Iterative decoding of coded and interleaved noncoherentmultiple symbol detected DPSK

Peleg, Michael; Shamai, Shlomo

doi:10.1049/el:19970697

Cited by 90 publications

(46 citation statements)

References 7 publications

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“…More precisely, we consider two types of serial concatenation. In the first scheme, we consider a concatenated code given by a convolutional code followed by a nonuniform interleaver and a differential encoder [21]- [25]. The idea is that the interleaved convolutionally encoded symbols feed, as a new information sequence, the differential encoder.…”

Section: B Serially Concatenated Codesmentioning

confidence: 99%

“…The first application of noncoherent decoding to turbo codes was proposed in [20], where the output of a conventional differential detector is used to feed a standard turbo decoder. In [21], a new receiver for convolutionally encoded, interleaved and differentially encoded -ary phase-shift keying ( -PSK) was proposed, based on an improved version of MSDD in order to allow iterative decoding. An extension to turbo codes was proposed in [22].…”

mentioning

confidence: 99%

“…The first algorithm is derived from an approximation of a minimum symbolerror probability decoder, with a structure similar to that of the well-known algorithm by Bahl et al (BCJR) [30]. While the soft-output decoding strategy proposed in [21] and [22] may be viewed as the equivalent of MSDD based on a minimum symbol-error probability criterion, this algorithm is the minimum symbol-error probability counterpart of NSD [13], [14]. The second algorithm is based on NSD [13], [14], in which reliability information about each symbol is obtained by means of a soft-output VA (SOVA) [31]- [33].…”

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confidence: 99%

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Noncoherent iterative (turbo) decoding

Colavolpe

Ferrari²,

Raheli³

2000

IEEE Trans. Commun.

100

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Abstract-Recently, noncoherent sequence detection schemes for coded linear and continuous phase modulations have been proposed, which deliver hard decisions by means of a Viterbi algorithm. The current trend in digital transmission systems toward iterative decoding algorithms motivates an extension of these schemes. In this paper, we propose two noncoherent soft-output decoding algorithms. The first solution has a structure similar to that of the well-known algorithm by Bahl et al.(BCJR), whereas the second is based on noncoherent sequence detection and a reduced-state soft-output Viterbi algorithm.Applications to the combined detection and decoding of differential or convolutional codes are considered. Further applications to noncoherent iterative decoding of turbo codes and serially concatenated interleaved codes are also considered. The proposed noncoherent detection schemes exhibit moderate performance loss with respect to corresponding coherent schemes and are very robust to phase and frequency instabilities.Index Terms-Iterative decoding, noncoherent decoding/detection, soft-input/soft-output algorithms, turbo (de)coding.

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Section: B Serially Concatenated Codesmentioning

confidence: 99%

mentioning

confidence: 99%

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confidence: 99%

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Noncoherent iterative (turbo) decoding

Colavolpe

Ferrari²,

Raheli³

2000

IEEE Trans. Commun.

100

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“…Here, AIDA without SC is that the early stopping approach is not used in AIDA. In case of AIDA without SC, the OWS of MSDD SISO corresponding to the outer iteration number from 1 to 6 is [2,4,6,8,8,8], and the outer iterations are stopped when the maximum outer iteration number is reached or a legitimate codeword is found. The simulation result of the considered systems with fixed S = 8 without AIDA is also presented for comparison.…”

Section: Selection Of the Dmi Criterion Thresholdsmentioning

confidence: 99%

“…Multiple-symbol differential detection (MSDD) [5] has been proven to be an effective approach to compensate for this performance loss. For serially concatenated coded systems consisting of a channel encoder and a differential encoder, an iterative decoding scheme based on MSDD was proposed in [6]. In this scheme, the soft-input soft-output demodulator (SISOD) with MSDD (called MSDD SISOD in the following) is used as the inner decoder, and the iterative decoding is performed between the MSDD SISOD and the outer decoder.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Iterative Decoding of Finite-Length Differentially Encoded LDPC Coded Systems with Multiple-Symbol Differential Detection

Handa

Sasamori

et al. 2013

IEICE Trans. Commun.

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SUMMARYIn this paper, through extrinsic information transfer (EXIT) band chart analysis, an adaptive iterative decoding approach (AIDA) is proposed to reduce the iterative decoding complexity and delay for finite-length differentially encoded Low-density parity-check (DE-LDPC) coded systems with multiple-symbol differential detection (MSDD). The proposed AIDA can adaptively adjust the observation window size (OWS) of the MSDD soft-input soft-output demodulator (SISOD) and the outer iteration number of the iterative decoder (consisting of the MSDD SISOD and the LDPC decoder) instead of setting fixed values for the two parameters of the considered systems. The performance of AIDA depends on its stopping criterion (SC) which is used to terminate the iterative decoding before reaching the maximum outer iteration number. Many SCs have been proposed; however, these approaches focus on turbo coded systems, and it has been proven that they do not well suit for LDPC coded systems. To solve this problem, a new SC called differential mutual information (DMI) criterion, which can track the convergence status of the iterative decoding, is proposed; it is based on tracking the difference of the output mutual information of the LDPC decoder between two consecutive outer iterations of the considered systems. AIDA using the DMI criterion can adaptively adjust the out iteration number and OWS according to the convergence situation of the iterative decoding. Simulation results show that compared with using the existing SCs, AIDA using the DMI criterion can further reduce the decoding complexity and delay, and its performance is not affected by a change in the LDPC code and transmission channel parameters. key words: adaptive iterative decoding, low-density parity-check (LDPC) codes, differential encoded LDPC coded systems, multiple-symbol differential detection, extrinsic information transfer (EXIT) band chart

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On Coded and Interleaved Noncoherent Multiple Symbol Detected MPSK

Peleg

Shitz

1999

Trans Emerging Tel Tech

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Abstract. The performance of multiple symbol noncoherent detection of MPSK combined with coding and interleaving is examined in terms of the cut-off rate bound. It is shown that, within this approach, inner modulation coding improves on standard DPSK when both are combined with an external error correcting code, such as the industry standard, li = 7 R = l/? convolutional code. Some modulation codes over BPSK and QPSK are examined and a reduced complexity decoder is presented. The results and conclusions are verified by some simulations.

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Iterative decoding of coded and interleaved noncoherentmultiple symbol detected DPSK

Cited by 90 publications

References 7 publications

Noncoherent iterative (turbo) decoding

Noncoherent iterative (turbo) decoding

Adaptive Iterative Decoding of Finite-Length Differentially Encoded LDPC Coded Systems with Multiple-Symbol Differential Detection

On Coded and Interleaved Noncoherent Multiple Symbol Detected MPSK

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