Performance Analysis of the Bioinspired Method for Optimizing Irregular Codes with A Low Density of Parity Checks

This paper reports the principles of building irregular codes with a low density of parity checks. It has been determined that finding irregular finite-length codes with improved characteristics necessitates the optimization of the distributions of powers of the symbol and test vertices of the corresponding Tanner graph. The optimization problem has been stated and the application of a bioinspired approach to solving it has been substantiated. The paper considers the main stages of the bioinspired method to optimize the finite-length irregular codes with a low density of parity checks. It is shown that a given method is based on the combined application of the bioinspired procedure of bats, a special method for building Tanner graphs, and computer simulation.The reported study aimed to evaluate the effectiveness of the proposed method for optimizing irregular codes when using the selected bioinspired procedure and the predefined model of a communication channel.Based on the study results, it has been determined that the optimized relatively short irregular codes with a low density of parity checks possess better characteristics compared to existing codes. It is shown that the derived codes do not demonstrate the effect of an "error floor" and ensure an energy win via encoding of about 0.5 dB compared to regular codes depending on the length of the code. It has been determined that the optimization of irregular codes with a low value of the maximum power in the distribution of powers of the symbol vertices of the Tanner graph leads to a decrease in the order of an error coefficient in the region with a high signal/noise ratio.The application of the optimized irregular codes with a low density of parity checks could improve the efficiency of next-generation wireless telecommunication system

Analysis of Efficiency of the Bioinspired Method for Decoding Algebraic Convolutional Codes

It has been shown that convolutional codes are widely used, along with various decoding methods, to improve the reliability of information transmission in wireless telecommunication systems. The general principles of synthesis and the parameters and algebraic non-systematic convolutional codes with arbitrary coding rate and maximum achievable code distance have been shown.The basic stages of the bioinspired method for decoding algebraic convolutional codes using a random shift mechanism have been presented. It has been shown that the essence of the presented decoding method implies applying the procedure of differential evolution with the heuristically determined parameters. In addition, this method uses information about the reliability of the adopted symbols to find the most reliable basis for the generalized generator matrix. The mechanism of random shift for the modification of the accepted sequence is additionally applied for the bioinspired search based on various most reliable bases of a generalized generator matrix.The research results established that the bioinspired method for decoding algebraic convolutional codes ensures greater efficiency compared with the algebraic decoding method in the communication channel with additive white Gaussian noise. Depending on the parameters of the algebraic convolutional code and the necessary error coefficient, the energy gain from encoding ranges from 1.6 dB to 3 dB. It was shown that the presented bioinspired decoding method can be used for convolutional codes with a large code constraint length.In doing so, the presented method for decoding algebraic convolutional codes is less efficient than the Viterbi decoding method and turbo codes at a sufficient number of decoding iteration