Journal Article10.1109/LCOMM.2012.102612.121473
Novel Blind Encoder Parameter Estimation for Turbo Codes
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TL;DR: A novel blind parameter-estimation method, which identifies a turbo encoder as a non-systematic convolutional encoder preceded by a feedback encoder, is proposed in this paper.
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Abstract: A novel blind parameter-estimation method, which identifies a turbo encoder, is proposed in this paper. The blind estimator is designed using an iterative expectation-maximization (EM) algorithm. To facilitate this innovative blind estimation scheme, we transform the recursive systematic convolutional (RSC) encoder into a non-systematic convolutional encoder preceded by a feedback encoder. The effect of the separate feedback encoder on the state sequence of the forward convolutional encoder will be studied. Besides, the effectiveness of our proposed new scheme will be evaluated by Monte Carlo simulations.
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Citations
Novel blind identification of LDPC codes using average LLR of syndrome a posteriori probability
Tian Xia,Hsiao-Chun Wu +1 more
- 01 Nov 2012
TL;DR: Monte Carlo simulation results demonstrate that the proposed blind LDPC encoder identification scheme is very promising even for low signal-to-noise ratio conditions.
93
Classification of Error Correcting Codes and Estimation of Interleaver Parameters in a Noisy Transmission Environment
Swaminathan R,A. S. Madhukumar +1 more
TL;DR: The proposed algorithms for the joint recognition of the type of FEC codes and interleaver parameters without knowing any information about the channel encoder classify the incoming data symbols among block coded, convolutional coded, and uncoded symbols and suggest analytical and histogram approaches for setting the threshold value to perform code classification and parameter estimation.
83
Novel Blind Encoder Parameter Estimation for Turbo Codes
TL;DR: A novel blind parameter-estimation method, which identifies a turbo encoder as a non-systematic convolutional encoder preceded by a feedback encoder, is proposed in this paper.
57
Classification Based on Euclidean Distance Distribution for Blind Identification of Error Correcting Codes in Noncooperative Contexts
TL;DR: This paper proposes an algorithm which is able to identify the length of a code through a classification process from the bits likelihood values, and highlights a difference of behavior between an independent identically distributed sequence and an encoded one.
A Least Square Method for Parameter Estimation of RSC Sub-Codes of Turbo Codes
Peidong Yu,Jing Li,Hua Peng +2 more
TL;DR: A new algorithm is developed for parameter estimation of the recursive systematic convolutional sub-codes of turbo codes based on a least square cost function of the encoder coefficients that significantly improves the performance while the complexity is quite reasonable.
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References
A tutorial on hidden Markov models and selected applications in speech recognition
Lawrence R. Rabiner
- 01 Feb 1989
TL;DR: In this paper, the authors provide an overview of the basic theory of hidden Markov models (HMMs) as originated by L.E. Baum and T. Petrie (1966) and give practical details on methods of implementation of the theory along with a description of selected applications of HMMs to distinct problems in speech recognition.
Parameter Estimation of a Convolutional Encoder from Noisy Observations
J. Dingel,Joachim Hagenauer +1 more
- 24 Jun 2007
TL;DR: A new iterative, probabilistic algorithm based on the Expectation Maximization (EM) algorithm is presented, using the concept of log-likelihood ratio (LLR) algebra which will greatly simplify the derivation and interpretation of the final algorithm.
62
A Method for Blind Recognition of Convolution Code Based on Euclidean Algorithm
Fenghua Wang,Zhitao Huang,Yiyu Zhou +2 more
- 08 Oct 2007
TL;DR: It is proved that the MKE can be used for blind recognition of convolution code with any code rate, and a fast algorithm based on Euclidean algorithm is achieved which can solve 2-order KE.
58
Novel Blind Encoder Parameter Estimation for Turbo Codes
TL;DR: A novel blind parameter-estimation method, which identifies a turbo encoder as a non-systematic convolutional encoder preceded by a feedback encoder, is proposed in this paper.
57
Novel semi-blind ICI equalization algorithm for wireless OFDM systems
TL;DR: A novel semi-blind ICI equalization scheme using the joint multiple matrix diagonalization (JMMD) algorithm to greatly reduce the intercarrier interference in OFDM is proposed and can achieve significantly better performance with symbol error rate reduction in several orders-of-magnitude.
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