Molecular Communication (MC) has emerged as a promising paradigm employing molecules to transfer information at the nano-scale. Unlike MC channel coding, MC source coding has remained mostly an unexplored area of research. In a recent paper, prefix source coding was introduced into the field, through an MC-adapted version of the Huffman Coding. In the context of MC source coding, this paper proposes the Molecular Arithmetic Coding (MAC) whose algorithmic implementation and code-structure is non-arbitrarily different than that of the widely-known classical arithmetic coding. MAC is designed to mitigate Inter-Symbol Interference (ISI) for alphabets with known symbol probabilities through, in a highly efficient way, avoiding consecutive 1-bits. However, due to bit precision limitations any arithmetic coding method faces, without any assumption made on the structure of the symbol alphabet, unique-decodability of MAC is not guaranteed. Accordingly, a uniquely-decodable new coding scheme named Molecular Arithmetic with Prefix Coding (MAPC) is also introduced. Across multiple alphabets, we show that MAPC provides a better compression performance compared to the optimal MC-adapted prefix coding. Simulation results of an exemplary alphabet demonstrates the superior symbol and word error rate performance of MAPC compared to the optimal MC-adapted prefix coding and to the uncoded BCSK schemes.

翻译：分子通信（MC）作为一种利用分子在纳米尺度传输信息的新兴范式已崭露头角。与MC信道编码不同，MC信源编码仍是一个尚未充分探索的研究领域。在近期的一篇论文中，通过一种适用于MC的霍夫曼编码变体，前缀信源编码被引入该领域。本文在MC信源编码框架下提出分子算术编码（MAC），其算法实现和码结构与广为人知的经典算术编码存在本质性差异。MAC旨在通过高效避免连续比特'1'的方式，为已知符号概率的字母表减轻符号间干扰（ISI）。然而，由于任何算术编码方法均受限于比特精度，且未对符号字母表结构作出任何假设，MAC的唯一可译性无法得到保证。据此，本文还提出一种具有唯一可译性的新型编码方案——分子算术前缀编码（MAPC）。在多种字母表上的实验表明，与最优MC适配前缀编码相比，MAPC能提供更优的压缩性能。以典型字母表为例进行的仿真结果证明，相较于最优MC适配前缀编码及未编码BCSK方案，MAPC在符号错误率和字错误率性能上均具有显著优势。