Blind frame synchronization for error correcting codes having a sparse parity check matrix

Imad, Rodrigue; Sicot, Guillaume; Houcke, Sébastien

doi:10.1109/tcomm.2009.06.070445

Cited by 45 publications

(48 citation statements)

References 10 publications

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“…A modified version of this algorithm has subsequently been used to detect an additional lonely bit piggybacked on a linearly encoded data stream [14]. Also, a similar algorithm has been used in [15], [16] in the context of blind frame synchronization. Since this scheme provides a basis for our further discussions, we will present it again in this section.…”

Section: A Contributionmentioning

confidence: 99%

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Fast Blind Recognition of Channel Codes

Moosavi

Larsson

2014

IEEE Trans. Commun.

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Abstract-We present a fast algorithm that, for a given input sequence and a linear channel code, computes the syndrome posterior probability (SPP) of the code, i.e., the probability that all parity check relations of the code are satisfied. According to this algorithm, the SPP can be computed blindly, i.e., given the soft information on a received sequence we can compute the SPP for the code without first decoding the bits. We show that the proposed scheme is efficient by investigating its computational complexity.We then consider two scenarios where our proposed SPP algorithm can be used. The first scenario is when we are interested in finding out whether a certain code was used to encode a data stream. We formulate a statistical hypothesis test and we investigate its performance. We also compare the performance of our scheme with that of an existing scheme. The second scenario deals with how we can use the algorithm for reducing the computational complexity of a blind decoding process. We propose a heuristic sequential statistical hypotheses test to use the fact that in real applications, the data arrives sequentially, and we investigate its performance using system simulations.

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Section: A Contributionmentioning

confidence: 99%

“…This approximation has been used in many works, mainly for reducing the computational complexity, since it does not significantly affect the performance [15], [16]. The box-plus operation can also be approximated using the well-known approximation [17] …”

Section: Approximation Of the Sppmentioning

confidence: 99%

Fast Blind Recognition of Channel Codes

Moosavi

Larsson

2014

IEEE Trans. Commun.

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“…In [20,21], the authors introduce a MAP approach to achieve blind frame synchronization of error-correcting codes with a sparse parity-check matrix. It is also developed on Reed Solomon (RS) codes [22] and BCH product codes [23] and yields better performances than previous hard decision ones.…”

Section: Related Workmentioning

confidence: 99%

“…We improve and extend this work in order to handle soft-decision situations. To utilize the soft-decision outputs, we employ the idea of MAP-based processing method proposed in [20][21][22][23].…”

Section: Related Workmentioning

confidence: 99%

Blind recognition of binary cyclic codes

Zhou

Huang

et al. 2013

J Wireless Com Network

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A solution to blind recognition of binary cyclic codes is proposed in this paper. This problem could be addressed on the context of non-cooperative communications or adaptive coding and modulations. We consider it as a reverse engineering problem of error-correcting coding. The proposed algorithm recovers the encoder parameters of a cyclic, coded communication system with the only knowledge of the noisy information streams. By taking advantages of soft-decision outputs of the channel and by employing statistical signal-processing methods, it achieves higher recognition performances than existing algorithms which are based on algebraic approaches in hard-decision situations. By comprehensive simulations, we show that the probability of false estimation of coding parameters of our proposed algorithm is much lower than the existing algorithms, and falls rapidly when signal-tonoise ratio increases.

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“…Many soft-decision-based decoding algorithms have been applied to the error-correcting codes [25][26][27][28][29][30] and yield better decoding performances than hard decision algorithms. Some blind frame synchronization techniques for error correcting codes also utilize the soft output of the channel to improve the synchronization performances [31][32][33][34]. Inspired by the soft decision decoding algorithms, we develop the RIDERS algorithm introduced by [22][23][24] in the soft decision situations in this paper.…”

Section: Introductionmentioning

confidence: 99%

Information-Dispersion-Entropy-Based Blind Recognition of Binary BCH Codes in Soft Decision Situations

Zhou

Huang

Liu

et al. 2013

Entropy

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A method of blind recognition of the coding parameters for binary Bose-Chaudhuri-Hocquenghem (BCH) codes is proposed in this paper. We consider an intelligent communication receiver which can blindly recognize the coding parameters of the received data stream. The only knowledge is that the stream is encoded using binary BCH codes, while the coding parameters are unknown. The problem can be addressed on the context of the non-cooperative communications or adaptive coding and modulations (ACM) for cognitive radio networks. The recognition processing includes two major procedures: code length estimation and generator polynomial reconstruction. A hard decision method has been proposed in a previous literature. In this paper we propose the recognition approach in soft decision situations with Binary-Phase-Shift-Key modulations and Additive-White-Gaussian-Noise (AWGN) channels. The code length is estimated by maximizing the root information dispersion entropy function. And then we search for the code roots to reconstruct the primitive and generator polynomials. By utilizing the soft output of the channel, the recognition performance is improved and the simulations show the efficiency of the proposed algorithm.

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Blind frame synchronization for error correcting codes having a sparse parity check matrix

Cited by 45 publications

References 10 publications

Fast Blind Recognition of Channel Codes

Fast Blind Recognition of Channel Codes

Blind recognition of binary cyclic codes

Information-Dispersion-Entropy-Based Blind Recognition of Binary BCH Codes in Soft Decision Situations

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