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58
Per-Survivor Processing: A General Approach to MLSE in Uncertain Environments
- IEEE Trans. Commun
, 1995
"... Per-Survivor Processing (PSP) provides a general framework for the approximation of Maximum Likelihood Sequence Estimation (MLSE) algorithms whenever the presence of unknown quantities prevents the precise use of the classical Viterbi algorithm. This principle stems from the idea that data-aided est ..."
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Cited by 90 (0 self)
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Per-Survivor Processing (PSP) provides a general framework for the approximation of Maximum Likelihood Sequence Estimation (MLSE) algorithms whenever the presence of unknown quantities prevents the precise use of the classical Viterbi algorithm. This principle stems from the idea that data-aided estimation of unknown parameters may be embedded into the structure of the Viterbi algorithm itself. Among the numerous possible applications, we concentrate here on (a) adaptive MLSE, (b) simultaneous Trellis Coded Modulation (TCM) decoding and phase synchronization, (c) adaptive Reduced State Sequence Estimation (RSSE). As a matter of fact, PSP is interpretable as a generalization of decision feedback techniques of RSSE to decoding in the presence of unknown parameters. A number of algorithms for the simultaneous estimation of data sequence andunknown channel parameters are presented and compared with "conventional" techniques based on the use of tentative decisions. Results for uncoded modu...
Multichannel Blind Identification: From Subspace to Maximum Likelihood Methods
- Proc. IEEE
, 1998
"... this paper is to review developments in blind channel identification and estimation within the estimation theoretical framework. We have paid special attention to the issue of identifiability, which is at the center of all blind channel estimation problems. Various existing algorithms are classified ..."
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Cited by 50 (2 self)
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this paper is to review developments in blind channel identification and estimation within the estimation theoretical framework. We have paid special attention to the issue of identifiability, which is at the center of all blind channel estimation problems. Various existing algorithms are classified into the moment-based and the maximum likelihood (ML) methods. We further divide these algorithms based on the modeling of the input signal. If input is assumed to be random with prescribed statistics (or distributions), the corresponding blind channel estimation schemes are considered to be statistical. On the other hand, if the source does not have a statistical description, or although the source is random but the statistical properties of the source are not exploited, the corresponding estimation algorithms are classified as deterministic. Fig. 2 shows a map for different classes of algorithms and the organization of the paper.
Equalization Concepts for EDGE
- IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
, 1999
"... In this paper, an equalization concept for the novel radio access scheme EDGE (Enhanced Data Rates for GSM Evolution) is proposed, by which high performance can be obtained at moderate computational complexity. Because high-level modulation is employed in EDGE, optimum equalization as usually perfor ..."
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Cited by 19 (9 self)
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In this paper, an equalization concept for the novel radio access scheme EDGE (Enhanced Data Rates for GSM Evolution) is proposed, by which high performance can be obtained at moderate computational complexity. Because high-level modulation is employed in EDGE, optimum equalization as usually performed in GSM (Global System for Mobile Communications) receivers is too complex, and suboptimum schemes have to be considered. It is shown that delayed decision-feedback sequence estimation (DDFSE) and reduced-state sequence estimation (RSSE) are promising candidates. For various channel profiles, approximations for the bit error rate of these suboptimum equalization techniques are given and compared with simulation results for DDFSE. It turns out that a discrete-time prefilter creating a minimum-phase overall impulse response is indispensible for a favourable tradeoff between performance and complexity. Additionally, the influence of channel estimation and of the receiver input filter is investigated, and the reasons for performance degradation compared to the additive white Gaussian noise channel are indicated. Finally, the overall system performance attainable with the proposed equalization concept is determined for transmission with channel coding.
Capacity, mutual information, and coding for finite-state Markov channels
- IEEE Trans. Inform. Theory
, 1996
"... Abstract The Finite-State Markov Channel (FSMC) is a discrete-time varying channel whose variation is determined by a finite-state Markov process. These channels have memory due to the Markov channel variation. We obtain the FSMC capacity as a function of the conditional channel state probability. W ..."
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Cited by 13 (2 self)
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Abstract The Finite-State Markov Channel (FSMC) is a discrete-time varying channel whose variation is determined by a finite-state Markov process. These channels have memory due to the Markov channel variation. We obtain the FSMC capacity as a function of the conditional channel state probability. We also show that for i.i.d. channel inputs, this conditional probability converges weakly, and the channel's mutual information is then a closed-form continuous function of the input distribution. We next consider coding for FSMCs. In general, the complexity of maximum-likelihood decoding grows exponentially with the channel memory length. Therefore, in practice, interleaving and memoryless channel codes are used. This technique results in some performance loss relative to the inherent capacity of channels with memory. We propose a maximum-likelihood decisionfeedback decoder with complexity that is independent of the channel memory. We calculate the capacity and cutoff rate of our technique, and show that it preserves the capacity of certain FSMCs. We also compare the performance of the decision-feedback decoder with that of interleaving and memoryless channel coding on a fading channel with 4PSK modulation.
The structure and design of realizable decision feedback equalizers for IIR channels with coloured noise
, 1990
"... A simple algorithm for optimizing decision feedback equalizers by minimizing the mean square error (MSE) is presented. A complex baseband channel and correct past decisions are assumed. The dispersive channel may have infinite impulse response and the noise may be coloured. We consider optimal reali ..."
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Cited by 12 (9 self)
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A simple algorithm for optimizing decision feedback equalizers by minimizing the mean square error (MSE) is presented. A complex baseband channel and correct past decisions are assumed. The dispersive channel may have infinite impulse response and the noise may be coloured. We consider optimal realizable (stable and finite-lag smoothing) forward and feedback filters in discrete time. They are parametrized as recursive filters. In the special case of transmission channels with finite impulse response and autoregressive noise, the minimum MSE can be attained with transversal feedback and forward filters. In general, the forward part should include a noise-whitening filter (the inverse noise model). The finite realizations of the filters are calculated using a polynomial equation approach to the linear quadratic optimization problem. The equalizer is optimized essentially by solving a system of linear equations Ax = B, where A contains transfer function coefficients from the channel and ...
The Viterbi algorithm and Markov noise memory
- IEEE Trans. Inform. Theory
, 2000
"... Abstract—This work designs sequence detectors for channels with intersymbol interference (ISI) and correlated (and/or signal-dependent) noise. We describe three major contributions. i) First, by modeling the noise as a finite-order Markov process, we derive the optimal maximum-likelihood sequence de ..."
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Cited by 12 (2 self)
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Abstract—This work designs sequence detectors for channels with intersymbol interference (ISI) and correlated (and/or signal-dependent) noise. We describe three major contributions. i) First, by modeling the noise as a finite-order Markov process, we derive the optimal maximum-likelihood sequence detector (MLSD) and the optimal maximum a posteriori (MAP) sequence detector, extending to the correlated noise case the Viterbi algorithm. We show that, when the signal-dependent noise is conditionally Gauss–Markov, the branch metrics in the MLSD are computed from the conditional second-order noise statistics. We evaluate the branch metrics using a bank of finite impulse response (FIR) filters. ii) Second, we characterize the error performance of the MLSD and MAP sequence detector. The error analysis of these detectors is complicated by the correlation asymmetry of the channel noise. We derive upper and lower bounds and computationally efficient approximations to these bounds based on the banded structure of the inverses of Gauss–Markov covariance matrices. An experimental study shows the tightness of these bounds. iii) Finally, we derive several classes of suboptimal sequence detectors, and demonstrate how these and others available in the literature relate to the MLSD. We compare their error rate performance and their relative computational complexity, and show how the structure of the MLSD and the performance evaluation guide us in choosing a best compromise between several types of suboptimal sequence detectors. Index Terms—Correlated noise, Gauss–Markov processes, intersymbol
Iterative Equalization and Decoding with Channel Shortening Filters for Space-Time Coded Modulation
- in IEEE Vehicular Technology Conference (VTC
, 2000
"... We consider space-time trellis coded modulation in frequency selective channels. We discuss the outage capacity of space-time trellis coded modulation compared to the capacity of the underlying MIMO channel. Furthermore, we derive FIR channel shortening filters which are used as prefilters for turbo ..."
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Cited by 10 (3 self)
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We consider space-time trellis coded modulation in frequency selective channels. We discuss the outage capacity of space-time trellis coded modulation compared to the capacity of the underlying MIMO channel. Furthermore, we derive FIR channel shortening filters which are used as prefilters for turbo equalization in order to reduce the number of equalizer states. We show that we can compensate for part of the performance loss due to channel shortening by turbo iterations and a transformation of time diversity to a form of spatial diversity.
Reduced-complexity space-time turbo-equalization for frequency-selective MIMO channels
- IEEE Trans. Wireless Commun
, 2002
"... Abstract—We consider turbo equalization of space–time-coded transmission over frequency-selective fading multiple-input–multiple-output (MIMO) channels. A MIMO finite-impulse-response prefilter is proposed and shown to reduce the turbo equalizer complexity significantly at a small performance loss. ..."
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Cited by 9 (1 self)
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Abstract—We consider turbo equalization of space–time-coded transmission over frequency-selective fading multiple-input–multiple-output (MIMO) channels. A MIMO finite-impulse-response prefilter is proposed and shown to reduce the turbo equalizer complexity significantly at a small performance loss. Advantages of the proposed scheme are that we do not alter the equalization algorithm or require the channel to be minimum phase. The prefiltered turbo equalizer is an attractive receiver structure for broadband wireless transmission using spectrally-efficient high-order modulation schemes as in EDGE. Index Terms—Channel-shortening filters, space–time codes, transmit diversity, turbo equalization.
Pattern-Dependent Noise Prediction in Signal-Dependent Noise
, 2001
"... Maximum and near-maximum likelihood sequence detectors in signal-dependent noise are discussed. It is shown that the linear prediction viewpoint allows a very simple derivation of the branch metric expression that has previously been shown as optimum for signal-dependent Markov noise. The resulting ..."
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Cited by 9 (3 self)
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Maximum and near-maximum likelihood sequence detectors in signal-dependent noise are discussed. It is shown that the linear prediction viewpoint allows a very simple derivation of the branch metric expression that has previously been shown as optimum for signal-dependent Markov noise. The resulting detector architecture is viewed as a noise predictive maximum likelihood detector that operates on an expanded trellis and relies on computation of branch-specific, patterndependent noise predictor taps and predictor error variances. Comparison is made on the performance of various low-complexity structures using the position-jitter/width-variation model for transition noise. It is shown that when medium noise dominates, a reasonably low complexity detector that incorporates pattern-dependent noise prediction achieves a significant signal-to-noise ratio gain relative to the extended class 4 partial response maximum likelihood detector. Softoutput detectors as well as the use of soft decision feedback are also discussed in the context of signaldependent noise.
Integrated Circuits for Data Transmission Over Twisted-Pair Channels
, 1997
"... This tutorial paper discusses typical architectures and challenges in designing integrated circuits for data transmission over twisted-pair wire channels. To highlight the various architectural approaches, two main applications are discussed---high-bit-rate digital subscriber loop (HDSL) and fast-et ..."
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Cited by 8 (1 self)
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This tutorial paper discusses typical architectures and challenges in designing integrated circuits for data transmission over twisted-pair wire channels. To highlight the various architectural approaches, two main applications are discussed---high-bit-rate digital subscriber loop (HDSL) and fast-ethernet. Although these two applications have orders of magnitude difference in their bit rates, they share many common building blocks including line-drivers, 2--4 wire hybrids, echo cancellation, digital equalization, and clock recovery. Typical integrated circuit approaches for realizing each of these blocks are presented as well as possible tradeoffs. Finally, future challenges facing integrated circuit designers are presented. Index Terms---Clock recovery, digital transmission, echo cancellation, equalization. I. INTRODUCTION D UE to the abundance and low-cost of unshielded twistedpair (UTP) cables, there is great interest in transmitting high-speed data over UTP cable. However, ther...

