The Experts below are selected from a list of 312 Experts worldwide ranked by ideXlab platform
Paul H Siegel - One of the best experts on this subject based on the ideXlab platform.
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markov processes asymptotically achieve the capacity of finite state Intersymbol Interference channels
IEEE Transactions on Information Theory, 2008Co-Authors: Jiangxin Chen, Paul H SiegelAbstract:Recent progress in capacity evaluation has made it possible to compute a sequence of lower bounds on the capacity of a finite-state Intersymbol-Interference (ISI) channel by finding a sequence of optimized Markov input processes with increasing order , for which the state of the process is the previous input symbols. In this correspondence, we prove that, as the order goes to infinity, the sequence of optimized Markov sources asymptotically achieves the capacity of the channel. The conclusion is extended to two-dimensional finite-state ISI channels, the binary symmetric channel (BSC) with constrained inputs, and general indecomposable finite-state channels with a mild constraint.
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Determining and Approaching Achievable Rates of Binary Intersymbol Interference Channels Using Multistage Decoding
IEEE Transactions on Information Theory, 2007Co-Authors: Soriaga Joseph Binamira, Henry D Pfister, Paul H SiegelAbstract:By examining the achievable rates of a multistage decoding system on stationary ergodic channels, we derive lower bounds on the mutual information rate corresponding to independent and uniformly distributed (i.u.d.) inputs, also referred to as the i.u.d. information rate. For binary Intersymbol Interference (ISI) channels, we show that these bounds become tight as the number of decoding stages increases. Our analysis, which focuses on the marginal conditional output densities at each stage of decoding, provides an information rate corresponding to each stage. These rates underlie the design of multilevel coding schemes, based upon low-density parity-check (LDPC) codes and message passing, that in combination with multistage decoding approach the i.u.d. information rate for binary ISI channels. We give example constructions for channel models that have been commonly used in magnetic recording. These examples demonstrate that the technique is very effective even for a small number of decoding stages
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markov processes asymptotically achieve the capacity of finite state Intersymbol Interference channels
International Symposium on Information Theory, 2004Co-Authors: Jiangxin Chen, Paul H SiegelAbstract:Magnetic recording channels are generally modeled as finite-state linear Intersymbol Interference (ISI) channels with additive white Gaussian noise and a binary input constraint. Lower bounds on the channel capacity have been computed by using this technique to estimate the information rates of optimized, order-r Markov input processes. RLL-constrained binary symmetric channel (BSC) and for two-dimensional finite-state ISI channels is proved in this paper
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on the symmetric information rate of two dimensional finite state isi channels
Information Theory Workshop, 2003Co-Authors: Jiangxin Chen, Paul H SiegelAbstract:We derive upper and lower bounds on the symmetric information rate of a two-dimensional finite-state Intersymbol-Interference (ISI) channel model.
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constrained coding for binary channels with high Intersymbol Interference
IEEE Transactions on Information Theory, 1999Co-Authors: R Karabed, Paul H Siegel, Emina SoljaninAbstract:Partial-response (PR) signaling is used to model communications channels with Intersymbol Interference (ISI) such as the magnetic recording channel and the copper-wire channel for digital subscriber lines. Coding for improving noise immunity in higher order partial-response channels, such as the "extended" class-4 channels denoted EPR4, E/sup 2/PR4, E/sup 3/PR4, has become an important subject as the linear densities in magnetic recording approach those at which these partial-response channels are the best models of real channels. In this paper, we consider partial-response channels for which ISI is so severe that the channels fail to achieve the matched-filter bound (MFB) for symbol error rate, assuming maximum-likelihood decoding. We show that their performance can be improved to the MFB by high-rate codes based on constrained systems, some of which may even simplify the Viterbi (1979) detectors relative to the uncoded channels. We present several examples of high-rate constrained codes for E/sup 2/PR4 and E/sup 3/PR4 channels and evaluate their performance by simulation.
T Fujino - One of the best experts on this subject based on the ideXlab platform.
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an adaptive maximum likelihood sequence estimator for fast time varying Intersymbol Interference channels
IEEE Transactions on Communications, 1994Co-Authors: H Kubo, K Murakami, T FujinoAbstract:This paper proposes an adaptive maximum-likelihood sequence estimator (MLSE), which is a suboptimum approximation to the adaptive maximum-likelihood detector and is capable of tracking fast time-varying Intersymbol Interference (ISI) channels. The adaptive MLSE consists of a channel estimator and an MLSE implemented by the Viterbi algorithm (VA). The novel feature of the proposed adaptive MLSE is a channel estimation scheme, where the channel estimation is accomplished for each state in the VA along the surviving path connected to each state. This MLSE makes it possible to estimate a channel impulse response without an influence of a decision delay inherent in the VA, and the performance and complexity of the proposed procedure is controlled by the memory length of the VA. The bit error rate performance of the proposed MLSE is confirmed by experimental results. It is shown that the proposed MLSE has a capability of excellent tracking performance in a severe environment caused by fast time-varying ISI, for example frequency selective multipath fading in digital mobile radio communications. >
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an adaptive maximum likelihood sequence estimator for fast time varying Intersymbol Interference channels
IEEE Transactions on Communications, 1994Co-Authors: H Kubo, K Murakami, T FujinoAbstract:This paper proposes an adaptive maximum-likelihood sequence estimator (MLSE), which is a suboptimum approximation to the adaptive maximum-likelihood detector and is capable of tracking fast time-varying Intersymbol Interference (ISI) channels. The adaptive MLSE consists of a channel estimator and an MLSE implemented by the Viterbi algorithm (VA). The novel feature of the proposed adaptive MLSE is a channel estimation scheme, where the channel estimation is accomplished for each state in the VA along the surviving path connected to each state. This MLSE makes it possible to estimate a channel impulse response without an influence of a decision delay inherent in the VA, and the performance and complexity of the proposed procedure is controlled by the memory length of the VA. The bit error rate performance of the proposed MLSE is confirmed by experimental results. It is shown that the proposed MLSE has a capability of excellent tracking performance in a severe environment caused by fast time-varying ISI, for example frequency selective multipath fading in digital mobile radio communications. >
Gregory W. Wornell - One of the best experts on this subject based on the ideXlab platform.
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super nyquist rateless coding for Intersymbol Interference channels
arXiv: Information Theory, 2019Co-Authors: Uri Erez, Gregory W. WornellAbstract:A rateless transmission architecture is developed for communication over Gaussian Intersymbol Interference channels, based on the concept of super-Nyquist (SNQ) signaling. In such systems, the signaling rate is chosen significantly higher than the Nyquist rate of the system. We show that such signaling, when used in conjunction with good "off-the-shelf" base codes, simple linear redundancy, and minimum mean-square error decision feedback equalization, results in capacity-approaching, low-complexity rateless codes for the time-varying Intersymbol-Interference channel. Constructions for both single-input / single-output (SISO) and multi-input / multi-output (MIMO) ISI channels are developed.
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A class of block-iterative equalizers for Intersymbol Interference channels: fixed channel results
IEEE Transactions on Communications, 2001Co-Authors: A.m. Chan, Gregory W. WornellAbstract:A new and efficient class of nonlinear equalizers is developed for Intersymbol Interference (ISI) channels. These -"iterated-decision equalizers" use an optimized multipass algorithm to successively cancel ISI from a block of received data and generate symbol decisions whose reliability increases monotonically with each iteration. These equalizers have an effective complexity comparable to the decision-feedback equalizer (DFE), yet asymptotically achieve the performance of maximum-likelihood sequence detection (MLSD). We show that, because their structure allows cancellation of both precursor and postcursor ISI, iterated-decision equalizers outperform the minimum mean-square error DFE by 2.507 dB on severe ISI channels even with uncoded systems. Moreover, unlike the DFE, iterated-decision equalizers can be readily used in conjunction with error-control coding, making them attractive for a wealth of applications.
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A class of block-iterative equalizers for Intersymbol Interference channels
2000 IEEE International Conference on Communications. ICC 2000. Global Convergence Through Communications. Conference Record, 2000Co-Authors: A.m. Chan, Gregory W. WornellAbstract:A new and efficient class of nonlinear equalizers is introduced for Intersymbol Interference (ISI) channels. These "iterated-decision equalizers" use an optimized multipass algorithm to successively cancel ISI from a block of received data and generate symbol decisions whose reliability increases monotonically with each iteration. Asymptotically they achieve the performance of maximum-likelihood sequence detection (MLSD), but only have a computational complexity on the order of a linear equalizer (LE). And because their structure allows cancellation of both pre- and post-cursor ISI, iterated-decision equalizers outperform the minimum mean-square error decision-feedback equalizer (DFE) by 2.5 dB on severe ISI channels even with uncoded systems. Even more importantly, unlike the DFE, iterated-decision equalizers can be readily used in conjunction with error-control coding, making them attractive for a wealth of applications.
H Kubo - One of the best experts on this subject based on the ideXlab platform.
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an adaptive maximum likelihood sequence estimator for fast time varying Intersymbol Interference channels
IEEE Transactions on Communications, 1994Co-Authors: H Kubo, K Murakami, T FujinoAbstract:This paper proposes an adaptive maximum-likelihood sequence estimator (MLSE), which is a suboptimum approximation to the adaptive maximum-likelihood detector and is capable of tracking fast time-varying Intersymbol Interference (ISI) channels. The adaptive MLSE consists of a channel estimator and an MLSE implemented by the Viterbi algorithm (VA). The novel feature of the proposed adaptive MLSE is a channel estimation scheme, where the channel estimation is accomplished for each state in the VA along the surviving path connected to each state. This MLSE makes it possible to estimate a channel impulse response without an influence of a decision delay inherent in the VA, and the performance and complexity of the proposed procedure is controlled by the memory length of the VA. The bit error rate performance of the proposed MLSE is confirmed by experimental results. It is shown that the proposed MLSE has a capability of excellent tracking performance in a severe environment caused by fast time-varying ISI, for example frequency selective multipath fading in digital mobile radio communications. >
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an adaptive maximum likelihood sequence estimator for fast time varying Intersymbol Interference channels
IEEE Transactions on Communications, 1994Co-Authors: H Kubo, K Murakami, T FujinoAbstract:This paper proposes an adaptive maximum-likelihood sequence estimator (MLSE), which is a suboptimum approximation to the adaptive maximum-likelihood detector and is capable of tracking fast time-varying Intersymbol Interference (ISI) channels. The adaptive MLSE consists of a channel estimator and an MLSE implemented by the Viterbi algorithm (VA). The novel feature of the proposed adaptive MLSE is a channel estimation scheme, where the channel estimation is accomplished for each state in the VA along the surviving path connected to each state. This MLSE makes it possible to estimate a channel impulse response without an influence of a decision delay inherent in the VA, and the performance and complexity of the proposed procedure is controlled by the memory length of the VA. The bit error rate performance of the proposed MLSE is confirmed by experimental results. It is shown that the proposed MLSE has a capability of excellent tracking performance in a severe environment caused by fast time-varying ISI, for example frequency selective multipath fading in digital mobile radio communications. >
Yiming Chen - One of the best experts on this subject based on the ideXlab platform.
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iterative detection and decoding for tdmr with 2 d Intersymbol Interference using the four rectangular grain model
IEEE Transactions on Magnetics, 2015Co-Authors: Michael Carosino, B Belzer, Krishnamoorthy Sivakumar, Yiming Chen, Morteza Mehrnoush, Roger Wood, Jacob Murray, Paul WettinAbstract:This paper considers detection and error control coding for the 2-D magnetic recording (TDMR) channel modeled with the 2-D four-rectangular-grain model (FRGM). This simple model captures the effects of different 2-D grain sizes and shapes, as well as the TDMR grain overwrite effect. We construct a row-by-row Bahl-Cocke-Jelinek-Raviv-based detector that processes two rows at a time. Simulation results using the same coded bit density and channel code as a previous paper on FRGM detection show gains in user bits per grain of up to 13.4% when the detector and the decoder iteratively exchange soft information, resulting in densities higher than 0.5 user bits per grain under all scenarios simulated. When the proposed detector/decoder operates on coded bits read from a random Voronoi grain model, the achieved density drops to 0.25 user bits per grain due to model mismatch between the detector and the data. Finally, this paper considers an iterative detection and decoding scheme combining TDMR detection, 2-D-Intersymbol Interference (ISI) detection, and soft-in/soft-out channel decoding in a structure with two iteration loops. Simulation results for the concatenated FRGM and $2 \times 2$ averaging mask ISI channel with 10 dB signal-to-noise ratio show that densities of 0.496 user bits per grain and above can be achieved over the entire range of FRGM grain probabilities.
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joint self iterating equalization and detection for two dimensional Intersymbol Interference channels
IEEE Transactions on Communications, 2013Co-Authors: Yiming Chen, Shayan Garani SrinivasaAbstract:We develop several novel signal detection algorithms for two-dimensional Intersymbol-Interference channels. The contribution of the paper is two-fold: (1) We extend the one-dimensional maximum a-posteriori (MAP) detection algorithm to operate over multiple rows and columns in an iterative manner. We study the performance vs. complexity trade-offs for various algorithmic options ranging from single row/column non-iterative detection to a multi-row/column iterative scheme and analyze the performance of the algorithm. (2) We develop a self-iterating 2-D linear minimum mean-squared based equalizer by extending the 1-D linear equalizer framework, and present an analysis of the algorithm. The iterative multi-row/column detector and the self-iterating equalizer are further connected together within a turbo framework. We analyze the combined 2-D iterative equalization and detection engine through analysis and simulations. The performance of the overall equalizer and detector is near MAP estimate with tractable complexity, and beats the Marrow Wolf detector by about at least 0.8 dB over certain 2-D ISI channels. The coded performance indicates about 8 dB of significant SNR gain over the uncoded 2-D equalizer-detector system.
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iterative soft decision feedback zig zag equalizer for 2d Intersymbol Interference channels
IEEE Journal on Selected Areas in Communications, 2010Co-Authors: Yiming Chen, Taikun Cheng, B Belzer, P Njeim, Krishnamoorthy SivakumarAbstract:We present a novel iterative soft decision feedback zig-zag algorithm for detection of binary images corrupted by two dimensional Intersymbol Interference and additive white Gaussian noise. The algorithm exchanges soft information between maximum-a-posteriori detectors employing different zigzag scan directions. Each detector exploits soft-decision feedback from the other zig-zag detectors. Simulation results for the 2 × 2 averaging mask channel show that, at low signal-to-noise ratios, the new algorithm gains about 1 dB over an iterative row column soft decision feedback algorithm and over a separable mask algorithm, two of the best previously published schemes. When the zig-zag algorithm is concatenated with the row-column algorithm, the concatenated system performs as well as or better than four of the best previously published algorithms, at both low and high signal-to-noise ratios, for a variety of 2 × 2 and 3 × 3 convolution masks; in several cases, the system performs within less than 0.1 dB of the maximum-likelihood performance bound.
