Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
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Article Citation - WoS: 4Citation - Scopus: 4Mobile human ad hoc networks: A communication engineering viewpoint on interhuman airborne pathogen transmission(Elsevier, 2022) Güleç, Fatih; Atakan, Barış; Dressler, FalkoA number of transmission models for airborne pathogens transmission, as required to understand airborne infectious diseases such as COVID-19, have been proposed independently from each other, at different scales, and by researchers from various disciplines. We propose a communication engineering approach that blends different disciplines such as epidemiology, biology, medicine, and fluid dynamics. The aim is to present a unified framework using communication engineering, and to highlight future research directions for modeling the spread of infectious diseases through airborne transmission. We introduce the concept of mobile human ad hoc networks (MoHANETs), which exploits the similarity of airborne transmission-driven human groups with mobile ad hoc networks and uses molecular communication as the enabling paradigm. In the MoHANET architecture, a layered structure is employed where the infectious human emitting pathogen-laden droplets and the exposed human to these droplets are considered as the transmitter and receiver, respectively. Our proof-of-concept results, which we validated using empirical COVID-19 data, clearly demonstrate the ability of our MoHANET architecture to predict the dynamics of infectious diseases by considering the propagation of pathogen-laden droplets, their reception and mobility of humans.Editorial Guest Editorial for Signal Processing Aspects of Molecular Communications(Elsevier, 2022) Atakan, Barış; Galmés, Sebastià; Haselmayr, Werner; Farsad, Nariman; Nakano, TadashiMolecular communication is the most widespread communication mechanism on the Earth since it is fundamental for all living entities from unicellular organisms to multicellular animals and plants to maintain their vital functionalities. For example, many unicellular organisms sense and react to molecular signals from their surroundings to control their life cycles. Some signaling molecules called pheromone are also extensively employed by a variety of insects to send and receive information to coordinate colony activities. Moreover, in the neuronal system, signaling molecules known as neurotransmitters are used in junction points of neuron cells to carry out many mental activities. In addition to the various molecular communication mechanisms in nature, the recent advances in nano- and biotechnology have shown that molecular communication is one of the most favorable choices to enable the interconnection of nanomachines such as engineered cells and bionanorobots. The network of such nanomachines, i.e., nanonetwork, is considered to make frontier biomedical applications a reality. In these applications, molecular communication can enable the nanomachines to share information so as to provide reliability and controllability. Furthermore, this can also allow different nanomachine populations to be coordinated to reach highly sophisticated behavior and increase the number of design possibilities.Article Citation - WoS: 3Citation - Scopus: 5Event Distortion-Based Clustering Algorithm for Energy Harvesting Wireless Sensor Networks(Springer, 2021) Al-Qamaji, Ali; Atakan, BarışWireless sensor networks (WSNs) consist of compact deployed sensor nodes which collectively report their sensed readings about an event to the Base Station (BS). In WSNs, due to the dense deployment, sensor readings can be spatially correlated and it is nonessential to transmit all their readings to the BS. Therefore, for more energy efficient, it is vital to choose which sensor node should report their sensed readings to the BS. In this paper, the event distortion-based clustering (EDC) algorithm is proposed for the spatially correlated sensor nodes. Here, the sensor nodes are assumed to harvest energy from ambient electromagnetic radiation source. The EDC algorithm allows the energy-harvesting sensor nodes to select and eliminate nonessential nodes while maintain an acceptable level of distortion at the BS. To measure the reliability, a theoretical framework of the distortion function is first derived for both single-hop and two-hop communication scenarios. Then, based on the derived theoretical framework, the EDC algorithm is introduced. Through extensive simulations, the performance of the EDC algorithm is evaluated in terms of achievable distortion level, number of alive nodes and harvested energy levels. As a result, EDC algorithm can successfully exploit both the spatial correlation and energy harvesting to improve the energy efficiency while preserving an acceptable level of distortion. Furthermore, the performance comparisons reveal that the two-hop communication model outperforms the single-hop model in terms of the distortion and energy-efficiency.Article Citation - WoS: 12Citation - Scopus: 14A Molecular Communication Perspective on Airborne Pathogen Transmission and Reception Via Droplets Generated by Coughing and Sneezing(IEEE, 2021) Güleç, Fatih; Atakan, BarışInfectious diseases spread via pathogens such as viruses and bacteria. Airborne pathogen transmission via droplets is an important mode for infectious diseases. In this paper, the spreading mechanism of infectious diseases by airborne pathogen transmission between two humans is modeled with a molecular communication perspective. An end-to-end system model which considers the pathogen-laden cough/sneeze droplets as the input and the infection state of the human as the output is proposed. This model uses the gravity, initial velocity and buoyancy for the propagation of droplets and a receiver model which considers the central part of the human face as the reception interface is proposed. Furthermore, the probability of infection for an uninfected human is derived by modeling the number of propagating droplets as a random process. The numerical results reveal that exposure time affects the probability of infection. In addition, the social distance for a horizontal cough should be at least 1.7 m and the safe coughing angle of a coughing human to infect less people should be less than -25 degrees.Article Citation - WoS: 7Citation - Scopus: 9Fluid dynamics-based distance estimation algorithm for macroscale molecular communication(Elsevier, 2021) Güleç, Fatih; Atakan, BarışMany species, from single-cell bacteria to advanced animals, use molecular communication (MC) to share information with each other via chemical signals. Although MC is mostly studied in microscale, new practical applications emerge in macroscale. It is essential to derive an estimation method for channel parameters such as distance for practical macroscale MC systems which include a sprayer emitting molecules as a transmitter (TX) and a sensor as the receiver (RX). Due to the similarity between sneezing/coughing and spraying mechanisms, these practical systems have the potential to be applied in modeling airborne pathogen (viruses, bacteria, etc.) transmission with a MC perspective where an infected human emitting pathogen-laden droplets is considered as a TX. In this paper, a novel approach based on fluid dynamics is proposed for the derivation of the distance estimation in practical MC systems. According to this approach, transmitted molecules are considered as moving and evaporating droplets in the MC channel. With this approach, the Fluid Dynamics-based Distance Estimation (FDDE) algorithm which predicts the propagation distance of the transmitted droplets by updating the diameter of evaporating droplets at each time step is proposed. FDDE algorithm is validated by experimental data. The results reveal that the distance can be estimated by the fluid dynamics approach which introduces novel parameters such as the volume fraction of droplets in a mixture of air and liquid droplets and the beamwidth of the TX. Furthermore, the effect of the evaporation is shown with the numerical results. (C) 2021 Elsevier B.V. All rights reserved.Article Citation - WoS: 14Citation - Scopus: 15A Droplet-Based Signal Reconstruction Approach To Channel Modeling in Molecular Communication(Institute of Electrical and Electronics Engineers Inc., 2021) Güleç, Fatih; Atakan, BarışIn this paper, a novel droplet-based signal reconstruction (SR) approach to channel modeling, which considers liquid droplets as information carriers instead of molecules in the molecular communication (MC) channel, is proposed for practical sprayer-based macroscale MC systems. These practical MC systems are significant, since they can be used in order to investigate airborne pathogen transmission with biological sensors due to the similar mechanisms of sneezing/coughing and sprayer. Our proposed approach takes a two-phase flow which is generated by the interaction of droplets in liquid phase with air molecules in gas phase into account. Two-phase flow is combined with the SR of the receiver (RX) to propose a channel model. The SR part of the model quantifies how the accuracy of the sensed molecular signal in its reception volume depends on the sensitivity response of the RX and the adhesion/detachment process of droplets. The proposed channel model is validated by employing experimental data. IEEEConference Object Citation - Scopus: 8Localization of a Passive Molecular Transmitter With a Sensor Network(Springer, 2020) Güleç, Fatih; Atakan, BarışMacroscale molecular communication (MC), which has a potential for practical applications, is a promising area for communication engineering. In a practical scenario such as monitoring air pollutants released from an unknown source, it is essential to estimate the location of the molecular transmitter (TX). This paper presents a novel Sensor Network-based Localization Algorithm (SNCLA) for passive transmission by using a novel experimental platform which mainly comprises a clustered sensor network (SN) with 24 sensor nodes and evaporating ethanol molecules as the passive TX. With the usage of the SN concept, novel methods can be developed for the problems in macroscale MC by utilizing the wide literature of sensor networks. In SNCLA, Gaussian plume model is employed to derive the location estimator. The parameters such as transmitted mass, wind velocity, detection time and actual concentration are calculated or estimated from the measured signals via the SN to be employed as the input for the location estimator. The numerical results show that the performance of SNCLA is better for stronger winds in the medium. Our findings show that evaporated molecules do not propagate homogeneously through the SN due to the presence of the wind. In addition, the estimation error of SNCLA decreases for higher detection threshold values. © 2020, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.Book Citation - Scopus: 37Molecular Communications and Nanonetworks: From Nature To Practical Systems(Springer, 2014) Atakan, BarışThis book will introduce the concept of molecular communications and nanonetworks. The publication addresses why nanoscale communication is needed for the sophisticated nano and biotechnology applications. The text introduces the frontier applications of the molecular communication and nanonetworks. The book examines the molecular communication types called active, passive, and gap junction molecular communications. The author presents the molecular transmitter, receiver, encoding and decoding mechanisms used in these systems. Discussing the molecular communication system model and looking at the unique characteristics of practical molecular communication systems and these chemical reactions and their effects on the communication performance. Finally, the book examines the point-to-point, broadcast, and multiple-access molecular channel and shows two promising application examples of the nanonetworks. The first application example is the body area nanonetworks used in nanomedicine. the second nanonetwork application example, i.e., NanoSensor Networks (NSNs) with Molecular Communication. © Springer Science+Business Media New York 2014.Article Citation - WoS: 5Citation - Scopus: 7Signal Reconstruction in Diffusion-Based Molecular Communication(Wiley, 2019) Atakan, Barış; Güleç, FatihMolecular communication (MC) is an important nanoscale communication paradigm, which is employed for the interconnection of the nanomachines (NMs) to form nanonetworks. A transmitter NM (TN) sends the information symbols by emitting molecules into the transmission medium and a receiver NM (RN) receives the information symbols by sensing the molecule concentration. In this paper, a model of how an RN measures and reconstructs the molecular signal is proposed. The signal around the RN is assumed to be a Gaussian random process instead of the less realistic deterministic approach. After the reconstructed signal is derived as a doubly stochastic poisson process, the distortion between the signal around the RN and the reconstructed signal is derived as a new performance parameter in MC systems. The derived distortion, which is a function of system parameters such as RN radius, sampling period, and the diffusion coefficient of the channel, is shown to be valid by employing random walk simulations. Then, it is shown that the original signal can be satisfactorily reconstructed with a sufficiently low level of distortion. Finally, optimum RN design parameters, namely, RN radius, sampling period, and sampling frequency, are derived by minimizing the signal distortion. The simulation results reveal that there is a trade-off among the RN design parameters which can be jointly set for a desired signal distortion.Article Citation - WoS: 21Citation - Scopus: 25Distance Estimation Methods for a Practical Macroscale Molecular Communication System(Elsevier, 2020) Güleç, Fatih; Atakan, BarışAccurate estimation of the distance between the transmitter (TX) and the receiver (RX) in molecular communication (MC) systems can provide faster and more reliable communication. In addition, distance information can be used in determining the location of the molecular source in practical applications such as monitoring environmental pollution. Existing theoretical models in the literature are not suitable for distance estimation in a practical scenario. Furthermore, deriving an analytical model is a nontrivial problem, since the liquid in the TX is sprayed as droplets rather than molecules, these droplets move according to Newtonian mechanics, the size of the droplets change during their propagation and droplet-air interaction causes unsteady flows. Therefore, five different practical methods comprising three novel data analysis based methods and two supervised machine learning (ML) methods, Multivariate Linear Regression (MLR) and Neural Network Regression (NNR), are proposed for distance estimation at the RX side. In order to apply the ML methods, a macroscale practical MC system, which consists of an electric sprayer without a fan, alcohol molecules, an alcohol sensor and a microcontroller, is established, and the received signals are recorded. A feature extraction algorithm is proposed to utilize the measured signals as the inputs in ML methods. The numerical results show that the ML methods outperform the data analysis based methods in the root mean square error sense with the cost of complexity. The nearly equal performance of MLR and NNR shows that the input features such as peak time, peak concentration and the energy of the received signal have a highly linear relation with the distance. Moreover, the peak time based estimation, which is one of the proposed data analysis based methods, yields better results with respect to the other proposed four methods, as the distance increases. Given the experimental data and fluid dynamics theory, a possible trajectory of the molecules between the TX and RX is given. Our findings show that distance estimation performance is jointly affected by unsteady flows and the non-linearity of the sensor. According to our findings based on fluid dynamics, it is evaluated that fluid dynamics should be taken into account for more accurate parameter estimation in practical macroscale MC systems. (C) 2020 Elsevier B.V. All rights reserved.