论文标题
嗅觉启发的MC:分子混合物移位键和交叉反应受体阵列
Olfaction-inspired MCs: Molecule Mixture Shift Keying and Cross-Reactive Receptor Arrays
论文作者
论文摘要
在本文中,我们提出了一个受动物嗅觉启发的工程分子通信(MC)系统的新颖概念。我们专注于多用户方案,其中几个发射器希望与中央接收器进行通信。我们假设每个发射机都采用不同类型的信号分子的独特混合物来表示其信息,并且接收器配备了一个包括$ r $不同类型的受体的阵列,以检测发射的分子混合物。基于\ textIt {正交}分子受体对的MC系统的设计意味着接收器的硬件复杂性线性缩放,信号分子类型$ q $(即$ r = q $)。天然嗅觉系统通过采用\ textIt {交叉反应}受体的阵列来避免如此高的复杂性,其中每种类型的分子激活多种类型的受体,并且每种类型的受体主要被多种类型的分子激活,虽然具有不同的活化强度。例如,人们认为人类嗅觉系统仅使用几百种受体类型(即$ q \ gg r $)区分数千种化学物质。在这一观察结果的推动下,我们首先开发了一个端到端MC频道模型,该模型解释了嗅觉的关键特性。随后,我们介绍提出的发射器和接收器设计。特别是,在一组信号分子的情况下,我们开发出分配分子为不同发射器的算法,并优化混合字母以进行通信。此外,我们将分子混合物恢复为凸压缩感知问题,可以通过可用的数值求解器有效地解决。
In this paper, we propose a novel concept for engineered molecular communication (MC) systems inspired by animal olfaction. We focus on a multi-user scenario where several transmitters wish to communicate with a central receiver. We assume that each transmitter employs a unique mixture of different types of signaling molecules to represent its message and the receiver is equipped with an array comprising $R$ different types of receptors in order to detect the emitted molecule mixtures. The design of an MC system based on \textit{orthogonal} molecule-receptor pairs implies that the hardware complexity of the receiver linearly scales with the number of signaling molecule types $Q$ (i.e., $R=Q$). Natural olfaction systems avoid such high complexity by employing arrays of \textit{cross-reactive} receptors, where each type of molecule activates multiple types of receptors and each type of receptor is predominantly activated by multiple types of molecules albeit with different activation strengths. For instance, the human olfactory system is believed to discriminate several thousands of chemicals using only a few hundred receptor types, i.e., $Q\gg R$. Motivated by this observation, we first develop an end-to-end MC channel model that accounts for the key properties of olfaction. Subsequently, we present the proposed transmitter and receiver designs. In particular, given a set of signaling molecules, we develop algorithms that allocate molecules to different transmitters and optimize the mixture alphabet for communication. Moreover, we formulate the molecule mixture recovery as a convex compressive sensing problem which can be efficiently solved via available numerical solvers.