Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/11
Browse
9 results
Search Results
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: 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. IEEEArticle 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.Conference Object Citation - WoS: 4Citation - Scopus: 3On Exploiting Spatial Correlation for Energy Harvesting Wireless Sensor Networks(Institute of Electrical and Electronics Engineers Inc., 2017) Al-Qamaji, Ali; Atakan, BarışWireless Sensor Network (WSN) is a set of inexpensive densely deployed sensor nodes with limited functionalities and scarcity in energies. The observations of sensors are forwarded directly to the Base Station (BS). In densely deployed sensors, sensing data are likely to be highly correlated in space domain, which produces unfavorable redundant readings and wasting in energy. In this paper, we propose an Event Distortion-Based Node Selection (EDNS) algorithm which exploits spatial correlation for reducing inessential sensor nodes that have correlated readings for improving Energy-Efficiency (EE) with acceptable distortion level. Furthermore, we derive a theoretical framework of distortion function for single-hop communication model to observe the advantages from energy harvesting to the accuracy level. Furthermore, the trade-off between energy consumption and distortion level is investigated.Article Citation - WoS: 6Citation - Scopus: 10Performance Analysis of Diffusion-Based Molecular Communications With Memory(Institute of Electrical and Electronics Engineers Inc., 2016) Galmes, Sebastia; Atakan, BarışIn this paper, the comprehensive delay and performance analyses of the $M$-ary molecular communications with memory are presented. By taking into account any level of channel memory, the type-based and concentration-based modulation schemes are introduced and analyzed. In the type-based modulation, information symbols are encoded through different molecule types. In the concentration-based modulation, various concentration levels of one molecule type are used to encode information symbols. For both modulation schemes, the delay distributions of the molecular symbols are derived, and then, the symbol error probabilities are developed. The given distributions and the error probability expressions are validated through extensive simulation experiments. After showing that the derived expressions are valid, the performance of the modulation schemes is evaluated. The performance evaluations reveal that by properly selecting the parameters such as slot time and number of emitted molecules, the performance can be improved in both type and concentration-based molecular communication as the channel memory is increased. Furthermore, it is shown that the type-based molecular communication outperforms the concentration-based molecular communication.Article Citation - WoS: 3Citation - Scopus: 4On Exploiting Sampling Jitter in Vehicular Sensor Networks(Institute of Electrical and Electronics Engineers Inc., 2014) Atakan, BarışVehicular sensor networks (VSNs) are composed of vehicular sensor nodes that collaboratively sample, communicate, and reconstruct the event signal at the sink node. Samples of event signals are subjected to jitter based on the propagation speed of signal and locations of vehicular sensors. In this paper, a theoretical analysis is presented to understand the effects and how to exploit the jitter in the sensed event signal for energy-efficient and reliable communication in VSNs. Results reveal that sampling jitter can be advantageous and can be exploited in developing adaptive communication techniques, which can provide significant energy conservation while maintaining reliability in VSNs.Article Citation - WoS: 19Citation - Scopus: 24Optimal Transmission Probability in Binary Molecular Communication(Institute of Electrical and Electronics Engineers Inc., 2013) Atakan, BarışMolecular communication (MC) is a promising nanoscale communication paradigm that enables nanomachines to share information by using messenger mo\-le\-cu\-les. In this paper, an expression for the achievable rate in MC is first given. Then, using this expression, an optimal transmission probability is developed to maximize the MC rate. Numerical results show that the MC rate is time-dependent and the molecules freely wandering in the medium negatively affect the MC performance. However, the proposed optimal transmission probability is shown to maximize the MC rate.