arXiv subjects

Arman Ahmadzadeh

Publications and source records attributed to Arman Ahmadzadeh.

At least 19 recordsLinked to original sources

arXiv2022

Experimental System for Molecular Communication in Pipe Flow With Magnetic Nanoparticles

In the emerging field of molecular communication (MC), testbeds are needed to validate theoretical concepts, motivate applications, and guide further modeling efforts. To this end, this paper presents a flexible and extendable in-vessel testbed for flow-based macroscopic MC, abstractly modeling, e.g., a part of a chemical reactor or a blood vessel. Signaling is based on injecting non-reactive superparamagnetic iron oxide nanoparticles (SPIONs) dispersed in an aqueous suspension into a tube with background flow. A commercial magnetic susceptometer is used for non-intrusive downstream signal reception. To shed light on the operation of the testbed, we identify the physical mechanisms governing the transmission, propagation, and reception of the information-carrying SPIONs. Moreover, to facilitate system design, we propose a closed-form parametric expression for the end-to-end channel impulse response (CIR). The proposed CIR model is shown to consistently capture the experimentally observed distance-dependent impulse response peak heights and peak decays for transmission distances from 5cm to 40cm. Moreover, to validate our testbed, reliable communication is demonstrated based on experimental data for model-agnostic and model-based detection methods.

cs.ET↗

arXiv2021

Channel Modeling for Synaptic Molecular Communication With Re-uptake and Reversible Receptor Binding

In Diffusive Molecular Communication (DMC), information is transmitted by diffusing molecules. Synaptic signaling is a natural implementation of this paradigm. It is responsible for relaying information from one neuron to another, but also provides support for complex functionalities, such as learning and memory. Many of its features are not yet understood, some are, however, known to be critical for robust, reliable neural communication. In particular, some synapses feature a re-uptake mechanism at the presynaptic neuron, which provides a means for removing neurotransmitters from the synaptic cleft and for recycling them for future reuse. In this paper, we develop a comprehensive channel model for synaptic DMC encompassing a spatial model of the synaptic cleft, molecule re-uptake at the presynaptic neuron, and reversible binding to individual receptors at the postsynaptic neuron. Based on this model, we derive an analytical time domain expression for the channel impulse response (CIR) of the synaptic DMC system. Our model explicitly incorporates macroscopic physical channel parameters and can be used to evaluate the impact of re-uptake, receptor density, and channel width on the CIR of the synaptic DMC system. Furthermore, we provide results from particlebased computer simulation, which validate the analytical model. The proposed comprehensive channel model for synaptic DMC systems can be exploited for the investigation of challenging problems, like the quantification of the inter-symbol interference between successive synaptic signals and the design of synthetic neural communication systems.

q-bio.SC↗

arXiv2020

Synaptic Channel Modeling for DMC: Neurotransmitter Uptake and Spillover in the Tripartite Synapse

In Diffusive Molecular Communication (DMC), information is transmitted by diffusing molecules. Synaptic signaling, as a natural implementation of this paradigm, encompasses functional components that, once understood, can facilitate the development of synthetic DMC systems. To unleash this potential, however, a thorough understanding of the synaptic communication channel based on biophysical principles is needed. Since synaptic transmission critically depends also on non-neural cells, such understanding requires the consideration of the so-called tripartite synapse. In this paper, we develop a comprehensive channel model of the tripartite synapse encompassing a three-dimensional, finite-size spatial model of the synaptic cleft, molecule uptake at the presynaptic neuron and at glial cells, reversible binding to individual receptors at the postsynaptic neuron, and spillover to the extrasynaptic space. Based on this model, we derive analytical time domain expressions for the channel impulse response (CIR) of the synaptic DMC system and for the number of molecules taken up at the presynaptic neuron and at glial cells, respectively. These expressions provide insight into the impact of macroscopic physical channel parameters on the decay rate of the CIR and the reuptake rate, and reveal fundamental limits for synaptic signal transmission induced by chemical reaction kinetics and the channel geometry. Adapted to realistic parameters, our model produces plausible results when compared to experimental and simulation studies and we provide results from particle-based computer simulations to further validate the analytical model. The proposed comprehensive channel model admits a wide range of synaptic configurations making it suitable for the investigation of many practically relevant questions, such as the impact of glial cell uptake and spillover on signal transmission in the tripartite synapse.

q-bio.SC↗

arXiv2020

A Survey of Biological Building Blocks for Synthetic Molecular Communication Systems

Synthetic molecular communication (MC) is a new communication engineering paradigm which is expected to enable revolutionary applications such as smart drug delivery and real-time health monitoring. The design and implementation of synthetic MC systems (MCSs) at nano- and microscale is very challenging. This is particularly true for synthetic MCSs employing biological components as transmitters and receivers or as interfaces with natural biological MCSs. Nevertheless, since such biological components have been optimized by nature over billions of years, using them in synthetic MCSs is highly promising. This paper provides a survey of biological components that can potentially serve as the main building blocks, i.e., transmitter, receiver, and signaling particles, for the design and implementation of synthetic MCSs. Nature uses a large variety of signaling particles of different sizes and with vastly different properties for communication among biological entities. Here, we focus on three important classes of signaling particles: cations (specifically protons and calcium ions), neurotransmitters (specifically acetylcholine, dopamine, and serotonin), and phosphopeptides. For each of these candidate signaling particles, we present several specific transmitter and receiver structures mainly built upon proteins that are capable of performing the distinct physiological functionalities required from the transmitters and receivers of MCSs. Moreover, we present options for both microscale implementation of MCSs as well as the micro-to-macroscale interfaces needed for experimental evaluation of MCSs. Furthermore, we outline new research directions for the implementation and the theoretical design and analysis of the proposed transmitter and receiver architectures.

cs.ET↗

arXiv2019

Diffusive Mobile MC with Absorbing Receivers: Stochastic Analysis and Applications

This paper presents a stochastic analysis of the time-variant channel impulse response (CIR) of a three dimensional diffusive mobile molecular communication (MC) system where the transmitter, the absorbing receiver, and the molecules can freely diffuse. In our analysis, we derive the mean, variance, probability density function (PDF), and cumulative distribution function (CDF) of the CIR. We also derive the PDF and CDF of the probability p that a released molecule is absorbed at the receiver during a given time period. The obtained analytical results are employed for the design of drug delivery and MC systems with imperfect channel state information. For the first application, we exploit the mean and variance of the CIR to optimize a controlled-release drug delivery system employing a mobile drug carrier. We evaluate the performance of the proposed release design based on the PDF and CDF of the CIR. We demonstrate significant savings in the amount of released drugs compared to a constant-release scheme and reveal the necessity of accounting for the drug-carrier's mobility to ensure reliable drug delivery. For the second application, we exploit the PDF of the distance between the mobile transceivers and the CDF of p to optimize three design parameters of an MC system employing on-off keying modulation and threshold detection. Specifically, we optimize the detection threshold at the receiver, the release profile at the transmitter, and the time duration of a bit frame. We show that the proposed optimal designs can significantly improve the system performance in terms of the bit error rate and the efficiency of molecule usage.

cs.IT↗

arXiv2019

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.

cs.ET↗

arXiv2019

Magnetic Nanoparticle Based Molecular Communication in Microfluidic Environments

The possibility to guide and control magnetic nanoparticles in a non-invasive manner has spawned various applications in biotechnology such as targeted drug delivery and sensing of biological substances. These applications are facilitated by the engineering of the size, selective chemical reactivity, and general chemical composition of the employed particles. Motivated by their widespread use and favorable properties, in this paper, we provide a theoretical study of the potential benefits of magnetic nanoparticles for the design of molecular communication systems. In particular, we consider magnetic nanoparticle based communication in a microfluidic channel where an external magnetic field is employed to attract the information-carrying particles to the receiver. We show that the particle transport affected by Brownian motion, fluid flow, and an external magnetic field can be mathematically modeled as diffusion with drift. Thereby, we reveal that the key parameters determining the magnetic force are the particle size and the magnetic field gradient. Moreover, we derive an analytical expression for the channel impulse response, which is used to evaluate the potential gain in the expected number of observed nanoparticles due to the magnetic field. Furthermore, adopting the symbol error rate as performance metric, we show that using magnetic nanoparticles can enable reliable communication in the presence of disruptive fluid flow. Numerical results obtained by particle-based simulation validate the accuracy of the derived analytical expressions.

cs.ET↗

arXiv2018

Channel Modeling for Diffusive Molecular Communication - A Tutorial Review

Molecular communication (MC) is a new communication engineering paradigm where molecules are employed as information carriers. MC systems are expected to enable new revolutionary applications such as sensing of target substances in biotechnology, smart drug delivery in medicine, and monitoring of oil pipelines or chemical reactors in industrial settings. As for any other kind of communication, simple yet sufficiently accurate channel models are needed for the design, analysis, and efficient operation of MC systems. In this paper, we provide a tutorial review on mathematical channel modeling for diffusive MC systems. The considered end-to-end MC channel models incorporate the effects of the release mechanism, the MC environment, and the reception mechanism on the observed information molecules. Thereby, the various existing models for the different components of an MC system are presented under a common framework and the underlying biological, chemical, and physical phenomena are discussed. Deterministic models characterizing the expected number of molecules observed at the receiver and statistical models characterizing the actual number of observed molecules are developed. In addition, we provide channel models for time-varying MC systems with moving transmitters and receivers, which are relevant for advanced applications such as smart drug delivery with mobile nanomachines. For complex scenarios, where simple MC channel models cannot be obtained from first principles, we investigate simulation-driven and experimentally-driven channel models. Finally, we provide a detailed discussion of potential challenges, open research problems, and future directions in channel modeling for diffusive MC systems.

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arXiv2018

Diffusive Mobile MC for Controlled-Release Drug Delivery with Absorbing Receiver

Nanoparticle drug carriers play an important role in facilitating efficient targeted drug delivery, i.e., improving treatment success and reducing drug costs and side effects. However, the mobility of nanoparticle drug carriers poses a challenge in designing drug delivery systems. Moreover, healing results critically depend on the rate and time duration of drug absorption. Therefore, in this paper, we aim to design a controlled-release drug delivery system with a mobile drug carrier that minimizes the total amount of released drugs while ensuring a desired rate of drug absorption during a prescribed time period. We model the mobile drug carrier as a mobile transmitter, the targeted diseased cells as an absorbing receiver, and the channel between the transceivers as a time-variant channel since the carrier mobility results in a time-variant absorption rate of the drug molecules. Based on this, we develop a molecular communication (MC) framework to design the controlled-release drug delivery system. In particular, we develop new analytical expressions for the mean, variance, probability density function, and cumulative distribution function of the channel impulse response (CIR). Equipped with the statistical analysis of the CIR, we design and evaluate the performance of the controlled-release drug delivery system. Numerical results show significant savings in the amount of released drugs compared to a constant-release rate design and reveal the necessity of accounting for drug carrier mobility for reliable drug delivery.

physics.med-ph↗

arXiv2018

Biological Optical-to-Chemical Signal Conversion Interface: A Small-scale Modulator for Molecular Communications

Although many exciting applications of molecular communication (MC) systems are envisioned to be at microscale, the MC testbeds reported so far are mostly at macroscale. To link the macroworld to the microworld, we propose and demonstrate a biological signal conversion interface that can also be seen as a microscale modulator. In particular, the proposed interface transduces an optical signal, which is controlled using an LED, into a chemical signal by changing the pH of the environment. The modulator is realized using E. coli bacteria as microscale entity expressing the light-driven proton pump gloeorhodopsin from Gloeobacter violaceus. Upon inducing external light stimuli, these bacteria locally change their surrounding pH level by exporting protons into the environment. To verify the effectiveness of the proposed optical-to-chemical signal converter, we analyze the pH signal measured by a pH sensor, which serves as receiver. We develop an analytical parametric model for the induced chemical signal as a function of the applied optical signal. Using this model, we derive a training-based channel estimator which estimates the parameters of the proposed model to fit the measurement data. We further derive the optimal maximum likelihood detector and a suboptimal low-complexity detector to recover the transmitted data from the measured received signal. It is shown that the proposed parametric model is in good agreement with the measurement data. Moreover, for an example scenario, we show that the proposed setup is able to successfully convert an optical signal representing a sequence of binary symbols into a chemical signal with a bit rate of 1 bit/minute and recover the transmitted data from the chemical signal using the proposed estimation and detection~schemes. The proposed modulator may form the basis for future MC testbeds and applications at microscale.

cs.ET↗

arXiv2018

Stochastic Channel Modeling for Diffusive Mobile Molecular Communication Systems

In this paper, we develop a mathematical framework for modeling the time-variant stochastic channels of diffusive mobile MC systems. In particular, we consider a diffusive mobile MC system consisting of a pair of transmitter and receiver nano-machines suspended in a fluid medium with a uniform bulk flow, where we assume that either the transmitter, or the receiver, or both are mobile and we model the mobility by Brownian motion. The transmitter and receiver nano-machines exchange information via diffusive signaling molecules. Due to the random movements of the transmitter and receiver nano-machines, the statistics of the channel impulse response (CIR) change over time. We derive closed-form expressions for the mean, the autocorrelation function (ACF), the cumulative distribution function (CDF), and the probability density function (PDF) of the time-variant CIR. Exploiting the ACF, we define the coherence time of the time-variant MC channel as a metric for characterization of the variations of the CIR. The derived CDF is employed for calculation of the outage probability of the system. We also show that under certain conditions, the PDF of the CIR can be accurately approximated by a Log-normal distribution. Based on this approximation, we derive a simple model for outdated channel state information (CSI). Moreover, we derive an analytical expression for evaluation of the expected error probability of a simple detector for the considered MC system. In order to investigate the impact of CIR decorrelation over time, we compare the performances of a detector with perfect CSI knowledge and a detector with outdated CSI knowledge. The accuracy of the proposed analytical expressions is verified via particle-based simulation of the Brownian motion.

cs.IT↗

arXiv2018

Early Cancer Detection in Blood Vessels Using Mobile Nanosensors

In this paper, we propose using mobile nanosensors (MNSs) for early stage anomaly detection. For concreteness, we focus on the detection of cancer cells located in a particular region of a blood vessel. These cancer cells produce and emit special molecules, so-called biomarkers, which are symptomatic for the presence of anomaly, into the cardiovascular system. Detection of cancer biomarkers with conventional blood tests is difficult in the early stages of a cancer due to the very low concentration of the biomarkers in the samples taken. However, close to the cancer cells, the concentration of the cancer biomarkers is high. Hence, detection is possible if a sensor with the ability to detect these biomarkers is placed in the vicinity of the cancer cells. Therefore, in this paper, we study the use of MNSs that are injected at a suitable injection site and can move through the blood vessels of the cardiovascular system, which potentially contain cancer cells. These MNSs can be activated by the biomarkers close to the cancer cells, where the biomarker concentration is sufficiently high. Eventually, the MNSs are collected by a fusion center (FC) where their activation levels are read and exploited to declare the presence of anomaly. We analytically derive the biomarker concentration as well as the probability mass function of the MNSs' activation levels and validate the obtained results via particle-based simulations. Then, we derive the optimal decision rule for the FC regarding the presence of anomaly assuming that the entire network is known at the FC. Finally, for the FC, we propose a simple sum detector that does not require knowledge of the network topology. Our simulations reveal that while the optimal detector achieves a higher performance than the sum detector, both proposed detectors significantly outperform a benchmark scheme that used fixed nanosensors at the FC.

q-bio.TO↗

arXiv2018

Advanced Target Detection via Molecular Communication

In this paper, we consider target detection in suspicious tissue via diffusive molecular communications (MCs). If a target is present, it continuously and with a constant rate secretes molecules of a specific type, so-called biomarkers, into the medium, which are symptomatic for the presence of the target. Detection of these biomarkers is challenging since due to the diffusion and degradation, the biomarkers are only detectable in the vicinity of the target. In addition, the exact location of the target within the tissue is not known. In this paper, we propose to distribute several reactive nanosensors (NSs) across the tissue such that at least some of them are expected to come in contact with biomarkers, which cause them to become activated. Upon activation, an NS releases a certain number of molecules of a secondary type into the medium to alert a fusion center (FC), where the final decision regarding the presence of the target is made. In particular, we consider a composite hypothesis testing framework where it is assumed that the location of the target and the biomarker secretion rate are unknown, whereas the locations of the NSs are known. We derive the uniformly most powerful (UMP) test for the detection at the NSs. For the final decision at the FC, we show that the UMP test does not exist. Hence, we derive a genie-aided detector as an upper bound on performance. We then propose two sub-optimal detectors and evaluate their performance via simulations

cs.ET↗

arXiv2018

Biological Optical-to-Chemical Signal Conversion Interface: A Small-scale Modulator for Molecular Communications

Although many exciting applications of molecular communication (MC) systems are envisioned to be at microscale, the available MC testbeds reported in the literature so far are mostly at macroscale. This may partially be due to the fact that controlling an MC system at microscale is quite challenging. To link the macroworld to the microworld, we propose a biological signal conversion interface that can also be seen as a microscale modulator. This interface translates an optical signal, which can be easily controlled using a light-emitting diode (LED), into a chemical signal by changing the pH of the environment. The modulator is realized using \textit{Escherichia coli} bacteria that express the light-driven proton pump gloeorhodopsin from \textit{Gloeobacter violaceus}. Upon inducing external light stimuli, these bacteria can locally change their surrounding pH level by exporting protons into the environment. Based on measurement data from a testbed, we develop an analytical model for the induced chemical signal as a function of the applied optical signal. Finally, using a pH sensor as detector, we show for an example scenario that the proposed setup is able to successfully convert an optical signal representing a sequence of binary symbols into a chemical signal with a bit rate of $1$~bit/min.

cs.ET↗

arXiv2018

Experimental Molecular Communication Testbed Based on Magnetic Nanoparticles in Duct Flow

Simple and easy to implement testbeds are needed to further advance molecular communication research. To this end, this paper presents an in-vessel molecular communication testbed using magnetic nanoparticles dispersed in an aqueous suspension as they are also used for drug targeting in biotechnology. The transmitter is realized by an electronic pump for injection via a Y-connector. A second pump provides a background flow for signal propagation. For signal reception, we employ a susceptometer, an electronic device including a coil, where the magnetic particles move through and generate an electrical signal. We present experimental results for the transmission of a binary sequence and the system response following a single injection. For this flow-driven particle transport, we propose a simple parameterized mathematical model for evaluating the system response.

cs.ET↗

arXiv2017

Molecular Communication using Magnetic Nanoparticles

In this paper, we propose to use magnetic nanoparticles as information carriers for molecular communication. This enables the use of an external magnetic field to guide information-carrying particles towards the receiver. We show that the particle movement can be mathematically modeled as diffusion with drift. Thereby, we reveal that the key parameters determining the magnetic force are particle size and magnetic field gradient. As an example, we consider magnetic nanoparticle based communication in a bounded two-dimensional environment. For this model, we derive an analytical expression for the channel impulse response subject to fluid flow and magnetic drift. Furthermore, adopting the symbol error rate as performance metric, we show that using magnetic nanoparticles facilitates reliable communication, even in the presence of fluid flow.

cs.ET↗

arXiv2017

Symbol Synchronization for Diffusion-Based Molecular Communications

Symbol synchronization refers to the estimation of the start of a symbol interval and is needed for reliable detection. In this paper, we develop several symbol synchronization schemes for molecular communication (MC) systems where we consider some practical challenges which have not been addressed in the literature yet. In particular, we take into account that in MC systems, the transmitter may not be equipped with an internal clock and may not be able to emit molecules with a fixed release frequency. Such restrictions hold for practical nanotransmitters, e.g. modified cells, where the lengths of the symbol intervals may vary due to the inherent randomness in the availability of food and energy for molecule generation, the process for molecule production, and the release process. To address this issue, we develop two synchronization-detection frameworks which both employ two types of molecule. In the first framework, one type of molecule is used for symbol synchronization and the other one is used for data detection, whereas in the second framework, both types of molecule are used for joint symbol synchronization and data detection. For both frameworks, we first derive the optimal maximum likelihood (ML) symbol synchronization schemes as performance upper bounds. Since ML synchronization entails high complexity, for each framework, we also propose three low-complexity suboptimal schemes, namely a linear filter-based scheme, a peak observation-based scheme, and a threshold-trigger scheme which are suitable for MC systems with limited computational capabilities. Furthermore, we study the relative complexity and the constraints associated with the proposed schemes and the impact of the insertion and deletion errors that arise due to imperfect synchronization.

cs.IT↗

arXiv2017

SCW Codes for Maximum Likelihood Detection in Diffusive Molecular Communications without Channel State Information

Instantaneous or statistical channel state information (CSI) is needed for most detection schemes developed for molecular communication (MC) systems. Since the MC channel changes over time, e.g., due to variations in the velocity of flow, the temperature, or the distance between transmitter and receiver, CSI acquisition has to be conducted repeatedly to keep track of CSI variations. Frequent CSI acquisition may entail a large overhead whereas infrequent CSI acquisition may result in a low CSI estimation accuracy. To overcome these challenges, we design codes which enable maximum likelihood sequence detection at the receiver without instantaneous or statistical CSI. In particular, assuming concentration shift keying modulation, we show that a class of codes, referred to as strongly constant-weight (SCW) codes, enables optimal CSI-free sequence detection at the expense of a decrease in data rate. For the proposed SCW codes, we analyze the code rate, the error rate, and the average number of released molecules. In addition, we study the properties of binary SCW codes and balanced SCW codes in further detail. Simulation results verify our analytical derivations and reveal that SCW codes with CSI-free detection outperform uncoded transmission with optimal coherent and non-coherent detection.

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