On Blind Recognition of Channel Codes Within a Candidate Set

Yu, Peidong; Peng, Hua; Li, Jing

doi:10.1109/lcomm.2016.2525759

Cited by 49 publications

(39 citation statements)

References 8 publications

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“…In fact, the algorithms LLR and LD are equivalent. From [16] we can see that they have almost the same performance. Therefore, we only analyze the property of LD and CC since they have explicit probability density function and lower computational complexity.…”

Section: Analysis Of the Properties Of The Existing Algorithm Anmentioning

confidence: 82%

“…According to parity-checks H θ , 1 ≤ θ ≤ s , we regardĤ = arg max 1≤θ≤s AV ET (H θ ) as the correct encoder. We can also investigate the mean and variance of AV ET under different hypothesis exactly like [16] and [17].…”

Section: A the Proposed Algorithm Tpmentioning

confidence: 99%

“…Meanwhile, it has a high computational complexity for the existence of the inverse hyperbolic tangent function tanh −1 . In [16], the average likelihood difference (LD) was proposed, which has a similar performance to the average LLR but with lower computational complexity. Furthermore, its probability density function is explicit so that we can do specific theoretical analysis.…”

Section: Introductionmentioning

confidence: 99%

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An Improved Method for Identification of LDPC Codes Within a Candidate Set

Liu

Zhang

et al. 2021

IEEE Access

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Section: Analysis Of the Properties Of The Existing Algorithm Anmentioning

confidence: 82%

Section: A the Proposed Algorithm Tpmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An Improved Method for Identification of LDPC Codes Within a Candidate Set

Liu

Zhang

et al. 2021

IEEE Access

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“…The convolution code is one type of FEC code that helps in achieving reliable communication over a noisy channel [2][3][4] . The blind identification of convolution code parameters have been studied based on linear algebraic 5-8 , maximum likelihood [9][10] , euclidean 11 and soft information and correlation attack 12 algorithms.…”

Section: Introductionmentioning

confidence: 99%

Blind Identification of Block Interleaved Convolution Code Parameters

Tamakuwala

2019

Def. Sc. Jl.

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Most of the digital communication system uses forward error correction (FEC) in addition with interleaver to achieve reliable communication over a noisy channel. To get useful information from intercepted data, in non-cooperative context, it is necessary to have algoritihms for blind identification of FEC code and interleaver parameters. In this paper, a matrix rank-based algebraic algorithm for the joint and blind identification of block interleaved convolution code parameters for cases, where interleaving length is not necessarily an integer multiple of codeword length is presented. From simulations, it is observed that the code rate and block interleaver length are identified correctly with probability of detection equal to 1 for bit error rate values of less than or equal to 10-4.

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“…The blind code detection task has been shown to be NP-hard in general [1], [2], so that heuristic algorithms are used in practice. For example, various methods have been proposed for the blind detection of Hamming and BCH codes (e.g., [3], [4] and references therein), convolutional codes (e.g., [5], [6] and references therein), Turbo codes (e.g., [7], [8] and references therein), and LDPC codes (e.g., [9], [10] and references therein). However, so far, the blind detection of polar codes, which were recently included in the 5G standard, has received little attention [11]- [13].…”

Section: Introductionmentioning

confidence: 99%

On the Tradeoff Between Accuracy and Complexity in Blind Detection of Polar Codes

Giard

Balatsoukas‐Stimming

Burg

2018

2018 IEEE 10th International Symposium on Turbo Codes &Amp; Iterative Information Processing (ISTC)

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Polar codes are a recent family of error-correcting codes with a number of desirable characteristics. Their disruptive nature is illustrated by their rapid adoption in the 5 th -generation mobile-communication standard, where they are used to protect control messages. In this work, we describe a two-stage system tasked with identifying the location of control messages that consists of a detection and selection stage followed by a decoding one. The first stage spurs the need for polar-code detection algorithms with variable effort to balance complexity between the two stages. We illustrate this idea of variable effort for multiple detection algorithms aimed at the first stage. We propose three novel blind detection methods based on belief-propagation decoding inspired by early-stopping criteria. Then we show how their reliability improves with the number of decoding iterations to highlight the possible tradeoffs between accuracy and complexity. Additionally, we show similar tradeoffs for a detection method from previous work. In a setup where only one block encoded with the polar code of interest is present among many other blocks, our results notably show that, depending on the complexity budget, a variable number of undesirable blocks can be dismissed while achieving a missed-detection rate in line with the block-error rate of a complex decoding algorithm.

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On Blind Recognition of Channel Codes Within a Candidate Set

Cited by 49 publications

References 8 publications

An Improved Method for Identification of LDPC Codes Within a Candidate Set

An Improved Method for Identification of LDPC Codes Within a Candidate Set

Blind Identification of Block Interleaved Convolution Code Parameters

On the Tradeoff Between Accuracy and Complexity in Blind Detection of Polar Codes

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