2019
DOI: 10.1016/j.dsp.2019.102577
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Blind parameter estimation of turbo convolutional codes: Noisy and non-synchronized scenario

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Cited by 11 publications
(5 citation statements)
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“…In recent years, research has been published on methods to reconstruct channel coding parameters under non-cooperative conditions, including convolutional codes [1,2], cyclic codes [3][4][5][6][7][8][9], turbo codes [10,11], and LDPC codes [12,13]. These blind reconstruction methods all presuppose that the received message sequence is not scrambled or that the scrambler is known.…”
Section: Introductionmentioning
confidence: 99%
“…In recent years, research has been published on methods to reconstruct channel coding parameters under non-cooperative conditions, including convolutional codes [1,2], cyclic codes [3][4][5][6][7][8][9], turbo codes [10,11], and LDPC codes [12,13]. These blind reconstruction methods all presuppose that the received message sequence is not scrambled or that the scrambler is known.…”
Section: Introductionmentioning
confidence: 99%
“…A survey of modulation classification methods based on both traditional approaches is covered in [16]. Classification of channel codes in a non-cooperative context is discussed in [17], [18], and particularly, recognition of space-time block codes and turbo codes is presented in [19], [20] and [21], [22], respectively. Blind estimation of interleaver parameters has been addressed in [23]- [26], moreover, methods to estimate convolutional and block interleaver parameters are discussed in [27]- [30] and [31], [32], respectively.…”
Section: Introductionmentioning
confidence: 99%
“…This is because the communication protocol has many optional parameters and the intercepted signals may contain errors. In recent years, research has been published on methods for reconstructing channel coding parameters under non-cooperative conditions, including convolutional codes [1,2], cyclic codes [3,4], turbo codes [5,6], and LDPC codes [7,8]. Here, we study another important component of channel coding, namely linear scramblers.…”
Section: Introductionmentioning
confidence: 99%