Molecular Arithmetic Coding (MoAC) and Optimized Molecular Prefix Coding (MoPC) for Diffusion-Based Molecular Communication

Molecular communication (MC) enables information transfer through molecules at the nano-scale. This paper presents new and optimized source coding (data compression) methods for MC. In a recent paper, prefix source coding was introduced into the field, through an MC-adapted version of the Huffman coding. We first show that while MC-adapted Huffman coding improves symbol error rate (SER), it does not always produce an optimal prefix codebook in terms of coding length and power. To address this, we propose optimal molecular prefix coding (MoPC). The major result of this paper is the Molecular Arithmetic Coding (MoAC), which we derive based on an existing general construction principle for constrained arithmetic channel coding, equipping it with error correction and data compression capabilities for any finite source alphabet. We theoretically and practically show the superiority of MoAC to SAC, our another adaptation of arithmetic source coding to MC. However, MoAC’s unique decodability is limited by bit precision. Accordingly, a uniquely-decodable new coding scheme named Molecular Arithmetic with Prefix Coding (MoAPC) is introduced. On two nucleotide alphabets, we show that MoAPC has a better compression performance than optimized MoPC. MC simulation results demonstrate the effectiveness of the proposed methods.