Year: 2025
Type: article
Abstract: Molecular communication (MC) represents a novel approach to communication that employs nanoengineering and bioengineering technology to establish transient communication links in challenging environments. Deoxyribonucleic acid (DNA) molecular communication can transmit more and faster data than traditional molecular communication. Deoxyribonucleic acid (DNA) has been demonstrated to offer significant advantages over traditional information carriers, including its excellent storage density and structural stability, which renders it an ideal medium for information transmission. It is therefore imperative to investigate methods of increasing the data information density of DNA in order to reduce costs and enhance overall performance. LZW encoding is Lempel–Ziv–Welch encoding which creates a string table with shorter codes representing longer strings. Arithmetic coding is a compression process that involves the continuous refinement of probabilities of the input stream within an interval. A notable drawback of LZW coding is its suboptimal compression efficiency and the presence of data redundancy after dictionary mapping. Conversely, arithmetic coding attains compression efficiency that approaches the Shannon limit. In this study, we propose a novel DNA encoding method which is capable of adaptively generating coding streams in accordance with the characteristics of the stored content. The contribution of this paper is as follows: 1) A bespoke coding dictionary is constructed, which is capable of intelligently generating the corresponding coding stream in accordance with the specific characteristics of the file to be stored. 2) Utilising arithmetic coding techniques, these coding streams are converted into the final DNA sequence by means of compression techniques. Following comprehensive verification, it has been established that the information density of this encoding method is markedly superior to that of the prevailing mainstream encoding schemes.
Authors: Zhongyang Cheng, Qiang Liu, Kun Yang
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4409122047