This paper presents a Markov-based system model for microfluidic molecular communication (MC) channels. By discretizing the advection-diffusion dynamics, the proposed model establishes a physically consistent state-space formulation. The transition matrix explicitly captures diffusion, advective flow, reversible binding, and flow-out effects. The resulting discrete-time formulation enables analytical characterization of both transient and equilibrium responses through a linear system representation. Numerical results verify that the proposed framework accurately reproduces channel behaviors across a wide range of flow conditions, providing a tractable basis for the design and analysis of MC systems in microfluidic environments.

DNA-based Molecular Communication (MC) has received significant attention for its potential in nanoscale bio-communication systems such as drug delivery, biosensing, and the Internet of Bio-Nano Things (IoBNT). This paper presents a theoretical model for DNA-based MC in spatially confined environments. In the proposed framework, the transmitter (TX) releases complementary DNA (cDNA) molecules in the channel, which reversibly bind to immobilized probe DNAs at the receiver (RX). The stochastic dynamics of diffusion, binding, and release are characterized by a Markov process. Closed-form channel characteristics, including the Channel Impulse Response (CIR), equilibrium distribution, and settling time, are derived. System performance is evaluated through both the proposed model and Particle-Based Simulation (PBS). The results demonstrate that the proposed model effectively describes the dynamic behavior of DNA hybridization-based MC, offering accurate predictions with significantly lower computational complexity than conventional simulation methods.

As one of the most prevalent diseases worldwide, plaque formation in human arteries, known as atherosclerosis, is the focus of many research efforts. Previously, molecular communication (MC) models have been proposed to capture and analyze the natural processes inside the human body and to support the development of diagnosis and treatment methods. In the future, synthetic MC networks are envisioned to span the human body as part of the Internet of Bio-Nano Things (IoBNT), turning blood vessels into physical communication channels. By observing and characterizing changes in these channels, MC networks could play an active role in detecting diseases like atherosclerosis. In this paper, building on previous preliminary work for simulating an MC scenario in a plaque-obstructed blood vessel, we evaluate different analytical models for non-Newtonian flow and derive associated channel impulse responses (CIRs). Additionally, we add the crucial factor of flow pulsatility to our simulation model and investigate the effect of the systole-diastole cycle on the received particles across the plaque channel. We observe a significant influence of the plaque on the channel in terms of the flow profile and CIR across different emission times in the cycle. These metrics could act as crucial indicators for early non-invasive plaque detection in advanced future MC methods.

Molecular communication (MC) is getting closer to becoming a next-generation communication technology with many applications in life sciences and other industrial applications. Multiple techniques have been proposed on how to design MC receivers depending on the channel characteristics. Experimentally, first testbeds also demonstrate the potentialities for communication using molecules as carriers. In this paper, we focus on developing a reinforcement learning (RL)-based receiver, targeting a realistic scenario with testbed measurements, and addressing transmitter mobility. Leveraging on reported solutions for machine learning (ML) methods, we demonstrate the usability of an RL agent to synchronize the receiver to the received signal. We evidence the learning capabilities of the agent to compensate for the impact of mobility, achieving a low probability of missed detection and small misalignment with the symbol time.

In a communication scenario with two transceivers (TRXs) and one relay, four time slots are required to communicate one packet in each direction if the relay uses a store-and-forward technique. With digital network coding (NC) three time slots are needed, and if analog netwok coding (ANC) is used, only two time slots are necessary. Communication systems with a low transmission rate such as molecular communication (MC) systems can especially benefit from the traffic reduction of ANC. The available literature only considers theoretical studies on the application of NC in MC nanonetworks. In this paper, we present for the first time a macroscale MC testbed for ANC to fill the gap between theory and practice. By using our testbed, we demonstrate the influence of time synchronization on the bit error ratio (BER) performance of the network coded MC system. We also study the influence of the bit sequence length on the error ratio of the system. Furthermore, we implemented duplex NC and demonstrated that the error ratios of half duplex and full duplex NC are close, but full duplex NC results in a time gain of up to$(n-1)$time slots for a bit sequence length n.