Technical Program Committee
IEEE Global Communications Conference (GLOBCOM'2015,2016)
IEEE International Conference on Communications (ICC'2015)
International Conference on Bio-inspired Information and Communications Technologies (BICT'2015,2016)
Nariman Farsad is a Postdoctoral Research Scholar with the Department of Electrical Engineering at Stanford University. He is a member of Wireless Systems Laboratory, and works under the supervision of Professor Andrea Goldsmith. His research interests are in bio-inspired communication networks, communication and network engineering, machine learning, information theory, signal processing, and bioengineering. He focuses on questions such as: How very tiny devices communicate, form networks, and cooperate. How chemical signaling can be used in smart cities, medicine, biotechnology, and oil and gas industries to form efficient networks.
Media Coverage
My new experimental platform that uses household chemicals as carries of information has been covered by Stanford News.
Conference Presentation at Asilomar
I will present our paper "On the Capacity of Diffusion-Based Molecular Timing Channels with Diversity" at Asilomar Conference on Signals, Systems, and Computers.
Conference Presentation at ACM NANOCOM
Vahid Jamali presented our paper "Non-Coherent Multiple-Symbol Detection for Diffusive Molecular Communications" at ACM International Conference on Nanoscale Computing and Communication (NanoCom).
Conference Presentation at ACM NANOCOM
Yonathan Morin presented our paper "On Time-Slotted Communication over Molecular Timing Channels" at ACM International Conference on Nanoscale Computing and Communication (NanoCom).
News Coverage by IEEE Spectrum
The MIMO molecular communication platform we designed and built is covered by IEEE Spectrum.
Conference Presentation at ISIT
I presented our paper "On the Capacity of Diffusion-Based Molecular Timing Channels" at IEEE International Symposium on Information Theory (ISIT).
Conference Presentation at SPAWC
I presented our paper "A Molecular Communication System Using Acids, Bases and Hydrogen Ions" at IEEE International workshop on Signal Processing advances in Wireless Communications (SPAWC).
Invited Talk at University of British Columbia
I gave a talk titled "Molecular Communication: Theoretical Limits and Experimental Implementations" at University of British Columbia hosted by Victor Leung.
Invited Conference Talk at BSC
I gave a talk titled "Capacity Limits of Diffusion-Based Molecular Timing Channels" at the Canadian Biennial Symposium on Communications (BSC).
Conference Presentation at ICC
Birkan Yilmaz presented our paper titled "Energy Model for Vesicle-Based Active Transport Molecular Communication" at IEEE International Conference on Communications (ICC).
Invited Talk at Georgia Institute of Technology
I gave a talk titled "Molecular Communication: Theoretical Limits and Experimental Implementations" at Georgia Institute of Technology hosted by Faramaz Fekri.
Invited Talk at Carnegie Mellon University
I gave a talk titled "Molecular Communication: Theoretical Limits and Experimental Implementations" at Carnegie Mellon University hosted by Pulkit Grover.
Invited Talk at Boston University
I gave a talk titled "Molecular Communication: Theoretical Limits and Experimental Implementations" at Boston University hosted by Bobak Nazer.
Invited Talk at Massachusetts Institute of Technology
I gave a talk titled "Molecular Communication: Theoretical Limits and Experimental Implementations" at Massachusetts Institute of Technology hosted by Muriel Médard.
Invited Talk organized by IEEE Toronto Section at University of Toronto
I gave a talk titled "Molecular Communication: Theoretical Limits and Experimental Implementations" organized by IEEE Toronto Section at University of Toronto.
Invited Talk at Princton University
I gave a titled "Molecular Communication: Theoretical Limits and Experimental Implementations" at Princton University hosted by Vincent Poor.
Invited Workshop Presentation at ITA
I presented our work on "Capacity Limits of Molecular Timing Channels" at Information Theory and Applications (ITA) Workshop.
Journal Submission to IEEE T-IT
I submitted our paper "Capacity Limits of Diffusion-Based Molecular Timing Channels" to IEEE Transactions on Information Theory.
Conference Presentation at GLOBECOM
I presented our paper "Stable Distributions as Noise Models for Molecular Communication" at IEEE Global Communication Conference (GLOBCOM).
Invited Workshop Presentation at University of Southern California
I presented my work on "Molecular Communication using Acids and Bases" at USC's Communications, Inference, And Computing In Molecular And Biological Systems Workshop.
This work introduces capacity limits for molecular timing (MT) channels, where information is modulated on the release timing of small information particles, and decoded from the time of arrival at the receiver. It is shown that the random time of arrival can be represented as an additive noise channel, and for the diffusion-based MT (DBMT) channel this noise is distributed according to the Levy distribution. Lower and upper bounds on capacity of the DBMT channel are derived for the case where the delay associated with the propagation of information particles in the channel is finite. These bounds are also shown to be tight. Moreover, it is shown that by simultaneously releasing multiple particles the capacity linearly increases with the number of particles. This is analogous to receive diversity as each particle takes a random independent path, and can be used to increase data rate significantly since in molecular communication systems, it is possible to release many particles simultaneously.
The performance of communication systems is fundamentally limited by the loss of energy through propagation and circuit inefficiencies. The emergence of Internet of Nano Things ecosystem means there is need to design and build nanoscale energy efficient communication subsystems. In this article, we show that it is possible to achieve ultra low energy communications at the nanoscale, if diffusive molecules are used for carrying data. While the energy of electromagnetic waves will inevitably decays as a function of transmission distance and time, the energy in individual molecules does not. Over time, the receiver has an opportunity to recover some, if not all of the molecular energy transmitted. The article demonstrates the potential of ultra-low energy simultaneous molecular information and energy transfer (SMIET) through the design of two different nano-relay systems. It also discusses the benefits of crowd energy harvesting compared to traditional wave-based systems.
In molecular communication, information is conveyed through chemical messages. With much advancement in the field of nanotechnology, bioengineering and synthetic biology over the past decade, micro- and nano-scales devices are becoming a reality. Yet the problem of engineering a reliable communication system between tiny devices is still an open problem. At the same time, despite the prevalence of radio communication, there are still areas where traditional electromagnetic waves find it difficult or expensive to reach. Points of interest in industry, cities, medical, and military applications often lie in embedded and entrenched areas, accessible only by ventricles at scales too small for conventional radio- and micro-waves, or they are located in such a way that directional high frequency systems are ineffective. Molecular communication is a biologically inspired communication scheme that could be employed for solving these problems. Although biologists have studied molecular communication, it is poorly understood from a telecommunication perspective. In this paper, we highlight the recent advancements in the field of molecular communication engineering.
This article examines recent research in molecular communications from a telecommunications system design perspective. In particular, it focuses on channel models and state-of-the-art physical layer techniques. The goal is to provide a foundation for higher layer research and motivation for research and development of functional prototypes. In the first part of the article, we focus on the channel and noise model, comparing molecular and radio-wave pathloss formulae. In the second part, the article examines, equipped with the appropriate channel knowledge, the design of appropriate modulation and error correction coding schemes. The third reviews transmitter and receiver side signal processing methods that suppress inter-symbol-interference. Taken together, the three parts present a series of physical layer techniques that are necessary to producing reliable and practical molecular communications.
In diffusion-based molecular communications, the channel is governed by diffusion through a fluid medium, which leads to extremely low data rates compared to the radio frequency communication system. To mitigate this problem, we propose a novel design for molecular communication that utilizes multiple bulges (in RF communication this corresponds to antenna) at both the transmitter and molecular detectors at the receiver. We simulate the system with a one-shot signal to obtain the channel's finite impulse response. We then incorporate this result within our mathematical analysis to determine inter-link interference (ILI) and inter-symbol interference (ISI). Low complexity symbol detection methods are needed for the cases of incomplete information regarding the system and the channel state, since the receiver is supposed to be a small and simple node. Thus we propose four detection algorithms, namely adaptive thresholding, practical zero forcing with channel models excluding/including the ILI and ISI, and Genie-aided zero forcing. We verify the proposed system via extensive numerical/analytical evaluations and a novel macro-scale testbed.
Molecular communications (MC) has been studied as a bio-inspired information carrier for micro-scale and nanoscale environments. On the macro-scale, it can also be considered as an alternative to electromagnetic (EM) wave based systems, especially in environments where there is significant attenuation to EM wave power. This paper goes beyond the unbounded free space propagation to examine three macro-scale environments: the pipe, the knife edge, and the mesh channel. Approximate analytical expressions shown in this paper demonstrate that MC has an advantage over EM wave communications when: (i) the EM frequency is below the cut-off frequency for the pipe channel, (ii) the EM wavelength is considerably larger than the mesh period, and (iii) when the receiver is in the high diffraction loss region of an obstacle.
Lab-on-chip devices and point-of-care diagnostic chip devices are composed of many different components, such as nanosensors that must be able to communicate with other components within the device. Molecular communication is a promising solution for on-chip communication. In particular, kinesin driven microtubule motility is an effective means of transferring information particles from one component to another. However, finding an optimal shape for these channels can be challenging. In this paper, we derive a mathematical optimization model that can be used to find the optimal channel shape and dimensions for any transmission period. We derive three specific models for the rectangular channels, regular polygonal channels, and regular polygonal ring channels. We show that the optimal channel shapes are the square-shaped channel for the rectangular channel, and circular-shaped channel for the other classes of shapes. Finally, we show that among all 2-D shapes the optimal design choice that maximizes information rate is the circular-shaped channel.
Recently, a tabletop molecular communication platform has been developed for transmitting short text messages across a room. The end-to-end system impulse response for this platform does not follow previously published theoretical works because of imperfect receiver, transmitter, and turbulent flows. Moreover, it is observed that this platform resembles a nonlinear system, which makes the rich body of theoretical work that has been developed by communication engineers not applicable to this platform. In this work, we first introduce corrections to the previous theoretical models of the end-to-end system impulse response based on the observed data from experimentation. Using the corrected impulse response models, we then formulate the nonlinearity of the system as noise and show that through simplifying assumptions it can be represented as Gaussian noise. Through formulating the system's nonlinearity as the output a linear system corrupted by noise, the rich toolbox of mathematical models of communication systems, most of which are based on linearity assumption, can be applied to this platform.
In molecular communication, small particles such as molecules are used to convey information. These particles are released by a transmitter into a fluidic environment, where they propagate freely (e.g. through diffusion) or through externals means (e.g. different types of active transport) until they arrive at the receiver. Although there are a number of different mathematical models for the diffusion-based molecular communication, active transport molecular communication (ATMC) lacks the necessary theoretical framework. Previous works had to rely almost entirely on full Monte Carlo simulations of these systems. However, full simulations can be time consuming because of the computational complexities involved. In this paper, a Markov channel model has been presented, which could be used to reduce the amount of simulations necessary for studying ATMC without sacrificing accuracy. Moreover, a mathematical formula for calculating the transition probabilities in the Markov chain model is derived to complete our analytical framework. Comparing our proposed models with full simulations, it is shown that these models can be used to calculate parameters such channel capacity accurately in a timely manner.
The need to convey information has always existed in both the animal and human kingdoms. The article offers a review of the latest developments in transporting information using nanosized particles. The article begins by examining the usage of chemical signalling in nature, and goes on to discuss the recent advances in mimicking this in bio-inspired engineering. The article then distinguishes the important difference between signalling and general communications, and explains why the latter is a more challenging problem. The article then goes on to examine existing research on mimicking chemical signalling in nature, which is a precurser to research in general chemical communications. A review of the latest theoretical research in general chemical communications is presented, along with the practical developments of the world’s first nanoparticle communications test-bed. In the end, the authors discuss the potential research challenges and name three important areas for future development: robustness, miniaturization, and scalability.
In this work, we describe the first modular, and programmable platform capable of transmitting a text message using chemical signalling – a method also known as molecular communication. This form of communication is attractive for applications where conventional wireless systems perform poorly, from nanotechnology to urban health monitoring. Using examples, we demonstrate the use of our platform as a testbed for molecular communication, and illustrate the features of these communication systems using experiments. By providing a simple and inexpensive means of performing experiments, our system fills an important gap in the molecular communication literature, where much current work is done in simulation with simplified system models. A key finding in this paper is that these systems are often nonlinear in practice, whereas current simulations and analysis often assume that the system is linear. However, as we show in this work, despite the nonlinearity, reliable communication is still possible. Furthermore, this work motivates future studies on more realistic modelling, analysis, and design of theoretical models and algorithms for these systems.
We consider a confined space molecular communication system, where molecules or information carrying particles are used to transfer information on a microfluidic chip. Considering that information-carrying particles can follow two main propagation schemes: passive transport, and active transport, it is not clear which achieves a better information transmission rate. Motivated by this problem, we compare and analyze both propagation schemes by deriving a set of analytical and mathematical tools to measure the achievable information rates of the on-chip molecular communication systems employing passive to active transport. We also use this toolbox to optimize design parameters such as the shape of the transmission area, to increase the information rate. Furthermore, the effect of separation distance between the transmitter and the receiver on information rate is examined under both propagation schemes, and a guidepost to design an optimal molecular communication setup and protocol is presented.
In this letter, resource allocation is considered for large multi-source, multi-relay networks employing fractional cooperation, in which each potential relay only allocates a fraction of its resources to relaying. Using a Gaussian approximation, it is shown that the optimization can be posed as a linear program, where the relays use a demodulate-and-forward (DemF) strategy, and where the transmissions are protected by low-density parity-check (LDPC) codes. This is useful since existing optimization schemes for this problem are nonconvex.
This paper will provide a guidepost to design an optimal molecular communication setup and protocol. A barrier to the design of vesicle-based molecular communication nanonetworks is the computational complexity of simulating them. In this paper, a computationally efficient transport model is presented, which could be employed to design active transport molecular communication systems, particularly to optimize the shape of the transmission zone. Furthermore, a vesicular encapsulation model is presented as an addition to the transport model, and it is shown that there exists an optimal vesicle size for each molecular communication channel. As an application, our transport model is used to estimate the channel capacity of a molecular communication nanonetwork in a computationally efficient manner compared to traditional Monte Carlo techniques. Moreover, it is shown that the derived optimal vesicle size maximizes channel capacity.
This work studies modulation techniques for molecular timing (MT) channels. Three different modulation techniques are proposed: 1) Modulating information on the release timing of information particles, 2) Modulating information on the time between two consecutive releases of {\em indistinguishable} information particles, and 3) Modulating information on the time between two consecutive releases of {\em distinguishable} information particles. While the first modulation scheme requires transmitter-receiver synchronization, the latter two are asynchronous. We show that for all three modulation techniques the channel can be represented as an additive noise channel, where for diffusion-based MT (DBMT) channels the noise follows a stable distribution with characteristic exponent $1/2$. For DBMT channels, we provide expressions for the probability density function of the additive noise in terms of the Voigt functions, which can be numerically calculated efficiently. Next, we focus on the binary communication and derive the optimal detection rules for each modulation. To compare the performance of the different modulations, we first derive an expression for the geometric power of almost all stable distributions, and then use this results to obtain the geometric SNR (G-SNR) for each modulation scheme. Numerical evaluations indicate that the bit error rate is constant for a given G-SNR. Moreover, it is shown that synchronized communication in DBMT channels provides a significant performance gain. Yet, by using two {\em distinguishable} particles per bit instead of one, the probability of error using asynchronous communication in the third modulation technique can approach the probability of error obtained in synchronized communication of the first modulation scheme.
In diffusive molecular communication (MC), the channel state information (CSI) is defined as the probability that a molecule released by the transmitter is observed at the receiver as well as the expected number of the interfering molecules observed at the receiver. Most of the available works on MC assume that the CSI is perfectly known at the receiver for data detection, e.g., to determine the detection threshold. In contrast, in this paper, we study non-coherent detection schemes which do not require knowledge of the CSI. In particular, we first derive the optimal maximum likelihood (ML) multiple-symbol (MS) detector and the decision-feedback (DF) detector. As a special case of the optimal MS detector, we show that the optimal ML symbol-by-symbol (SS) detector can be equivalently written in the form of a threshold-based detector where the optimal threshold is constant and depends only on the statistics of the MC channel. Having stated that the complexity of the DF detector is lower than that of the optimal MS detector, the main challenge of both of these detectors is the complexity associated with the calculation of the their detection metrics. To cope with this issue, we propose approximated MS and DF detection metrics as well as a suboptimal blind detector with a complexity of much lower than the MS and DF detectors. Finally, we derive analytical expressions for the bit error rate (BER) of the optimal SS detector, and an upper bound and a lower bound for the BER of the optimal MS detector. Simulation results confirm our analyses and reveal the effectiveness of the proposed optimal and suboptimal detection schemes with respect to a baseline scheme which assumes perfect CSI knowledge, particularly when the number of observations used for detection is sufficiently large.
This work studies optimal detection for communication over diffusion-based molecular timing (DBMT) channels. The transmitter simultaneously releases multiple small information particles, where the information is encoded in the time of release. The receiver decodes the transmitted information based on the random time of arrival of the information particles, which is represented as an additive noise channel. For a diffusion-based MT channel, without flow, this noise follows the L ́evy distribution. Under this channel model, the maximum-likelihood (ML) detector is derived and shown to have high computational complexity. It is further shown that for any additive channel with α-stable noise, α < 1, such as the DBMT channel, a linear receiver is not able to take advantage of the release of multiple information particles. Thus, instead of the common low complexity linear approach, a new detector, which is based on the first arrival (FA) among all the transmitted particles, is derived. It is shown that for small number of released particles the performance of the FA detector is very close to that of the ML detector. On the other hand, via error exponent analysis, it is shown that the performance of the two detectors differ when the number of released particles is large. Thus, in the regime of small to medium number of sent particles, the FA detector is an attractive alternative to the relatively complicated ML detector.
This work studies the impact of time-synchronization in molecular timing (MT) channels by analyzing three different modulation techniques. The first requires transmitter-receiver synchronization and is based on modulating information on the release timing of information particles. The other two are asynchronous and are based on modulating information on the relative time between two consecutive releases of information particles using indistinguishable or distinguishable particles. All modulation schemes result in a system that relate the transmitted and the received signals through an additive noise, which follows a stable distribution. As the common notion of the variance of a signal is not suitable for defining the power of stable distributed signals (due to infinite variance), we derive an expression for the geometric power of a large class of stable distributions, and then use this result to characterize the geometric signal-to-noise ratio (G-SNR) for each of the modulation techniques. In addition, for binary communication, we derive the optimal detection rules for each modulation technique. Numerical evaluations indicate that the bit error rate (BER) is constant for a given G-SNR, and the performance gain obtained by using synchronized communication is significant. Yet, it is also shown that by using two distinguishable particles per bit instead of one, the BER of the asynchronous technique can approach that of the synchronous one.
This work studies communication over diffusion- based molecular timing (DBMT) channels. The transmitter si- multaneously releases multiple small information particles, where the information is encoded in the time of release. The receiver decodes the transmitted information based on the random time of arrival of the information particles, which is represented as an additive noise channel. For a DBMT channel, without flow, this noise follows the Lévy distribution. Under this channel model, the maximum-likelihood (ML) detector is derived and shown to have high computational complexity. It is further shown that for any additive noise channel with α-stable noise, α < 1, such as the DBMT channel, a linear receiver is not able to take advantage of the release of multiple information particles. Thus, instead of the common low complexity linear approach, a new detector, which is based on the first arrival (FA) among all the transmitted particles, is derived. Numerical simulations indicate that for a small to medium number of released particles, the performance of the FA detector is very close to the performance of the ML detector.
This work introduces bounds on the capacity of molecular timing (MT) channels, where information is modulated on the release timing of multiple indistinguishable information particles, and decoded from the times of arrival at the receiver. It is shown that for diffusion-based MT channels, the capacity scales linearly in the number of particles. This is analogous to receiver diversity as each particle takes a random independent path. However, unlike receiver diversity in wireless channels, which mitigates fading, this form of diversity in MT channels can be used to significantly increase data rate.
Most of the available works on molecular communication (MC) assume that the channel state information (CSI) is perfectly known at the receiver for data detection. In contrast, in this paper, we study non-coherent multiple-symbol detection schemes which do not require knowledge of the CSI. In particular, we derive the optimal maximum likelihood (ML) multiple-symbol (MLMS) detector. Moreover, we propose an approximated detection metric and a sub-optimal detector to cope with the high complexity of the optimal MLMS detector. Numerical results reveal the effectiveness of the proposed optimal and suboptimal detection schemes with respect to a baseline scheme which assumes perfect CSI knowledge, particularly when the number of observations used for detection is sufficiently large.
This work studies time-slotted communication over molecular timing (MT) channels. The transmitter, assumed to be perfectly synchronized in time with the receiver, releases a single information particle in each time slot, where the information is encoded in the time of release. The receiver decodes the transmitted information based on the random time of arrivals of the information particles during a finite-time reception window. The maximum-likelihood (ML) detector is derived and shown to have an exponential computational complexity, thus, rendering it impractical. In addition, two practical detectors are presented: The first is a symbol-by-symbol detector. The second is a sequence detector which is based on the Viterbi algorithm (VA), yet, the VA is used differently than in its common application in ML detection where information is transmitted over linear channels with memory. Numerical simulations indicate that the proposed sequence detection algorithm significantly improves the performance compared to the symbol-by-symbol detector. Furthermore, for a short number of transmitted symbols it closely approaches the highly complicated ML detector.
This work introduces capacity limits for molecular timing (MT) channels, where information is modulated on the release timing of small information particles, and decoded from the time of arrival at the receiver. It is shown that the random time of arrival can be represented as an additive noise channel, and for the diffusion-based MT (DBMT) channel this noise is distributed according to the Levy distribution. Lower and upper bounds on capacity of the DBMT channel are derived for the case where the delay associated with the propagation of information particles in the channel is finite. These bounds are also shown to be tight.
Concentration modulation, whereby information is encoded in the concentration level of chemicals, is considered. One of the main challenges with such systems is the limited control the transmitter has on the concentration level at the receiver. For example, concentration cannot be directly decreased by the transmitter, and the decrease in concentration over time occurs solely due to transport mechanisms such as diffusion. This can result in inter-symbol interference (ISI), which degrades performance. In this work, a novel scheme is proposed that uses the transmission of acids, bases, and the concentration of hydrogen ions for carrying information. By employing this technique, the concentration of hydrogen ions at the receiver can be both increased and decreased through the sender's transmissions. This enables ISI mitigation as well as the ability to form a wider array of signal patterns at the receiver.
In active transport molecular communication (ATMC), information particles are actively transported from a transmitter to a receiver using special proteins. Prior work has demonstrated that ATMC can be an attractive and viable solution for on-chip applications. The energy consumption of an ATMC system plays a central role in its design and engineering. In this work, an energy model is presented for ATMC and the model is used to provide guidelines for designing energy efficient systems. The channel capacity per unit energy is analyzed and maximized. It is shown that based on the size of the symbol set and the symbol duration, there is a vesicle size that maximizes rate per unit energy. It is also demonstrated that maximizing rate per unit energy yields very different system parameters compared to maximizing the rate only.
In this work, we consider diffusion-based molecular communication timing channels. Three different timing channels are presented based on three different modulation techniques, i.e., i) modulation of the release timing of the information particles, ii) modulation on the time between two consecutive information particles of the same type, and iii) modulation on the time between two consecutive information particles of different types. We show that each channel can be represented as an additive noise channel, where the noise follows one of the subclasses of stable distributions. We provide expressions for the probability density function of the noise terms, and numerical evaluations for the probability density function and cumulative density function. We also show that the tails are longer than Gaussian distribution, as expected.
In molecular communication information is transferred with the use of molecules. Molecular multiple-input multiple- output (MIMO) system with drift (positive velocity) at macro- scale will be presented and the improvement against single- input single-output (SISO) molecular communication systems will be verified via our testbed. Until now it was unclear whether MIMO techniques, which are extensively used in modern radio frequency (RF) communications, could be applied to molecular communication. In the demonstration, using our MIMO testbed we will show that we can achieve nearly 1.7 times higher data rate than SISO molecular communication systems. Moreover, signal-to-inter-link-interfeence metric for one-shot signal will be depicted for a given symbol duration.
In molecular communication information is conveyed through chemical signals. In this work, we have considered a novel communication scheme where information is encoded in chemical barcodes, through use of persistent chemical tags. We have assumed that this information is already encoded in the environment, and we have devised a robotic platform for reading the chemical tag. We have performed many experiments to find the optimal encoding scheme and an algorithm for reading and decoding the chemically tagged information. We have demonstrated that chemical tags can be decoded using simple algorithms and inexpensive, off-the-shelf sensors. Finally, we have evaluated and presented the bit error rate performance of our devised algorithm.
Wave-based signals have been successful in reliably and efficiently transferring data between two or more well defined points (e.g., known location area). However, it is challenged when the transmitter is hidden and the receivers are absent. Essentially, the transmitter and the receivers have no location knowledge of each other. We demonstrate that unlike wave-based transmissions, the total molecular energy doesn't monotonically degrade as a function of time. This paper uses a bio-inspired method of communicating data from a hidden transmitter to a group of absent receivers. A specialized molecular communication system is designed, including how to embed vital location information in the structure of a heterogeneous biochemical molecule. Like message in a bottle, there is a growing probability of receiving the location message over a period of several years. The only caveat is that there is an initial delay of a few hours to days, depending on the proximity of the rescue team to the crash site. This will provide an attractive alternative to current wave-based communications for delay-tolerant crash recovery.
In this paper, we propose an end-to-end channel model for molecular communication systems with metal-oxide sensors. In particular, we focus on the recently developed table top molecular communication platform. The system is separated into two parts: the propagation and the sensor detection. There is derived, based on this, a more realistic end-to-end channel model. However, since some of the coefficients in the derived models are unknown, we collect a great deal of experimental data to estimate these coefficients and evaluate how they change with respect to the different system parameters. Finally, a noise model is derived for the system to complete an end-to-end system model for the tabletop platform.
In this demonstration, we will present the world's first molecular multiple-input multiple-output (MIMO) communication link to deliver two data streams in a spatial domain. We show that chemical signals such as concentration gradients could be used in MIMO fashion to transfer sequential data. Until now it was unclear whether MIMO techniques, which are used extensively in modern radio communication, could be applied to molecular communication. In the demonstration, using our devised MIMO apparatus and carefully designed detection algorithm, we will show that we can achieve about 1.7 times higher data rate than single input single output (SISO) molecular communication systems.
In this paper, we propose a realistic channel model for a table-top molecular communication platform that is capable for transmitting short text messages across a room. The observed system response for this experimental platform does not match the theoretical results in the literature. This is because many simplifying assumptions regarding the flow, the sensor, and environmental conditions, which were used in derivations of previous theoretical models do not hold in practice. Therefore, in this paper, based on experimental observations, theoretical models are modified to create more realistic channel models.
In this paper, we consider a molecular diffusion based communications link that can reliably transport data over-the-air. We show that the system can also reliably transport data across confined structural environments, especially in cases where conventional electromagnetic (EM) wave based systems may fail. In particular, this paper compares the performance of our proprietary molecular communication test-bed with Zigbee wireless sensors in a metal pipe network that does not act as a radio wave-guide. The paper first shows that a molecular-based communication link's performance is determined primarily by the delay time spread of the pulse response. The paper go on to show that molecular-based systems can transmit more reliably in complex and confined structural environments than conventional EM-based systems. The paper then utilizes empirical data to find relationships between the received radio signal strength, the molecular pulse spread, data rate (0.1 bits/s) and the structural propagation environment.
This demonstration will present the world's first macroscale molecular communication link to reliably transmit a continuous data stream. The system modulates alcohol molecules, which are then diffused via ambient and induced air currents to carry information to a receiver. The communication distance is several meters and the propagation channel we will demonstrate consists of both free space and tunnel environments. The goal is to show that molecules can be used as an alternative to electromagnetic (EM) waves in challenging environments where EM waves do not perform well.
One of the most prominent forms of information transmission between nano- or micro-scale devices is molecular communication, where molecules are used to transfer information inside a fluidic channel. The effects of channel shape on achievable information transmission rates is considered in this work. Specifically, regular convex polygons are studied. A mathematical framework for finding the optimal channel among this class of geometric shapes is derived. Using this framework it is shown that the optimal channel tends to be circular. This result is verified using computer simulations.
In this paper, a mathematical optimization formula for estimating the optimal channel dimensions of active transport molecular communication is presented. More specifically, rectangular channels with constant microtubule (MT) concentration are considered. It is shown, both using our formula and using Monte Carlo simulations, that square-shaped channels are optimal. Furthermore, when the value of time per channel use is on the order of a few minutes, which is the range of interest for a lot of potential applications such as diagnostic chips for healthcare, it is shown that our optimization formula can quickly and accurately estimate the optimal channel dimensions.
Fractional cooperation is a decentralized, low-complexity wireless networking protocol in which nodes have the ability to dynamically select a fraction of its resources to commit to forwarding, and where sources may use more than one relay to convey information to the destination. In this paper, an implementation and a series of experiments are presented to demonstrate the practical performance and effectiveness of fractional cooperation. A low-complexity MAC layer protocol is used, which employs fractional cooperation using LT codes in the absence of central coordination. Experimental results from real-world trials are given, which show that this protocol can maintain a reasonable throughput when nodes are abruptly entering and leaving, making it ideal for a dynamically changing system, such as an ad-hoc network. The redundancy of information seen in the network makes this scheme robust to unfavourable channel conditions.
In molecular communication, gaps in the underlying theoretical and mathematical framework create numerous challenges. Currently, most researchers rely on simulations to study these systems. However, simulations can be time consuming and impractical. Moreover, due to the complexity and dependencies present in these systems, deriving a mathematical framework that can capture the essence of molecular communication systems is also challenging. In this work, we derive a simple mathematical model, based on some independence assumptions, to estimate the information rate of a molecular communication system employing active transport propagation. We show that the presented model estimates the simulated information rate closely for small communication time intervals. We also use the derived mathematical model to design and verify an optimal loading area that would maximize the information rate.
In molecular communication, information is encoded and transmitted as a pattern of molecules or other very small information carriers (in this paper, vesicles are used). Nanoscale techniques, such as molecular motors or Brownian motion, are used to convey the vesicles from the transmitter to the receiver, where the transmitted message is deciphered. In this paper, the microchannel environment is considered, and the achievable information rates are compared between the use of Brownian motion and molecular motors, which are evaluated through simulation. Communication is viewed as a mass transfer problem, where messages are sent by transporting a number of vesicles from transmitter to receiver. Results are provided which suggest that active transport is best when the available number of vesicles is small, and Brownian motion is best when the number of vesicles is large.
In a cooperative wireless network, there may be many potential relays within radio range of a source; similarly, there may be many potential sources seeking to use relays. Allocating these resources is a non-trivial optimization problem. In this paper, fractional cooperation is considered, where each potential relay only allocates a fraction of its resources to relaying. It is shown that linear programming can be used to optimally allocate resources in multi-source, multi-relay net- works, where the relays use a demodulate-and-forward (DemF) strategy, and where the transmissions are protected by low-density parity-check (LDPC) codes. Compared with existing optimization schemes, this method is particularly suitable for very large networks with numerous sources and relays. Simulation results are presented to demonstrate the performance of this scheme.
Wireless sensor networks, which consist of numerous devices that take measurements of a physical phenomenon, are commonly used to observe phenomena that are correlated in space. In this paper, we devise a low-complexity coding scheme for correlated sources based on Slepian-Wolf compression, and analyze its performance in terms of diversity order. The main idea of this scheme is to use the correlated measurements as a substitute for relay links. Although we show that the asymptotic diversity order is limited by the constant correlation factor, we give experimental results that show excellent performance over practical ranges of SNR.
In this paper, a mathematical optimization formula for estimating the optimal channel dimensions of active transport molecular communication is presented. More specifically, rectangular channels with constant microtubule (MT) concentration are considered. It is shown, both using our formula and using Monte Carlo simulations, that square-shaped channels are optimal. Furthermore, when the value of time per channel use is on the order of a few minutes, which is the range of interest for a lot of potential applications such as diagnostic chips for healthcare, it is shown that our optimization formula can quickly and accurately estimate the optimal channel dimensions.
Molecular communication is a promising technique for microchannel systems. In this paper, various microchannel molecular communication schemes are simulated and analyzed using information theory, including molecular motors and Brownian motion with drift. Results suggest Brownian motion with drift can deliver excellent performance, depending on the drift velocity.
My research is currently focused on how bio-inspired forms of communication, such as use of chemical signals or exchange of molecules could be used to create networks in environments that are harsh to radio propagation. This technique, which is called molecular communication in the literature (this is a good introduction) has attracted a lot of attention in recent years. This new multidisciplinary field can be used for in-body communication, robotics, secrecy, networking microscale and nanoscale devices, infrastructure monitoring in smart cities and industrial complexes, as well as for underwater communications. Therefore, molecular communication, as a technology, can have a disruptive effect by unlocking many futuristic applications much like Guglielmo Marconi’s pioneering work in radio that laid the foundation for modern telecommunications and the wealth of applications it supports.
Much of my past and current research has been focused on studying, designing, and building point-to-point molecular communication links at both macroscales and microscales, and improving the performance of these links. Specifically, my current research spans evaluating the theoretical limits of molecular communications, system design, analysis, and optimization, as well as building experimental platforms. I use tools and models from several disciplines including communication and network engineering, machine learning, information theory, signal processing, optimization, chemistry, biology, bioengineering, and medical sciences. I also design and build experimental systems to support, validate, and complement my theoretical work (e.g., world's first experimental demonstrator for molecular communication). Below, I highlight some of the applications of molecular communication at microscales and macroscales, which I strive to explore, and why molecular communication is central to these applications.
At microscale, I am solving the communication problem among tiny devices (smaller than a few micrometers). Engineering radio-based communication networks at these scales can be very challenging, since 1) we need to use higher frequencies to have small antennas that fit inside the small device; and 2) High frequency radio does not propagate very well in ionic fluids (e.g. inside human body). Nevertheless, there are research group that are trying to adapt the radio technology to these small dimensions using novel materials such as carbon nanotube or graphene. However to date, there have not been any practical demonstrations of feasibility of this approach. On the other hand, molecular communication is already used in nature to solve this problem and it can be biocompatible, which would make it very suitable for many potential applications, especially in medicine.
Why is this important? Engineering micro- and nano-scale systems are the key to unlocking many futuristic applications such as nanomedicine, microrobotics, nanorobotics, lab-on-a-chip devices, diagnostic chip devices, targeted drug delivery and biological Computation. Most of these futuristic and transformative applications have one feature in common: they involve not just single devices working independently, but swarms of devices working in concert.
At macroscale, chemical signals open a new mode of communication (e.g., using chemical tags) for connecting devices such as robots. Although molecular communication cannot outperform radio-based communication in terms of delay and throughput, there are environments that are harsh to electromagnatic waves. For example, inside networks of tunnels or pipes as we show here. However, chemical communication can be used instead to transfer small amounts of data with a delay in these situations.
Why is this important? One of the requirements of smart cities is infrastructure monitoring. However, there are a number of challenges for radio-based solutions that needs to be overcome (for example see here). Chemical communication can be used in conjunction with radio based systems to overcome some of these challenges. Another area that chemical communication can prove useful is inside pipelines, where applications of interest would be in different industries such as oil and gas. Finally, employing chemical communication can add a new and exciting dimension to the way robots and devices in general communicate.
MITS5200G: Advanced Communication Networks (Graduate Level Course)
University of Ontario Institute of Technology, Oshawa, Canada
Course offered by the Departments of Electrical Engineering/Computer Sciece/Information Technology
INFR3710U: Signals and Random Processes (Third Year Undergraduate Course)
University of Ontario Institute of Technology, Oshawa, Canada
Department of Business and Information Technology
INFR3710U: Signals and Random Processes (Third Year Undergraduate Course)
University of Ontario Institute of Technology, Oshawa, Canada
Department of Business and Information Technology
I have served as a teaching assistant for various courses in electrical engineering and computer science, almost every fall and winter throughout my Masters and Ph.D. Most courses that I have been assigned have had dedicated lab sessions as well, where I was the lab instructor. Typically, the number of students in the lab ranged from 10 to 30 students, where they designed and implemented software and hardware solutions to a set of problems and projects. The following are the list of courses:
IEEE Global Communications Conference (GLOBCOM'2015,2016)
IEEE International Conference on Communications (ICC'2015)
International Conference on Bio-inspired Information and Communications Technologies (BICT'2015,2016)
P1906.1 - Recommended Practice for Nanoscale and Molecular Communication Framework
EEE Journal of Selected Areas of Communication (JSAC) - Special Issue on Emerging Technologies in Communications
IEEE Transactions on Molecular, Biological, and Multi-Scale Communications
IEEE Journal of Selected Areas of Communication (JSAC) - Special Issue on Molecular, Biological, and Multi-Scale Communications
IEEE Transactions on Information Theory
IEEE Transactions on Signal Processing
IEEE Transactions on Communications
IEEE Transactions on NanoBioscience
IEEE Transactions on Nanotechnology
IEEE Wireless Communications Letters
My newest experimental platform uses acids and bases for communication and is 10 times faster than any of my previous platforms.
The world's first molecular communication system, capable of transferring short text messages with alcohol.
A MIMO implementation of this work demonstrates improvment in data rate.
Some of my work has been covered by these media outlets. Click the logos to go to the corresponding site. I recommend the article by the ChemistryWorld.
I am always interested in discussing research opportunities, assisting research enthusiasts, and collaborating on new projects. Feel free to contact me at nfarsad@stanford.edu or meet me in my office:
350 Serra Mall
Packard Building, Room 372
Stanford, CA 94305