Evaluation of efficiency of ordered statistics decoding for algebraic convolutional codes
DOI:
https://doi.org/10.26906/SUNZ.2025.1.209-212Keywords:
algebraic convolutional codes, ordered statistics, decoding, efficiency, modeling, radio communication systemsAbstract
The paper considers the application of ordered statistics decoding to short algebraic convolutional codes. It is
shown that this approach is expedient to use for reliable transmission of service messages in control channels of modern radio
communication systems. The paper proposes an algorithm for software implementation of the process of noise-resistant information transmission for given conditions. The general principles and features of the implementation of the main stages of modeling are considered. The research was conducted for algebraic convolutional codes with maximum code distance for different
code constraint lengths. Decoding of these codes was implemented for two selected values of ordered statistics in additive white
Gaussian noise channel. In the developed software implementation, decoding was carried out according to the criterion of minimizing the weighted Hamming weight between the generated test codewords and the received word. The modeling was completed when the target value of the error rate was reached. According to the results of the conducted research, it was determined that
ordered statistics decoding is effective for short algebraic convolutional codes, especially in the range of high signal-to-noise
ratio. The presented decoding method is advisable to use to increase the efficiency of service information transmission based on
short algebraic convolutional codes in new generation radio communication systems.
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