Iterative demapping for QPSK modulation

Brink, Stephan ten; Speidel, Joachim; Han, Ruiyan

doi:10.1049/el:19981059

Cited by 123 publications

(68 citation statements)

References 2 publications

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“…where I(X; Y ) is the unidimensional version of the MI in (12). As expected, R mem ≥ I(X; Y ) [51, Sec.…”

Section: B Memoryless Receiverssupporting

confidence: 61%

“…Excellent agreement between the simulated curves and the experimental points is demonstrated for all SD-FEC code rates, launch powers, and distances, even though the simulations and experiments concern entirely different channels. 12 Each result shown with a marker in Fig. 10 corresponds to a given launch power (per channel), code rate R c , and number of spans N s .…”

Section: Optical Channel-experimentsmentioning

confidence: 99%

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Replacing the Soft-Decision FEC Limit Paradigm in the Design of Optical Communication Systems

Alvarado

Agrell

Lavery

et al. 2016

J. Lightwave Technol.

106

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Abstract-The FEC limit paradigm is the prevalent practice for designing optical communication systems to attain a certain bit-error rate (BER) without forward error correction (FEC). This practice assumes that there is an FEC code that will reduce the BER after decoding to the desired level. In this paper, we challenge this practice and show that the concept of a channel-independent FEC limit is invalid for soft-decision bitwise decoding. It is shown that for low code rates and high order modulation formats, the use of the soft FEC limit paradigm can underestimate the spectral efficiencies by up to 20%. A better predictor for the BER after decoding is the generalized mutual information, which is shown to give consistent post-FEC BER predictions across different channel conditions and modulation formats. Extensive optical full-field simulations and experiments are carried out in both the linear and nonlinear transmission regimes to confirm the theoretical analysis.

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“…where I(X; Y ) is the unidimensional version of the MI in (12). As expected, R mem ≥ I(X; Y ) [51, Sec.…”

Section: B Memoryless Receiverssupporting

confidence: 61%

Section: Optical Channel-experimentsmentioning

confidence: 99%

Replacing the Soft-Decision FEC Limit Paradigm in the Design of Optical Communication Systems

Alvarado

Agrell

Lavery

et al. 2016

J. Lightwave Technol.

106

View full text Add to dashboard Cite

show abstract

“…We also address the influence of different symbol labelings. Whereas coherent iterative receivers can only benefit from anti-Gray mapping [10], we found that our noncoherent iterative receiver benefits from anti-Gray mapping in the error-floor region, while it yields better performance in the waterfall region applying Gray mapping. Before outlining the paper let us stipulate some notation.…”

mentioning

confidence: 72%

“…[10]. The main conclusion one can draw is that as soon as feedback information is available Gray-mapping may not be the preferred choice.…”

Section: A the Role Of Symbol Labelingmentioning

confidence: 99%

A Multiple-Symbol Turbo Detector for Coded M-DPSK Over Time-Varying Rayleigh Flat Fading Channels

Klenner

Kammeyer

2006

IEEE Vehicular Technology Conference

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Abstract-In the past few years, a number of publications concentrated on developing soft-in-soft-out algorithms for coded noncoherent detection, thereby enabling iterative processing and avoiding the need of channel estimation. This paper focuses on iterative noncoherent detection of convolutionally coded M -DPSK signals for time-variant Rayleigh flat fading channels without the receiver having channel state information (CSI). Specifically we show that a noncoherent soft demodulator for minimum-shift keying, which was previously reported in the literature, lends itself quite naturally for soft demodulation of DPSK. We present an extension of this receiver in terms of persurvivor processing and examine the influence of different symbol labelings.I. INTRODUCTION DPSK is well-known as a robust means to transmit data because it renders the need of carrier phase tracking unnecessary and eludes the problem of phase ambiguities, thus allowing for a simple receiver design. To overcome the entailed penalty in shape of a loss in SNR (approx. 2-3dB for QDPSK against QPSK), multiple symbol differential detection (MSDD) schemes were introduced. Numerous publications center around the idea to extend the observation interval of two symbols for conventional detection of DPSK to larger intervals. Thus e.g. for the AWGN channel, it is possible to attain the performance of differentially encoded and coherently detected M -PSK. In [1] it is shown, how MSDD is implemented for AWGN as well as Rayleigh fading channels. There, a number of maximum-likelihood metrics are derived from the multivariate Gaussian distribution. Several publications adopted the idea of MSDD to implement iterative strategies, in order to combine the benefits of coding and multiple symbol observations. In[2] a noncoherent BCJRtype algorithm is derived which introduces a MSDD-like transition metric by truncating the observations for a transition to a few previous symbols. Hence, the generated APPs are only approximate, which is made up for by feeding back extrinsic information from the channel decoder. Only AWGN is considered in [2]. A similar approach is taken in [3], where the focus lies on turbo-decoding. Unlike [2], the alphabet is not restricted to PSK, but also only AWGN is considered. [4] advances the scheme of [3] by incorporating block fading. Although minimum-shift keying is considered, the described transition metric is generally applicable.

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“…The most significant gain is obtained at the second iteration. Note that no gain can be obtained by performing the iterative process for the systems with gray mapping, in which the bits are mapped to I and Q channels independently [21]. The iterative MMSE decoding with anti-gray mapping outperforms the one with gray mapping at the 4th iteration when E b /N0 > 26.1 dB and E b /N0 > 22.2 dB for 2-path and 7-path channels, respectively.…”

Section: Numerical Resultsmentioning

confidence: 99%

Joint complex diversity coding and channel coding over space, time and frequency

Wu¹,

Xiao²,

Sellathurai³

et al. 2011

IET Signal Process.

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This paper provides a general diversity analysis for joint CDC and channel coding based space-time-frequency codes (STFCs) is provided.The mapping designs from channel coding to CDC are crucial for efficient exploitation of the diversity potential. This paper provides and proves a sufficient condition of full diversity construction with joint 3-D CDC and channel coding, bit-interleaved coded complex diversity coding (BICCDC) and symbol-interleaved coded complex diversity coding (SICCDC). Both non-iterative and iterative detection of joint channel code and CDC transmission are investigated. The proposed minimum mean square error based iterative soft decoding achieves the performance of the soft sphere decoding with reduced complexity.

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Iterative demapping for QPSK modulation

Cited by 123 publications

References 2 publications

Replacing the Soft-Decision FEC Limit Paradigm in the Design of Optical Communication Systems

Replacing the Soft-Decision FEC Limit Paradigm in the Design of Optical Communication Systems

A Multiple-Symbol Turbo Detector for Coded M-DPSK Over Time-Varying Rayleigh Flat Fading Channels

Joint complex diversity coding and channel coding over space, time and frequency

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