An Improved Blind Recognition Method of the Convolutional Interleaver Parameters in a Noisy Channel

Abstract

In a digital communication system, forward error correction (FEC) codes and interleavers are implemented to code the data so as to improve the error performance, which is hindered by random and burst errors. In the context of noncooperative communication, interleaver parameter recognition, which is the prerequisite for frame synchronization, channel coding recognition subsequently, is of vital significance. Methods of blindly recognizing convolutional interleaver parameters have been proposed in published literature, but the accuracy of recognition decreases significantly when bit error rate (BER) is high. To improve the performance of the algorithm, the effect of error bits on Gauss-Jordan elimination through pivoting (GJTEP) algorithm is analyzed in this paper. The following conclusion is drawn: error bits on the principal diagonal of data storage matrix will exert a great impact on the recognition accuracy. Based on the conclusion, an improved blind recognition method with denoising, the core principle of which is reducing error bits on the principal diagonal of data storage matrix, is proposed in this paper. The simulation experiment results demonstrate that the performance on error resilience is markedly improved.

An Improved Blind Recognition Method for Synchronization Position and Coding Parameters of k/n Rate Convolutional Codes in a Noisy Environment

“…It is concluded in [13] that randomly swapping the rows of the matrix will not change the linear relationship between the columns of the matrix. This method in [13] has a great potential to reduce the error of the main diagonal of the matrix and thus improve the robustness of the GJETP algorithm. This method is applied in this paper to improve the accuracy of identifying synchronization positions and coding parameters.…”

“…After algorithm 2 successfully estimates n − k quasi-check vectors h 1 to h n−k , the basic check matrix h ∞ of of the convolutional code can be obtained. Assuming the form of h 1 to h n−k are (12), then the basic check matrix h ∞ is (13).…”

“…In [12], the relationship between rank and convolutional code constraint length was revealed. The GJETP algorithm for blind recognition of convolutional interleaving parameters was improved in [13]. It can be seen that, for the blind recognition problem of k/n rate convolutional codes in a noisy environment, the GJETP algorithm can be applied to parameter estimation.…”

Blind Interleaver Parameter Estimation From Scant Data

“…Reference [12] estimated block interleaver parameter using the rank of matrix composed of received data for noiseless channels and [13] extended the estimation method to noisy channels by using Gauss-Jordan elimination through pivoting. Further, [14]- [19] estimated various types of interleavers by using the number of ones or zeros in each row (or column). Reference [14] estimated helical scan interleaver for block channel coded data.…”

“…Further, [17] jointly recognized the type of channel codes and interleaver parameters, and [18] jointly estimated Reed-Solomon code and block interleaver parameters. Recently, [19] proposed a blind estimation method of a convolutional interleaver with denoising algorithm.…”