Molecular Communication Channel Research Articles

Time-Hopping Concentration-Position Shift Keying for Multiple Access in Concentration-Encoded Molecular Communication

Molecular communication (MC) represents a paradigm shift in communication technologies, extending beyond traditional electromagnetic methods by incorporating advances in nanotechnology, biotechnology, and communication theory. This innovative approach holds promise for groundbreaking applications in diverse fields such as medicine, military operations, and environmental monitoring. MC employs molecules to carry and transmit data. In concentration-encoded molecular communication (CEMC), information is represented through the concentration levels of the transmitted molecules. In this study, we introduce a novel method named time-hopping concentration-position shift keying (TH-CPSK), designed to facilitate multiple access within MC networks. The TH-CPSK method encodes information based on the position of the transmitted molecular concentration, significantly enhancing the accuracy of data transmission by reducing interference in MC channels. Numerical simulations reveal that an increase in the number of users adversely affects communication performance. Furthermore, our findings indicate that augmenting the number of hops improves communication performance at transmitter-receiver distances of 1 cm and 2 cm. Conversely, at a distance of 3 cm, performance degradation is observed, attributed to the increased complexity. Therefore, it is important to carefully select the number of hops considering the molecular channel’s characteristics. Overall, TH-CPSK can enhance the efficiency and reliability of CEMC systems, offering a significant step forward in the realization of MC’s potential applications.

Frequency-Domain Model of Microfluidic Molecular Communication Channels With Graphene BioFET-Based Receivers

Frequency-Domain Model of Microfluidic Molecular Communication Channels With Graphene BioFET-Based Receivers

Analysis of Signal Distortion in Molecular Communication Channels Using Frequency Response

Analysis of Signal Distortion in Molecular Communication Channels Using Frequency Response

Heuristic Barycenter Modeling of Fully Absorbing Receivers in Diffusive Molecular Communication Channels

Heuristic Barycenter Modeling of Fully Absorbing Receivers in Diffusive Molecular Communication Channels

Estimating Time Window to Administer Anti-Cytokine Therapeutic Drugs to COVID-19 Patients.

The severe COVID-19 infection often leads to "Cytokine Release Syndrome (CRS)", which is a serious adverse medical condition causing multiple organ failures. Anti-cytokine therapy has shown promising results for the treatment of the CRS. As part of the anti-cytokine therapy, the immuno-suppressants or anti-inflammatory drugs are infused to block the release of cytokine molecules. However, determining the time window to infuse the required dose of drugs is challenging due to the complex processes involving the release of inflammatory markers, such as IL-6 and C-reactive protein (CRP) molecules. In this work, we develop a molecular communication channel to model the transmission, propagation, and reception of cytokine molecules. The proposed analytical model can be used as a framework to estimate the time window to administer anti-cytokine drugs to get successful outcomes. Simulation results show that at a 50 s-1 release rate of IL-6 molecules, the cytokine storm is triggered at ~ 10 hours, and consequently, the CRP molecules reach the severe level of 97 mg/L at ~ 20 hours. Further, the results reveal that with one-half of the release rate of IL-6 molecules, the time to observe the severe level of 97 mg/L CRP molecules increases by 50%.

Ratio Shift Keying Modulation for Time-Varying Molecular Communication Channels.

Molecular Communications (MC) is a bio-inspired communication technique that uses molecules to encode and transfer information. Many efforts have been devoted to developing novel modulation techniques for MC based on various distinguishable characteristics of molecules, such as their concentrations or types. In this paper, we investigate a particular modulation scheme called Ratio Shift Keying (RSK), where the information is encoded in the concentration ratio of two different types of molecules. RSK modulation is hypothesized to enable accurate information transfer in dynamic MC scenarios where the time-varying channel characteristics affect both types of molecules equally. To validate this hypothesis, we first conduct an information-theoretical analysis of RSK modulation and derive the capacity of the end-to-end MC channel where the receiver estimates concentration ratio based on ligand-receptor binding statistics in an optimal or suboptimal manner. We then analyze the error performance of RSK modulation in a practical time-varying MC scenario, that is mobile MC, in which both the transmitter and the receiver undergo diffusion-based propagation. Our numerical and analytical results, obtained for varying levels of similarity between the ligand types used for ratio-encoding, and varying number of receptors, show that RSK can significantly outperform the most commonly considered MC modulation technique, concentration shift keying (CSK), in dynamic MC scenarios.

Impact of Evanescence Process on Three-Dimensional Sub-Diffusion based Molecular Communication Channel.

In most of the existing works of molecular communication (MC), the standard diffusion environment is taken into account where the mean square displacement (MSD) of an information molecule (IM) scales linearly with time. On the contrary, this work considers the sub-diffusion motion that appears in crowded and complex (porous or fractal) environments (movement of the particles in the living cells) where the particle's MSD scales as a fractional order power law in time. Moreover, we examine an additional evanescence process resulting from which the molecules can degrade before hitting the boundary of the receiver (RX). Thus, in this work, we present a 3D MC system with a point transmitter (TX) and the spherical RX with the sub-diffusive behavior of an IM along with its evanescence. Furthermore, an IM's closed-form expressions for the arrival probability and the first passage time density (FPTD) are emulated in the above context. Additionally, we investigate the performance of MC by using the concentration-based modulation technique in a sub-diffusion channel. Finally, the considered MC channel is exploited in terms of the probability of detection, probability of false alarm, and probability of error for different parameters such as the reaction rate, fractional power, and radius of the RX.

Explainability of Neural Networks for Symbol Detection in Molecular Communication Channels

Explainability of Neural Networks for Symbol Detection in Molecular Communication Channels

A Computational Approach for the Characterization of Airborne Pathogen Transmission in Turbulent Molecular Communication Channels

Airborne pathogen transmission mechanisms play a key role in the spread of infectious diseases such as COVID-19. In this work, we propose a computational fluid dynamics (CFD) approach to model and statistically characterize airborne pathogen transmission via pathogen-laden particles in turbulent channels from a molecular communication viewpoint. To this end, turbulent flows induced by coughing and the turbulent dispersion of droplets and aerosols are modeled by using the Reynolds-averaged Navier-Stokes equations coupled with the realizable k-model and the discrete random walk model, respectively. Via simulations realized by a CFD simulator, statistical data for the number of received particles are obtained. These data are post-processed to obtain the statistical characterization of the turbulent effect in the reception and to derive the probability of infection. Our results reveal that the turbulence has an irregular effect on the probability of infection, which shows itself by the multi-modal distribution as a weighted sum of normal and Weibull distributions. Furthermore, it is shown that the turbulent MC channel is characterized via multi-modal, i.e., sum of weighted normal distributions, or stable distributions, depending on the air velocity.

Olfaction-Inspired MCs: Molecule Mixture Shift Keying and Cross-Reactive Receptor Arrays

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 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i> different types of receptors in order to detect the emitted molecule mixtures. The design of an MC system based on <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">orthogonal</i> molecule-receptor pairs implies that the hardware complexity of the receiver linearly scales with the number of signaling molecule types <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Q</i> (i.e., <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R = Q</i> ). Natural olfaction systems avoid such high complexity by employing arrays of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">cross-reactive</i> 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., <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Q</i> ≫ <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i> . 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. Finally, we present a comprehensive set of simulation results to evaluate the performance of the proposed MC designs revealing interesting insights regarding the design parameters. For instance, we show that mixtures comprising few types of molecules are best suited for communication since they can be more reliably detected by the cross-reactive array than one type of molecule or mixtures of many molecule types.

Estimation and Detection for Molecular MIMO Communications in the Internet of Bio-Nano Things

For the Internet of Bio-Nano Things (IoBNT) applications demanding high transmission rates, a well-modeled Molecular Communication (MC) channel is essential. The existing studies proposing multiple-input and multiple-output (MIMO) models for MC, however, often make the unrealistic assumption of using ideal receivers with perfect absorption. Hence, this paper proposes a molecular MIMO channel model with spherical transmitters and partially-absorbing ligand receptor-based receivers underpinned by four unique parameters. For the non-analytical nature of the MIMO channel, we use a supervised learning algorithm to estimate the number of molecules in the reception space. We evaluate the root mean square error (RMSE) of our solution, which returns consistent results. The estimation is used for ligand-receptor binding statistics, in which the intersymbol inference (ISI) and molecular interference are considered. We also propose two techniques based on convolutional and recurrent neural networks (CNN & RNN) as alternatives to the generic threshold-based detection. Our detectors outperform the threshold-based technique; specifically, the CNN-based method improves the mean bit error rate (BER) performance three times.

Convolutional Codec Implemented by Genetic Circuits for Molecular Communication.

Molecular communication (MC), which transmits information through molecules, has emerged as a promising technique to enable communication links between nanomachines. To establish information transmission using molecules, synthetic biology through genetic circuits techniques can be utilized to construct biological components. Recent efforts on genetic circuits have produced many exciting MC systems and generated substantial insights. With basic gene regulatory modules and motifs, researchers are now constructing artificial networks with novel functions that will serve as building blocks in the MC system. In this paper, we investigate the design of genetic circuits to implement the convolutional codec in a diffusion-based MC channel with the concentration shift keying (CSK) transmission scheme. At the receiver, a majority-logic decoder is applied to decode the received symbols. These functions are completely realized in the field of biochemistry through the activation and inhibition of genes and biochemical reactions, rather than through classical electrical circuits. Biochemical simulations are used to verify the feasibility of the system and analyze the impairments caused by diffusion noise and chemical reaction noise of genetic circuits.

Rescaled Brownian Motion of Molecules and Devices in Three-Dimensional Multiuser Mobile Molecular Communication Systems

This paper considers a three-dimensional anomalous-diffusive mobile molecular communication (MC) channel. Herein, the communicating devices, i.e., point transmitter (Tx) and passive receiver (Rx) can also move anomalously with the information-carrying molecule (ICM). In order to incorporate the anomalous diffusion phenomenon, the concept of rescaled-Brownian motion is explored. Two different scenarios, named point-to-point and multi-user MC systems, are considered for the analysis. First, considering the point-to-point scenario, the expressions for the channel impulse response (CIR) incorporating static and mobile Tx and Rx are derived. Further, the expressions for the peak time of CIR and the corresponding peak value are also derived. Furthermore, the point-to-point MC system is exploited in terms of bit-error-rate (BER), minimum BER, maximum mutual information, and throughput. A multi-user MC system is considered in the second scenario, and a molecular division multiple access (MDMA) method is used. The system is analyzed in terms of BER and throughput. Further, the system performance is optimized using two schemes known as min-max fairness for error probability and max-min fairness for throughput. Furthermore, we use best-to-best and best-to-worst assignment strategies to allocate different types of ICMs for each Rx. Subsequently, the optimal allocation for the number of ICMs is obtained when specific ICMs are assigned to all users/receivers for a two-user scenario. All the channel metrics are verified through particle-based and Monte-Carlo simulations.

Impact of Mutual Influence Between Bob and Eve on the Secrecy of Diffusion-Based Molecular Timing Channels

Secrecy in the context of molecular communication is a relatively unexplored area. The presence of an eavesdropping (Eve) unit in a molecular communication channel can pose a significant threat to the integrity of the information being transmitted from the legitimate transmitter (Alice) to the legitimate receiver (Bob). The presence of both Bob and Eve simultaneously in a multiparticle diffusion-based molecular timing (DB-MT) channel leads to a mutual influence between them. This mutual influence can play a significant role in analyzing the secrecy performance of DB-MT channels. Motivated by this, in this letter, we analyze the mutual influence between Bob and Eve in terms of the correlation ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\rho $ </tex-math></inline-formula> ) between their respective distances from Alice and its impact on the secrecy performance of the system. Specifically, we calculate the closed-form expression of the secrecy outage probability (SOP) metric by considering the impact of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\rho $ </tex-math></inline-formula> on the SOP of the system. Numerical results corroborate the derived analytical findings.

On Anomalous Diffusion of Devices in Molecular Communication Systems

A one-dimensional (1-D) anomalous-diffusive molecular communication channel is considered, wherein the devices (transmitter (TX) and receiver (RX)) can move in either direction along the axis. For modeling the anomalous diffusion of information carrying molecules (ICM) as well as that of the TX and RX, the concept of time-scaled Brownian motion is explored. In this context, a novel closed-form expression for the first hitting time density (FHTD) is derived. Further, the derived FHTD is validated through particle-based simulation. For the transmission of binary information, the timing modulation is exploited. Furthermore, the channel is assumed as a binary erasure channel (BEC) and analyzed in terms of achievable information rate (AIR).

Channel Capacity of Molecular Signaling via Diffusion in Confined Microenvironment

Aims: To model molecular signal propagation in confined environment. Background: Molecular communication (MC) is rooted in the concepts of understanding, modeling, and engineering information exchange among naturally and artificially synthesized nanosystems. To develop or analyze an MC system, there is the need to model the communication channel through which the molecular signal diffuse, from the transmitter to the receiver. Many models for the diffusion- based MC channel have been proposed in the literature for evaluating the performance of MC systems. Most of the contemporary works assume, and rightly so for some scenarios, that the MC channels under consideration have infinite boundaries. However, this assumption becomes invalid in bounded domains such as the interiors of natural cells and artificially synthesized nanosystems. Objective: In this paper, the model of molecular propagation in a confined. microenvironment is employ to explore the effect of such an environment on the MC system. Method: The mutual information of the channel and specifically the closed-form expression of the channel capacity of the molecular signaling in the confined geometry is derive. Result: Numerical results showing the variation in the channel capacity as the function of the channel dimension are presented. Conclusion: Results showed that the channel capacity increases with the decrease in the channel dimension. Subsequently, as the dimension of the channel tends to the nanoscale range typical of many artificially synthesized nanosystems, the effect of the channel width on the capacity and by induction on many other system metrics increases.

Equal-gain combining with interference mitigation for molecular type hopping assisted molecular shift keying systems

In multiple access molecular diffusive communications, many nano-machines exchange information and fuse data through a common Diffusive Molecular Communication (DMC) channel. Hence, there is Multiple-Access Interference (MAI), which should be sufficiently mitigated so as to achieve reliable communications. In this paper, we propose a novel low-complexity detection scheme, namely Equal-Gain Combining with Interference Mitigation (EGC-IM), for signal detection in the Molecular Type Hopping assisted Molecular Shift Keying (MTH-MoSK) DMC systems. By removing a number of entries from each row of the detection matrix formed during detection, the EGC-IM scheme shows its potential to significantly mitigate MAI and hence, outperform the conventional EGC scheme. Furthermore, the EGC-IM scheme has lower complexity than the conventional EGC scheme and therefore, it is beneficial for practical implementation.

Modeling Molecular Communication Channel in the Biological Sphere With Arbitrary Homogeneous Boundary Conditions

Diffusion-based molecular communication (DMC) is envisioned to realize nanonetworks for health applications. Inspired by sphere-like entities in the body, modeling diffusion channel in the biological sphere is motivated. The boundary condition in such biological environments is considered as homogeneous boundary conditions (HBC) that can simply model the molecular processes over biological barriers, e.g., carrier-mediated transport and transcytosis over the blood vessel walls. In this letter, we model the diffusive communication channel between a point source transmitter and a transparent receiver arbitrarily located inside a spherical environment with HBC. To this end, the concentration Green’s function (CGF) is analytically derived in the Fourier domain. Statistics of the signal received at the receiver is computed based on the derived CGF to obtain the analytical results. The analytical results are accurately confirmed with particle-based simulation (PBS). The performance of a simple on-off keying modulation scheme is also examined in terms of error probability.

Low complexity receiver design for time-varying Poisson molecular communication channels with memory

This paper introduces novel approaches for the design of the linear filter and the detection algorithms in unbounded advection diffusion-based molecular communication systems affected by inter-symbol interference. The received signal samples are modeled as Poisson random variables with memory where the effect of enzymatic reactions is also included. A main characteristic of the new filter design is to allow for a real-time computation of the filter's coefficients. For the detection of the transmitted symbols, we define an averaging method suitable for time-varying channels with finite memory length. In this paper the mean value of the Poisson channel is varying with time and we quantify the memory length with a finite number, from receiver point of view. The computational burden of the proposed approaches is evaluated in terms of number of required operations and their performance is evaluated in terms of bit error rate for different sets of parameters. We show that the proposed design of the filter and of the detection algorithms enables us to achieve a performance comparable to that of the state of the art approaches in relation to their simplicity.

A molecular communication channel consisting of a single reversible chain of hydrogen bonds in a conformationally flexible oligomer

SummaryCommunication of information through the global switching of conformation in synthetic molecules has hitherto entailed the inversion of chirality. Here, we report a class of oligomer through which information may be communicated through a global reversal of polarity. Ethylene-bridged oligoureas are constitutionally symmetrical, conformationally flexible molecules organized by a single chain of hydrogen bonds running the full length of the oligomer. NMR reveals that this hydrogen-bonded chain may undergo a coherent reversal of directionality. The directional uniformity of the hydrogen-bond chain allows it to act as a channel for the spatial communication of information on a molecular scale. A binding site at the terminus of an oligomer detects local information about changes in pH or anion concentration and transmits that information—in the form of a directionality switch in the hydrogen-bond chain—to a remote polarity-sensitive fluorophore. This propagation of polarity-encoded information provides a new mechanism for molecular communication.