Data compression and run-length-limited ISI-mitigation (RLIM) coding for molecular communication

Molecular Communication (MC) enables information transfer at the nanoscale by encoding messages into sequences of released molecules, but its practical deployment is hindered by two fundamental constraints: the high cost of molecule releases and severe inter-symbol interference (ISI) arising from residual molecules in the diffusion channel. This thesis develops coding techniques to tackle each challenge. We first introduce source‐coding schemes that reduce both average code length and molecule usage. Building on an MC-adapted Huffman baseline (MoHuffman), we propose Optimized Molecular Prefix Coding (MoPC) to select a prefix codebook with minimal expected length and fewest number of 1-symbols. To push compression further, we derive Molecular Arithmetic Coding (MoAC) using an existing constrained arithmetic coding construction scheme and show its superior efficiency over substitution arithmetic coding (SAC), our different adaptation of arithmetic source coding to MC. Finally, we design Molecular Arithmetic with Prefix Coding (MoAPC) to ensure unique decodability under finite-precision arithmetic. Using two nucleotide alphabets, we then demonstrate that MoAPC has a better compression ratio than MoPC. Through MC simulations, the effectiveness of the proposed methods is also shown. To mitigate ISI at the channel coding level, we develop an infinite family of Run-Length-Limited ISI-Mitigation (RLIM) codes with a corresponding built-in error correction algorithm. We then demonstrate, via binomial and diffusion channel simulations, that RLIM codes reduce bit-error rate compared to prominent coding schemes. Together, these contributions lay a comprehensive foundation for reliable and efficient diffusion-based Molecular Communication.