Classification of Error Correcting Codes and Estimation of Interleaver Parameters in a Noisy Transmission Environment

Abstract

Channel encoder, which includes a forward error correcting (FEC) code followed by an interleaver, plays a vital role in improving the error performance of digital storage and communication systems. In most of the applications, the FEC code and interleaver parameters are known at the receiver to decode and de-interleave the information bits, respectively. But the blind/semi-blind estimation of code and interleaver parameters at the receiver will provide additional advantages in applications such as adaptive modulation and coding, cognitive radio, non-cooperative systems, etc. The algorithms for the blind estimation of code parameters at the receiver had previously been proposed and investigated for known FEC codes. In this paper, we propose algorithms for the joint recognition of the type of FEC codes and interleaver parameters without knowing any information about the channel encoder. The proposed algorithm classify the incoming data symbols among block coded, convolutional coded, and uncoded symbols. Further, we suggest analytical and histogram approaches for setting the threshold value to perform code classification and parameter estimation. It is observed from the simulation results that the code classification and interleaver parameter estimation are performed successfully over erroneous channel conditions. The proposed histogram approach is more robust against the analytical approach for noisy transmission environment and system latency is one of the important challenges for the histogram approach to achieve better performance.

Blind recognition of LDPC code parameters over erroneous channel conditions

“…However, Algorithm 1 (Fig. 2) fails in case of low-SNR or more erroneous channel conditions [14]. This is mainly due to the presence of transmission errors or white noise.…”

“…Since LDPC codes belong to the family of linear block codes, the following discussion on deficient and full rank phenomena considering linear block codes can also be extended to LDPC codes. In case of linear block codes, n output block coded data symbols will depend on k input uncoded data symbols [14, 23, 24]. Similarly, output block coded data symbols will depend on input uncoded symbols.…”

“…The algorithm for blind estimation of binary cyclic code parameters was proposed in [13]. In [14], the code classification algorithms were proposed to classify the incoming FEC coded symbols among block coded, convolutionally coded, and uncoded symbols. The blind identification techniques for recognising the codeword length of various non-binary error correcting codes including LDPC codes were reported for noisy environment in [15].…”

Blind Interleaver Parameter Estimation From Scant Data

“…Regarding convolutional channel coded data, [15] estimated block and helical scan interleavers, and [16] estimated convolutional and helical interleavers. 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.…”

Classification Based on Euclidean Distance Distribution for Blind Identification of Error Correcting Codes in Noncooperative Contexts

“…Over the last few years, many methods using hard bits information to identify the channel coding have been proposed for linear codes [2]- [9], LDPC codes [5], [6], convolutional codes [1], [8], [10]- [15], turbo-codes [16], [17], Reed-Solomon [18] and cyclic codes [19]. More recently, new methods based on soft bits information have been proposed [20], [21].…”