Molecular communications rely on diffusive propagation to transport information, which is attractive for a variety of nano-scale applications. Due to the long-tail channel response, spatial-temporal coding of information may lead to severe inter-symbol interference (ISI). Classical linear signal processing in wireless communications is usually operating with high complexity and high signal-to-noise ratios, whereas signal processing in molecular communication system requires operating in opposite conditions. In this work, we propose a novel signal processing paradigm inspired by the biological principle, which enables low-complexity signal detection in extremely noisy environments. We first propose a non-linear filter inspired by stochastic resonance, which is found in a variety of biological systems, and it can significantly improve the output SNR by converting noise to useful signals. Then, we design a non-coherent detection method, one which exploits the generally transient trend of observed signals (i.e. quick-rising and slow-decaying) rather than hidden channel state information (CSI), thus excluding CSI estimation and involving only summations. Implementation issues are also discussed, including parameters configuration and adaptive threshold. Numerical results show that the proposed bio-inspired scheme can improve the performance remarkably over classical approaches. Even compared with the optimal linear methods, the required SNR of the proposed scheme can be reduced by 7 dB, which reaffirms why it can be used in noisy biological environments. As the first attempt to design bio-inspired molecular signal detectors, the proposed non-linear processing paradigm may provide the great promise to the emerging nano-machine applications.

中文翻译：

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分子通信中与 CSI 无关的非线性信号检测

分子通信依赖于扩散传播来传输信息，这对各种纳米级应用都很有吸引力。由于长尾信道响应，信息的时空编码可能导致严重的符号间干扰（ISI）。无线通信中的经典线性信号处理通常以高复杂度和高信噪比运行，而分子通信系统中的信号处理则需要在相反的条件下运行。在这项工作中，我们提出了一种受生物学原理启发的新型信号处理范式，它可以在极其嘈杂的环境中进行低复杂度的信号检测。我们首先提出了一种受随机共振启发的非线性滤波器，它存在于各种生物系统中，它可以通过将噪声转换为有用信号来显着提高输出 SNR。然后，我们设计了一种非相干检测方法，该方法利用观察到的信号的一般瞬态趋势（即快速上升和缓慢衰减）而不是隐藏的信道状态信息（CSI），因此排除了 CSI 估计并且只涉及求和。还讨论了实现问题，包括参数配置和自适应阈值。数值结果表明，与经典方法相比，所提出的仿生方案可以显着提高性能。即使与最佳线性方法相比，所提出的方案所需的 SNR 也可以降低 7 dB，这再次证实了为什么它可以用于嘈杂的生物环境。作为设计仿生分子信号探测器的首次尝试，