due to FTN by using the MetNet in the presence of channel uncertainty.

Motivated by recent high bandwidth communication systems, Inter-Symbol Interference (ISI) channels with 1-bit quantized output are considered under an average-power-constrained continuous input. While the exact capacity is difficult to characterize, an approximation that matches with the exact channel output up to a probability of error is provided. The approximation does not have additive noise, but constrains the channel output (without noise) to be above a threshold in absolute value. The capacity under the approximation is computed using methods involving standard Gibbs distributions. Markovian achievable schemes approaching the approximate capacity are provided. The methods used over the approximate ISI channel result in ideas for practical coding schemes for ISI channels with 1-bit output quantization.

In this paper, we introduce a simulation-based method to compute the information rates of intersymbol interference (ISI) channels with signal-dependent Gaussian noise when the inputs are binary and independent identically distributed. The method extends the idea in Arnold et al. (2001), which focuses on the ISI channels with additive white Gaussian noise (AWGN). With the new method, we can compute the information rates of the Lorentzian channels with media noise that represents a suitable model for practical magnetic recording channels.

In this paper, we investigate the theory of using tail-biting recursive systematic convolutional (RSC) codes in Turbo codes. Tail-biting is not always possible for a given RSC code with some length. The condition of tail-biting RSC and What length is suitable for such RSC will be studied.

Recently relay networks have attracted a lot of attention for their potential to increase spatial diversity. However, limited attention has been paid to practical detector design and implementation issues. In this paper, we investigate the design of maximum-likelihood detectors for half-duplex amplify-and-forward relay networks in intersymbol interference (ISI) channels. In particular, we study the case when the relay period is long, which results in an effective channel impulse response that is sparse and periodically time-varying. The proposed design provides a good performance/complexity tradeoff.

In this paper, we address the design of Cooperative communication with coding schemes for the 3-node relay channel with half-duplex constraint. Based on an analysis of the extrinsic information transfer characteristics (EXIT) chart of the component codes we investigate the potential of Turbo codes which are employed by the source node in order to increase the reliability of the system. The source node transmits coded symbols to both the relay and the destination nodes during the first transmission period. The relay performs parallel concatenated codes decoding. It then re-encodes the information bits using a Recursive Systematic Convolutional (RSC) code during the second transmission period. The resultant symbols transmitted from the source and relay nodes can be viewed as the coded symbols of a three-component parallel-concatenated encoder. Thus the EXIT chart is used for iterative decoding and it is helpful to find the best constituent coding schemes for creating parallel concatenated codes for cooperative communication. Thus by considering the interleaver size, code rate and code polynomial we can design a system for cooperative communication using Turbo codes.

A new concept of Bit Geometrical Uniformity (BGU) is introduced to help the analysis and estimation of performance of systems with Iterative Detection/Decoding (ID). It is also shown that the BGU labelings of the signal constellation allows a fast search for best component binary Recursive Systematic Convolutional (RSC) codes of a BICM-ID system using both of overall and in-line interleaving. Best rate-1/2 RSC codes are reported for 4PSK constellation as an example. The new concept and new search method can be directly extended to MPSK and MQAM constellations.

Punctured turbo codes may show poor performance for some specific code rates, due to uneven error protection of input bits after puncturing. In this paper, such phenomenon is analyzed by considering the structure of recursive systematic convolutional (RSC) code and, new design criteria of interleaver are proposed such that the information bits are protected as equally as possible. Simulation results confirm that the proposed interleaver show good performance for the specific code rates considered.

Rate and diversity impose a fundamental trade-off in communications. This trade-off was investigated for flat-fading channels in as well as for Inter-symbol Interference (ISI) channels in . A different point of view was explored in where high-rate codes were designed so that they have a high-diversity code embedded within them. These diversity embedded codes were investigated for flat fading channels both from an information-theoretic viewpoint and from a coding theory viewpoint in . In this paper, we explore the use of diversity embedded codes for inter-symbol interference channels. In particular the main result of this paper is that the diversity multiplexing trade-off for fading MISO/SIMO/SISO ISI channels is indeed successively refinable. This implies that for fading ISI channels with a single degree of freedom one can embed a high diversity code within a high rate code without any performance loss (asymptotically). This is related to a deterministic structural observation about the asymptotic behavior of frequency response of channel with respect to fading strength of time domain taps as well as a coding scheme to take advantage of this observation.