Motivated by classical communications engineering, early works in molecular communication (MC) largely adopted established modeling and signal processing concepts from wireless electromagnetic communication systems. In the context of the human cardiovascular system (CVS), MC channel models evolved from simple unbounded and single-duct environments mimicking individual blood vessels to complex vessel network (VN) topologies, generally at the expense of analytical tractability. Up until now, this has largely prohibited rigorous communication-theoretic analysis of large-scale VNs. In this work, we leverage a recently established closed-form analytical channel model for VNs, named mixture of inverse Gaussians for hemodynamic transport (MIGHT), to conduct the first systematic communication-theoretic study of MC in complex, large-scale VNs. Based on MIGHT, we derive a Poisson channel noise model and unveil structural analogies between multipath wireless communications (MWC) and advective-diffusive MC in VNs. In particular, we establish classical MWC metrics, namely the root mean squared (RMS) delay spread, the mean excess delay, and the coherence bandwidth, for MC in VNs and derive closed-form expressions for the channel frequency response and power delay profile (PDP). Building on this characterization, we propose a VN-adapted, coherent decision-feedback (DF) detector and show how the derived multipath metrics can inform the choice of critical system parameters like the symbol duration, the sampling time, and the memory length. Additionally, we evaluate the detector's performance in different VNs exhibiting inter-symbol interference (ISI). Together, these contributions open the door to a systematic, MWC-inspired MC system design for large-scale VNs.

翻译：受经典通信工程启发，分子通信（MC）的早期工作大量借鉴了无线电磁通信系统中成熟的建模和信号处理概念。在人体心血管系统（CVS）背景下，MC信道模型从模拟单根血管的简单无界和单管道环境，演变为复杂的血管网络（VN）拓扑，但这通常以牺牲解析可处理性为代价。迄今为止，这在很大程度上阻碍了对大规模VN进行严格的通信理论分析。本文利用近期建立的VN闭式解析信道模型——用于血流动力传输的逆高斯混合模型（MIGHT），首次对复杂大规模VN中的MC展开系统性的通信理论研究。基于MIGHT，我们推导了泊松信道噪声模型，并揭示了无线多径通信（MWC）与VN中对流扩散MC之间的结构相似性。具体而言，我们为VN中的MC建立了经典的MWC度量指标，即均方根（RMS）时延扩展、平均过量时延和相干带宽，并推导了信道频率响应和功率时延分布（PDP）的闭式表达式。基于这一表征，我们提出了一种适用于VN的相干决策反馈（DF）检测器，并展示了如何利用推导的多径度量指标指导关键系统参数（如符号持续时间、采样时间和记忆长度）的选择。此外，我们评估了该检测器在不同存在符号间干扰（ISI）的VN中的性能。这些贡献共同为大规模VN中系统化的、受MWC启发的MC系统设计打开了大门。