A decoding for low density parity check codes over impulsive noise channels

Nakagawa, H.; Daisuke, Umehara; Denno, Satoshi; Morihiro, Yoshifumi

doi:10.1109/isplc.2005.1430471

Cited by 72 publications

(50 citation statements)

References 6 publications

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“…Among the various statistical models for these phenomena, generally referred to as "impulse noise", the most widely used in the literature is the class-A model [1], which is adopted also in this letter. The performance of such systems is generally studied under the assumption of ideal knowledge of the statistical properties of the impulse noise [2]- [4]. These statistics, which are actually unknown to the receiver, can be effectively estimated [5], but the estimation algorithms unfortunately affect the complexity of the system and cannot properly cope with time-varying channels [5]- [8].…”

Section: Introductionmentioning

confidence: 99%

A robust metric for soft-output detection in the presence of class-A noise

Fertonani

Colavolpe

2009

IEEE Trans. Commun.

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Abstract-Digital communications over channels impaired by impulse noise are considered. We first address the problem from an information-theoretical viewpoint, discussing the performance limits imposed by the channel model. Then, we describe and compare a couple of practical communication schemes employing powerful channel codes and iterative decoding, with focus on a very simple and robust detection scheme that does not require the estimation of the statistics of the impulse noise.Index Terms-Impulse noise, soft-output detection, achievable information rate.

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Section: Introductionmentioning

confidence: 99%

A robust metric for soft-output detection in the presence of class-A noise

Fertonani

Colavolpe

2009

IEEE Trans. Commun.

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“…for re-generation as expressed by the third term in (12). Therefore, by calculating difference signal, |r…”

Section: Proposed Channel Estimation Schemementioning

confidence: 99%

[Paper] Channel Estimation Scheme under Class A Impulsive Noise Environment

Yasui

Nakamura

Ohno

et al. 2016

MTA

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OFDM (Orthogonal Frequency Division Multiplexing) is the modulation scheme that is widely used in broad band power line communication (PLC). In OFDM transmission, impulsive noise is one of the major factors that limits the performance of PLC systems. In order to sufficiently reduce the influence of impulsive noise, precise estimation of channel transfer function is necessary. In this paper, the estimation scheme of channel transfer function under existence of additive impulsive noise is proposed. In the proposed scheme, successive two pilot OFDM symbols are used for reduction of the influence of impulsive noise. As the results, it is possible to perform precise estimation of channel transfer functions.

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“…For instance, convolutional coding is applied in [11], turbo coding in [12], and low density parity-check coding in [13]. For more details, readers can refer to Chapter 5 in [14] and the references therein.…”

Section: A Related Workmentioning

confidence: 99%

Robust Decoding for Convolutionally Coded Systems Impaired by Memoryless Impulsive Noise

Tseng

Han

Mow

et al. 2013

IEEE Trans. Commun.

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It has been known that communication systems are susceptible to strong impulsive noises. To combat this, convolutional coding has long served as a cost-effective tool in the context of moderately frequent occurrence of memoryless impulses with given statistics. Nevertheless, the impulsive noise statistics is hard to be accurately modeled and is generally not time-invariant, making the respective system design challenging. In this article, in the absence of full knowledge of the probability density function (PDF) of impulsive noises, we devise an efficient decoding scheme for single-carrier narrowband communication systems by incorporating a design parameter into the recently introduced joint erasure marking and This is the Pre-Published Version 2 Viterbi decoding algorithm, dubbed the metric erasure Viterbi algorithm (MEVA). The proposed scheme is equivalent to incorporating a well-designed clipping operation into the Viterbi algorithm, of which the clipping threshold has to be appropriately set. In contrast with existing publications that often resort to extensive simulations, we characterize the bit error probability performance associated with the clipping threshold by deriving its Chernoff bound. Simulation results reveal that with a judicious selection of the clipping threshold, the MEVA can be on par with its optimal maximum-likelihood decoding counterpart under fairly general circumstances.

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A decoding for low density parity check codes over impulsive noise channels

Cited by 72 publications

References 6 publications

A robust metric for soft-output detection in the presence of class-A noise

A robust metric for soft-output detection in the presence of class-A noise

[Paper] Channel Estimation Scheme under Class A Impulsive Noise Environment

Robust Decoding for Convolutionally Coded Systems Impaired by Memoryless Impulsive Noise

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