Turbo Coding

Heegard, C.; Wicker, S.B.

doi:10.1007/978-1-4757-2999-3

Cited by 250 publications

(133 citation statements)

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“…It follows that the FEC code rate is equal to The initial state is and (termination bits). The code bits are permuted using an S-random interleaver [11] to the bits , which are modulated to the symbols using BPSK modulation. It follows that the transmitted symbols are given by…”

Section: A System Modelmentioning

confidence: 99%

“…For example, the extrinsic transition matrix corresponding to for the memory-2 convolutional code defined in Section II-A is given by the equation at the bottom of the page. Similarly, the extrinsic LLR is defined corresponding to (11) For example, the extrinsic LLRs for the ISI channel model defined in Section II-A can be computed using the BCJR algorithm described in Table II as follows:…”

Section: Joint Equalization and Decodingmentioning

confidence: 99%

“…In a practical implementation, the number of iterations is often constrained by the computational complexity allowed and the delay of the receiver algorithm. For more information about this topic, the reader is referred to [11], [79], and [87]. Fig.…”

Section: Joint Equalization and Decodingmentioning

confidence: 99%

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Turbo Equalization: An Overview

Tüchler

Singer

2011

IEEE Trans. Inform. Theory

175

160

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Abstract-Turbo codes and the iterative algorithm for decoding them sparked a new era in the theory and practice of error control codes. Turbo equalization followed as a natural extension to this development, as an iterative technique for detection and decoding of data that has been both protected with forward error correction and transmitted over a channel with intersymbol interference (ISI). In this paper, we review the turbo equalization approach to coded data transmission over ISI channels, with an emphasis on the basic ideas, some of the practical details, and many of the research directions that have arisen from this offshoot, introduced by Douillard, et al. of the original turbo decoding algorithm. The subsequent relaxation of the maximum a posteriori (MAP) equalization algorithm to include linear and other simpler receivers sparked a decade and a half of research into iterative algorithms, spanning research problems ranging from trellis coded modulation to underwater acoustic communications.Index Terms-Equalization, iterative decoding, minimum mean square error, turbo equalization.

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Section: A System Modelmentioning

confidence: 99%

Section: Joint Equalization and Decodingmentioning

confidence: 99%

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Turbo Equalization: An Overview

Tüchler

Singer

2011

IEEE Trans. Inform. Theory

175

160

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“…The symmetric expression of spreading factor is the s-parameter, which is the largest number s such that symbols within distance s at the input are s samples apart in the output stream [22]. The interleaver delay is defined:…”

Section: Delay-limited Interleaver Designmentioning

confidence: 99%

Error-resilient packet header compression

Suryavanshi

Nosratinia

2008

IEEE Trans. Commun.

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Abstract-Full packet headers consume valuable bitrate, which is especially costly in satellite links and some terrestrial wireless links. This has motivated the compression of packet headers by exploiting their correlation via using finite-state machines. The drawback is that compression in the presence of channel errors (packet loss) may result in error propagation. We offer several designs by adapting error control codes for the requirements of packet header compression in uni-directional and bi-directional links, and explore the tradeoffs in complexity, delay, and system performance. For the bi-directional link, we propose a new design called predictive hybrid ARQ and evaluate its performance. Experiments show significant gains in link-layer throughput as well as improved application layer performance demonstrated via video transfer experiments.

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“…1. The message bits {x k } are encoded by a serial concatenation of an error-correction encoder, an srandom interleaver [13] (i.e., the π block), and precoder. The readback signal, s(t), can then be written as…”

Section: Channel Descriptionmentioning

confidence: 99%

Per-survivor iterative timing recovery for coded partial response channels

Kovintavewat

Barry

Erden³

et al.

IEEE Global Telecommunications Conference, 2004. GLOBECOM '04.

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Abstract-We propose a new iterative timing recovery scheme based on per-survivor processing that jointly performs timing recovery and turbo equalization on partial response channels with error-correction codes. The scheme embeds the timing recovery process inside the Bahl, Cocke, Jelinek, and Raviv (BCJR) equalizer using per-survivor processing. This per-survivor BCJR equalizer then iteratively exchanges soft information with an error-correction decoder. Results indicate that the proposed scheme yields a better performance than a conventional receiver that performs timing recovery and turbo equalization separately, and also the iterative timing recovery scheme proposed in [1], especially when the channel encounters severe timing jitter noise. We also present evidence that suggests that the proposed scheme can correct a cycle slip much more efficiently than the others.

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Turbo Coding

Cited by 250 publications

References 0 publications

Turbo Equalization: An Overview

Turbo Equalization: An Overview

Error-resilient packet header compression

Per-survivor iterative timing recovery for coded partial response channels

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