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

Yiyao Xu,Yang Zhong,Zhiping Huang

doi:10.1109/access.2019.2930663

Yiyao Xu, Yang Zhong + Show 1 more

Open Access

https://doi.org/10.1109/access.2019.2930663

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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.

Highlights

In a digital communication system, interleavers are usually implemented after forward error correction (FEC) to resist burst errors
The mechanism error bits impacting recognition accuracy is analyzed and we find out that error bits on the principal diagonal of the data storage matrix play an important role in decreasing recognition accuracy
The received data stream is assumed to have bit errors; Input: The data storage matrix Rl; Output: ξtemp; 1: while i ≤ exccnt do Exchange the rows of Rl randomly; Exchange the columns of Rl randomly; Apply Gauss-Jordan elimination through pivoting (GJETP) algorithm on Rl to get the lower triangular matrix; Calculate the normalized rank of the lower triangular matrix and record it in ; end 2: ξtemp = min( ); the goal of reducing error bits on the principal diagonal may not be achieved by ERCR-GJETP algorithm when bit error rate (BER) is high, which means that the value of temporary normalized rank ξtemp is not estimated correctly

Summary

INTRODUCTION

In a digital communication system, interleavers are usually implemented after FEC to resist burst errors. Y. Xu et al.: Improved Blind Recognition Method of the Convolutional Interleaver Parameters in a Noisy Channel. In [14], [15], a blind interleaver parameters estimation method enhanced by identifying relatively error-less partial symbols among intercepted streams is proposed. In [16], Swaminathan et al propose a algorithms for the joint recognition of the type of FEC codes and interleaver parameters without knowing any information about the channel encoder. The denoising algorithm based on reducing error bits on the principal diagonal of data storage matrix is proposed to improve error performance. Based on the conclusion drawn, a novel denoising algorithm is proposed in section V to enhance error performance by reducing error bits on the principal diagonal of data storage matrix.

STRUCTURE OF CONVOLUTIONAL INTERLEAVERS

SIMULATION RESULTS

CONCLUSION