A General Analytical Approximation to Impulse Response of 3-D Microfluidic Channels in Molecular Communication

In this paper, the impulse response for a 3-D microfluidic channel in the presence of Poiseuille flow is obtained by solving the diffusion equation in radial coordinates. Using the radial distribution, the axial distribution is then approximated accordingly. Since Poiseuille flow velocity changes with radial position, molecules have different axial properties for different radial distributions. We, therefore, present a piecewise function for the axial distribution of the molecules in the channel considering this radial distribution. Finally, we lay evidence for our theoretical derivations for impulse response of the microfluidic channel and radial distribution of molecules through comparing them using various Monte Carlo simulations.Comment: The manuscript is submitted to IEEE: Transactions on Nanobioscienc

Analytical Derivation of the Impulse Response for the Bounded 2-D Diffusion Channel

This paper focuses on the derivation of the distribution of diffused particles absorbed by an agent in a bounded environment. In particular, we analogously consider to derive the impulse response of a molecular communication channel in 2-D and 3-D environment. In 2-D, the channel involves a point transmitter that releases molecules to a circular absorbing receiver that absorbs incoming molecules in an environment surrounded by a circular reflecting boundary. Considering this setup, the joint distribution of the molecules on the circular absorbing receiver with respect to time and angle is derived. Using this distribution, the channel characteristics are examined. Furthermore, we also extend this channel model to 3-D using a cylindrical receiver and investigate the channel properties. We also propose how to obtain an analytical solution for the unbounded 2-D channel from our derived solutions, as no analytical derivation for this channel is present in the literature.Comment: 13 pages and 5 figure

Modeling duct flow for molecular communication

Active transport such as fluid flow is sought in molecular communication to extend coverage, improve reliability, and mitigate interference. Flow models are often over-simplified, assuming one-dimensional diffusion with constant drift. However, diffusion and flow are usually encountered in three-dimensional bounded environments where the flow is highly non-uniform such as in blood vessels or microfluidic channels. For a qualitative understanding of the relevant physical effects inherent to these channels, based on the Peclet number and the transmitter-receiver distance, we study when simplified models of uniform flow and advection-only transport are applicable. For these two regimes, analytical expressions for the channel impulse response are derived and validated by particle-based simulation. Furthermore, as advection-only transport is typically overlooked and hence not analyzed in the molecular communication literature, we evaluate the symbol error rate for exemplary on-off keying as performance metric

Channel Estimation for Diffusive Molecular Communications

In molecular communication (MC) systems, the \textit{expected} number of molecules observed at the receiver over time after the instantaneous release of molecules by the transmitter is referred to as the channel impulse response (CIR). Knowledge of the CIR is needed for the design of detection and equalization schemes. In this paper, we present a training-based CIR estimation framework for MC systems which aims at estimating the CIR based on the \textit{observed} number of molecules at the receiver due to emission of a \textit{sequence} of known numbers of molecules by the transmitter. Thereby, we distinguish two scenarios depending on whether or not statistical channel knowledge is available. In particular, we derive maximum likelihood (ML) and least sum of square errors (LSSE) estimators which do not require any knowledge of the channel statistics. For the case, when statistical channel knowledge is available, the corresponding maximum a posteriori (MAP) and linear minimum mean square error (LMMSE) estimators are provided. As performance bound, we derive the classical Cramer Rao (CR) lower bound, valid for any unbiased estimator, which does not exploit statistical channel knowledge, and the Bayesian CR lower bound, valid for any unbiased estimator, which exploits statistical channel knowledge. Finally, we propose optimal and suboptimal training sequence designs for the considered MC system. Simulation results confirm the analysis and compare the performance of the proposed estimation techniques with the respective CR lower bounds.Comment: to be appeared in IEEE Transactions on Communications. arXiv admin note: text overlap with arXiv:1510.0861

Nano/Bio-Receiver Architectures and Detection Methods for Molecular Communications

Internet of Nano Things (IoNT) is an emerging technology, which aims at extending the connectivity into nanoscale and biological environments with collaborative networks of artificial nanomachines and biological entities integrated into the Internet. To enable the IoNT and its groundbreaking applications, such as real-time intrabody health monitoring, it is imperative to devise nanoscale communication techniques with low-complexity transceiver architectures. Bio-inspired molecular communications (MC), which uses molecules to transfer information, is the most promising technique to realise IoNT due to its inherent biocompatibility and reliability in physiologically-relevant environments. Despite the substantial body of work concerning MC, the implications of an interface between MC channel and practical MC transceiver architectures are largely neglected, leading to a major gap between theory and practice. As the first step to remove this discrepancy, in this thesis, I develop a realistic analytical ICT model for microfluidic MC with surface-based receivers as a convection-diffusion-reaction system. In the second part, I focus on biological MC receivers, which can be implemented in living cells using synthetic biology tools. In this direction, I theoretically develop low-complexity and reliable MC detection methods exploiting the various statistics of the stochastic ligand-receptor interactions at the membrane of biological MC receivers. The estimation and detection theoretical analysis of these detection methods demonstrate that even single type of receptors can provide sufficient statistics to overcome the receptor saturation problem, cope with the interference of non-cognate molecules, and simultaneously sense the concentration of multiple types of ligands. I also propose synthetic receptor designs for the transduction of decision statistics into a representation by concentration of intracellular molecules, and design chemical reaction networks performing decoding with intracellular reactions. Finally, I fabricate a micro/nanoscale MC receiver based on graphene field-effect transistor biosensors and perform its ICT characterisation in a custom-designed microfluidic MC system with the information encoded into the concentration of DNAs. This experimental platform is the first practical demonstration of micro/nanoscale MC, and can serve as a testbed for developing realistic MC methods