Shannon Capacity of Channels with Markov Insertions, Deletions, and Substitutions: Analysis and Theorems

Core Concepts

Existence and properties of i-capacity for Markov-IDS channel sequences.

Abstract

The content discusses the Shannon capacity of channels with Markov insertions, deletions, and substitutions. It extends the concept to channels with memory in synchronization errors, proving the existence of a coding scheme achieving mutual information limits. The Markov-IDS channel model is introduced, showing its generalization of IDS and FSMC channels. The paper outlines the structure of the Markov-IDS channel sequence and proves the existence of i-capacity for such sequences. Theorems and propositions are presented to support the analysis.

Stats

A classical result for channels is their information stability, implying the existence of the Shannon capacity.
The paper extends this result to channels with memory in synchronization errors.
The Markov-IDS channel model is introduced, showing its generalization of IDS and FSMC channels.

Quotes

"We consider IDS channels with Markov memory, i.e., the underlying insertions/deletions are governed by a Markov chain."
"The Markov-IDS channel is a generalization of both IDS and FSMC."

Key Insights Distilled From

Shannon Capacity of Channels with Markov Insertions, Deletions and Substitutions

by Ruslan Moroz... at arxiv.org 03-28-2024

https://arxiv.org/pdf/2401.16063.pdf

Deeper Inquiries

How does the Markov-IDS channel model impact the capacity theorems for different types of channels

The Markov-IDS channel model significantly impacts capacity theorems for various types of channels by extending the analysis to channels with memory in synchronization errors. This model considers channels where insertions, deletions, and substitutions are governed by a stationary and ergodic finite state Markov chain. By incorporating memory into the synchronization errors, the model allows for a more realistic representation of communication channels, particularly those with complex error patterns. This extension enables the study of channels with memory in a systematic and mathematically rigorous manner, providing insights into the behavior of such channels and their capacity properties.

What are the practical implications of the existence of i-capacity for Markov-IDS channel sequences

The existence of i-capacity for Markov-IDS channel sequences has practical implications in the design and analysis of communication systems. The i-capacity represents the maximum achievable mutual information between the input and output of a channel sequence, indicating the ultimate limit of information transmission efficiency. For Markov-IDS channels, the existence of i-capacity ensures that there is a coding scheme that can achieve this limit, allowing for the development of efficient communication protocols that maximize information transfer rates. This is particularly valuable in applications where reliable and high-capacity data transmission is essential, such as in DNA storage channels and other information-critical systems.

How can the concept of information stability be applied to other types of communication channels beyond the Markov-IDS model

The concept of information stability, as applied to Markov-IDS channels, can be extended to other types of communication channels to analyze their capacity properties and coding theorems. Information stability ensures that the mutual information capacity is equal to the coding capacity, indicating the robustness of the channel in transmitting information reliably. By applying the principles of information stability to different channel models, researchers can determine the optimal coding schemes and error correction techniques to maximize data transmission rates while maintaining data integrity. This approach can be beneficial in various communication scenarios, including wireless communication, optical communication, and satellite communication, where channel reliability and efficiency are crucial factors.