Molecular communication (MC) is emerging paradigm that employs molecules as information carriers, inspired by biological signaling processes. Existing modulation schemes such as on-off keying (OOK), although simple to implement, suffer from high error probability in dynamic or hard-to-estimate channels due to their dependence on accurate channel information (CI). This work develops a unified MC constellation framework that allows higher order modulation across multiple dimensions and designs efficient constellation for dynamic MC. We propose a general multi-axis concentration modulation (MAxCM(K,M)) of modulation order M, utilizing K-dimensional constellation space with each axis corresponding to a particular molecular type, and information is jointly encoded in their concentrations. The corresponding ML decoders are derived for both static and dynamic MC under exact and partial CI. We show that the use of MAxCM can provide improvements in spectral efficiency (SE) and error rate. We then focus on a special subclass, namely multiple-axis ratio shift keying (MAxRSK), that encodes information into the concentration ratios. Its ML decoder is shown to be a weighted combiner, and design constraints are derived to enable channel-independent decoding. We study one such example, symmetric binary RSK (SBRSK), to show its robustness in dynamic channel conditions compared to OOK. Numerical investigations show significant performance gains over OOK and provide insights into optimal constellation design and receiver configurations.

翻译：分子通信是一种新兴的通信范式，其受生物信号传递过程启发，利用分子作为信息载体。现有的调制方案（如开关键控）虽然实现简单，但由于其依赖准确的信道信息，在动态或难以估计的信道中误码率较高。本文构建了一个统一的分子通信星座框架，支持跨多个维度的高阶调制，并为动态分子通信设计了高效的星座结构。我们提出了一种通用的多轴浓度调制方案，其调制阶数为M，利用K维星座空间，其中每个轴对应一种特定分子类型，信息通过其浓度联合编码。针对静态与动态分子通信场景，分别在精确与部分信道信息条件下推导了相应的最大似然解码器。研究表明，采用多轴浓度调制可提升频谱效率并降低误码率。我们进一步聚焦于一个特殊子类——多轴比例移位键控，该方案将信息编码于浓度比值中。其最大似然解码器被证明是一种加权合并器，并通过推导设计约束实现了与信道无关的解码。我们以对称二进制比例移位键控为例，通过与开关键控对比，证明了其在动态信道条件下的鲁棒性。数值分析表明，该方案较开关键控具有显著的性能增益，并为最优星座设计与接收机配置提供了理论依据。