Inscribed Matter Communication: Part I
Inscribed Matter Communication: Part I
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铭刻物质交流：第一部分
DOI：
10.1109/tmbmc.2017.2655025
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
IS Mian
中科院分区：
文献类型：
--
作者：
C. Rose;IS Mian
我们提供了一个基本的治疗的分子通信通道，其中“铭刻的物质”是通过空间间隙传输，以提供可靠的发送器和接收器之间的信号。内刻物质被定义为“标记”（生物/非生物对象）的集合，并且至少部分地受到生物系统的启发，在生物系统中，从分子到病毒和生物体的单独构建的离散颗粒的组由源释放并行进到目标-例如，形态发生剂或化学信息素从一个细胞、组织或生物体扩散到另一个。对于既不丢失也不修改的相同令牌，我们考虑使用三种候选通信方案编码的消息：1）令牌定时（定时释放）; 2）令牌有效载荷（合成）;以及3）令牌定时加有效载荷。我们提供了每个方案的容量界限，并讨论了它们的相对效用。我们发现，在不合理的假设下，兆比特每秒的速率可以支持在100毫微微瓦发射机功率。由于诸如标记浓度或标记计数之类的量是标记到达时间的衍生物，因此标记时间支持所有分子通信技术。因此，我们关于有效的基于令牌的信息传输的物理模型和结果可以为工程和生物学中各种理论和实际问题的调查提供信息。本文的第一部分主要讨论了容量的信息论界限。第二部分开发了一些支持这里提出的界限的数学和信息理论机制。
We provide a fundamental treatment of the molecular communication channel wherein “inscribed matter” is transmitted across a spatial gap to provide reliable signaling between a sender and receiver. Inscribed matter is defined as an ensemble of “tokens” (biotic/abiotic objects) and is inspired, at least partially, by biological systems where groups of individually constructed discrete particles ranging from molecules to viruses and organisms are released by a source and travel to a target—for example, morphogens or semiochemicals diffuse from one cell, tissue, or organism to another. For identical-tokens that are neither lost nor modified, we consider messages encoded using three candidate communication schemes: 1) token timing (timed release); 2) token payload (composition); and 3) token timing plus payload. We provide capacity bounds for each scheme and discuss their relative utility. We find that under not unreasonable assumptions, megabit per second rates could be supported at 100 femtoWatt transmitter powers. Since quantities such as token concentration or token counting are derivatives of token arrival timing, token timing undergirds all molecular communication techniques. Thus, our modeling and results about the physics of efficient token-based information transfer can inform investigations of diverse theoretical and practical problems in engineering and biology. This paper, Part I, focuses on the information theoretic bounds on capacity. Part II develops some of the mathematical and information theoretic machinery that support the bounds presented here.