An Information Theoretic Framework to Analyze Molecular Communication Systems Based on Statistical Mechanics
An Information Theoretic Framework to Analyze Molecular Communication Systems Based on Statistical Mechanics
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DOI：
10.1109/jproc.2019.2927926
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发表时间：
2019-07-01
影响因子：
20.6
通讯作者：
Balasubramaniam, Sasitharan
中科院分区：
文献类型：
--
作者：
Akyildiz, Ian F.;Pierobon, Massimiliano;Balasubramaniam, Sasitharan
在过去的10年里，分子通信（MC）已经确立了自己作为一个关键的通信理论的变革范式。受生物系统中化学通信的启发，该学科的重点是通过分子交换进行信息传输的建模，表征和工程，并立即应用于生物技术，医学，生态学和国防等领域。尽管有过多的不同的贡献，这已经发表了关于这个问题的研究界，一个通用的框架来研究MC系统的性能目前还没有。本文旨在填补这一空白，提供了一个分析的物理过程的MC，沿着与他们的信息理论基础。特别是，提出了一个数学框架来定义MC中的主要功能块，由化学动力学和统计力学的一般模型支持。在这个框架中，朗之万方程被用作MC系统中分子传播的统一建模工具，并作为确定信息容量的方法的核心。不同的MC系统进行分类的基础上的分子传播的过程，其在朗之万方程的贡献。分类和每个类别下的系统如下：随机游走（钙信号，神经元通信和细菌群体感应），漂移随机游走（心血管系统，微流体系统和信息素通信）和主动运输（分子马达和细菌趋化性）。对于这些类别中的每一个，一个通用的信息容量表达式推导出简化的假设下，随后讨论在更复杂的MC系统的具体功能块。最后，根据所提出的框架，设想了MC作为一门学科的未来路线图。
Over the past 10 years, molecular communication (MC) has established itself as a key transformative paradigm in communication theory. Inspired by chemical communications in biological systems, the focus of this discipline is on the modeling, characterization, and engineering of information transmission through molecule exchange, with immediate applications in biotechnology, medicine, ecology, and defense, among others. Despite a plethora of diverse contributions, which has been published on the subject by the research community, a general framework to study the performance of MC systems is currently missing. This paper aims at filling this gap by providing an analysis of the physical processes underlying MC, along with their information-theoretic underpinnings. In particular, a mathematical framework is proposed to define the main functional blocks in MC, supported by general models from chemical kinetics and statistical mechanics. In this framework, the Langevin equation is utilized as a unifying modeling tool for molecule propagation in MC systems, and as the core of a methodology to determine the information capacity. Diverse MC systems are classified on the basis of the processes underlying molecule propagation, and their contribution in the Langevin equation. The classifications and the systems under each category are as follows: random walk (calcium signaling, neuron communication, and bacterial quorum sensing), drifted random walk (cardiovascular system, microfluidic systems, and pheromone communication), and active transport (molecular motors and bacterial chemotaxis). For each of these categories, a general information capacity expression is derived under simplifying assumptions and subsequently discussed in light of the specific functional blocks of more complex MC systems. Finally, in light of the proposed framework, a roadmap is envisioned for the future of MC as a discipline.