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

Fertonani, D.; Colavolpe, Giulio

doi:10.1109/tcomm.2009.0901.070041

Cited by 24 publications

(27 citation statements)

References 15 publications

(38 reference statements)

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“…However, the computational cost for JEVA is high and becomes unmanageable for long codelengths. Fertonani and Colavolpe [10] made a similar conclusion for low-density parity-check codes with iterative decoding based on a robust (against impusive noise) soft decoding metric, which can be obtained by simply clipping the Gaussian noise metric. However, a systematic way to choose the clipping threshold is unavailabe in [10].…”

Section: Introductionmentioning

confidence: 61%

“…Fertonani and Colavolpe [10] made a similar conclusion for low-density parity-check codes with iterative decoding based on a robust (against impusive noise) soft decoding metric, which can be obtained by simply clipping the Gaussian noise metric. However, a systematic way to choose the clipping threshold is unavailabe in [10]. In [11], by interpreting the Viterbi algorithm with a clipped Euclidean metric as a special form of JEVA that can mark a varying number of erasures, the so-called metric erasure Viterbi algorithm (MEVA) was proposed and a systematic way to choose the clipping threshold was derived by assuming the impulsive noise probability is close to 1.…”

Section: Introductionmentioning

confidence: 61%

“…The aforementioned metric clipping based decoders are easy to implement as practical decoders always adopt some form of metric clipping due to the finite bit precision in digital circuit implementation. However, the assumption made in [11] (and implicitly in [10]) about the noise statistics for deriving the clipping threshold are violated at high SNR which leads to an error floor in bit error probability curve, as shown in the Experimentsl Results Section.…”

Section: Introductionmentioning

confidence: 99%

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Optimized metric clipping decoder design for impulsive noise channels at high signal-to-noise ratios

Chen

Mow

2015

2015 36th IEEE Sarnoff Symposium

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Abstract-In many practical communication systems, the channel is corrupted by non-Gaussian impulsive noise (IN). It introduces decoding metric mismatch for the traditional Euclidean metric decoders and limits system performance. The situation is worsen by the practical difficulty in accurately estimating the IN statistics. Recently, some metric clipping based decoders with a properly chosen clipping threshold has been shown to be very effective in mitigating the effect of IN, even without a precise knowledge of its statistics. However, we observe that such a clipping threshold is derived based on some assumptions which lead to an error floor in the bit error probability curve at high signal-to-noise ratio (SNR). In this work, a clipping threshold is derived by an optimization approach without exploiting the IN statistics. It is demonstrated by simulation that with our proposed clipping threshold, the optimzed metric clipping decoder is able to perform close to the maximum likelihood decoding performance at high SNR under the Bernoulli Gaussian noise model with various parameters.

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Section: Introductionmentioning

confidence: 61%

Section: Introductionmentioning

confidence: 61%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimized metric clipping decoder design for impulsive noise channels at high signal-to-noise ratios

Chen

Mow

2015

2015 36th IEEE Sarnoff Symposium

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“…From Fourier analysis, the behavior of the characteristic function for in the neighborhood of zero governs the tail probability of the random envelope. Thus to accurately model the tails, we approximate for in the neighborhood of zero , such that (15) reduces to (18) When is Rayleigh distributed, e.g., for constant amplitude modulated transmissions in Rayleigh fading environment, then and the expression in (18) is exact. We now simplify for the following bounded and unbounded pathloss functions.…”

Section: Joint Statistics Of Interferencementioning

confidence: 99%

Joint Temporal Statistics of Interference in Decentralized Wireless Networks

Gulati

Evans

Srikanteswara

2012

IEEE Trans. Signal Process.

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Characterizing interference statistics is central to the design and analysis of both physical layer and medium access control layer techniques to mitigate interference in a wireless network. The applicability of interference statistics, however, is limited by the assumptions adopted to derive the statistics in closed-form. Common assumptions for a decentralized wireless network include temporally independent user locations and an unbounded pathloss function. In this correspondence, we derive the joint temporal statistics of interference that capture the temporal correlation in the network along with the realistic assumption of a bounded pathloss function. The closed-form statistics are asymptotically exact for low tail probabilities, and match closely in simulations even when the tail probability is fairly high. The primary contributions are to i) show that joint interference statistics follow a multivariate Gaussian mixture distribution under the assumption of a bounded pathloss function, and ii) characterize the joint tail probability decay behavior for both bounded and unbounded pathloss functions.

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“…5), while the estimate of the parameter P B is not. We point out that the estimate of the parameter R may be much less critical, or even not critical at all, when blind detection schemes are used instead of the FBA -this point is addressed in [17], [18] for channels with γ = 1. In the following, since we are here mainly interested in the impact of the parameter γ, it is assumed that correct information on all other channel parameters is available.…”

Section: B Mismatched Decodingmentioning

confidence: 99%

On reliable communications over channels impaired by bursty impulse noise

Fertonani

Colavolpe

2009

IEEE Trans. Commun.

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Abstract-Digital communications over channels impaired by impulse noise are addressed. We adopt a two-state Markov model that allows to describe the typical bursty nature of the impulse noise, in contrast to the memoryless models generally considered in the literature. For this channel, we evaluate the achievable information rate and propose a couple of practical communication systems based on powerful codes and iterative receivers. Moreover, we discuss the effectiveness of the considered receivers in terms of performance/latency tradeoff as well as in terms of robustness to erroneous channel estimations. The proposed schemes are shown to perform fairly close to the theoretical limits, and significantly better than the conventional schemes employing memoryless detection.Index Terms-Impulse noise, Markov channels, maximum-aposteriori symbol detection, achievable information rate, lowdensity parity-check codes.

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

Cited by 24 publications

References 15 publications

Optimized metric clipping decoder design for impulsive noise channels at high signal-to-noise ratios

Optimized metric clipping decoder design for impulsive noise channels at high signal-to-noise ratios

Joint Temporal Statistics of Interference in Decentralized Wireless Networks

On reliable communications over channels impaired by bursty impulse noise

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