M.D. Artamonov1

1 ANO "Digital Audit" (Moscow, Russia)

1 a.mark.2001@mail.ru

In modern telecommunication systems, there are clustering errors, which necessitates the use of discrete memory communication channels. The existing approaches to statistical modeling of such channels have a number of disadvantages. The interleaving mechanisms that mask the correlation introduce fixed delays that are unacceptable for real-time systems. Models based on simply connected binary Markov chains do not take into account the high levels of stochastic relationships used in real channels. As a result, existing approaches do not allow full use of the a priori information stored in the channel's memory, which limits the achievable noise immunity of the system. The aim of the research is to develop a generalized model of a discrete communication channel with memory and noise-resistant coding, which takes into account the Markov properties of the error source, the mathematical apparatus of the monitoring function and the parameters of block coding to increase the reliability of message transmission. As a result, a generalized model of a discrete memory communication channel was developed, including an observation function that calculates the error vector by comparing the received message characters with a priori known bits and data skip positions. The model also includes an estimation algorithm for calculating a matrix of transition probabilities of arbitrary dimension, as well as a decoding algorithm that uses the minimum average risk criterion as a decisive rule. A comparative analysis showed that the developed algorithm surpasses the algorithm based on a singly connected Markov chain in terms of the reliability of message transmission by an average of 5.9%. The developed model makes it possible to increase the reliability of message transmission in noise conditions without introducing additional time delays and without increasing the structural redundancy of the correction code. The results of the study can be used in modern noise-resistant decoding systems.

Artamonov M.D. Discrete communication channel model that takes into consideration the Markov properties of the error source, the monitoring function, and the code parameters // Science Intensive Technologies. 2026. V. 27. № 5. P. 45−51. DOI: https://doi.org/10.18127/j19998465-202605-05

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