arXiv subjects

Ozgur B. Akan

Publications and source records attributed to Ozgur B. Akan.

At least 91 records · Page 5Linked to original sources

arXiv2024

Modelling 1D Partially Absorbing Boundaries for Brownian Molecular Communication Channels

Molecular Communication (MC) architectures suffer from molecular build-up in the channel if they do not have appropriate reuptake mechanisms. The molecular build-up either leads to intersymbol interference (ISI) or reduces the transmission rate. To measure the molecular build-up, we derive analytic expressions for the incidence rate and absorption rate for one-dimensional MC channels where molecular dispersion obeys the Brownian Motion. We verify each of our key results with Monte Carlo simulations. Our results contribute to the development of more complicated models and analytic expressions to measure the molecular build-up and the impact of ISI in MC.

q-bio.MN↗

arXiv2024

Odor Perceptual Shift Keying (OPSK) for Odor-Based Molecular Communication

Molecular communication (MC) has promising potential and a wide range of applications. However, odor-based communication which is common in nature, has not been sufficiently examined within the context of MC, yet. In this paper, we introduce a novel approach for implementing odor-based MC systems. We propose a new modulation scheme called Odor Perceptual Shift Keying (OPSK), which encodes information by shifting the perceptual values of odor molecules in pleasantness, intensity and edibility dimensions. We construct a system which transmits OPSK modulated signals between a transmitter and receiver. We conduct analyses on the system parameters to simulate performance metrics such as symbol error rate (SER) and symbol rate (SR). Our analyses indicate that OPSK has a potential for realizing odor-based MC systems. We find that under certain conditions, reliable odor-based MC systems can be implemented using OPSK across a variety of distance ranges from millimeters up to kilometers. Additionally, we introduce adaptive symbol transmission to our system for input symbol sequences featuring symbols that occur with unequal probabilities. We further demonstrate that the proposed algorithm at the transmitter side can achieve extended operation times.

cs.ET↗

arXiv2024

3D Receiver for Molecular Communications in Internet of Organoids

Organoids have garnered attention due to their effectiveness in modeling the 3D structure of organ interactions. However, the communication engineering perspective has received relatively little attention. One way to achieve organoids communication is molecular communication (MC). Molecular communication is a bio-inspired communication paradigm that uses molecules as information carriers. It is considered one of the most promising methods for enabling the Internet of Nano-Things (IoNT) and nanonetworks. BioFETs are commonly used to implement practical MC receivers. However, most previous analyses have focused on a planar device, neglecting considerations like the threshold voltage and its potential 3D structure. This paper introduces the first FinFET-based MC receiver that covers both the top and side gates with receptors. Both binding noise and flicker noise are considered in the analysis. The performance, in terms of signal-to-noise ratio (SNR) and symbol error probability (SEP), is compared with that of the 2D receiver.

cs.ET↗

arXiv2023

What Really is `Molecule' in Molecular Communications? The Quest for Physics of Particle-based Information Carriers

Molecular communication, as implied by its name, uses molecules as information carriers for communication between objects. It has an advantage over traditional electromagnetic-wave-based communication in that molecule-based systems could be biocompatible, operable in challenging environments, and energetically undemanding. Consequently, they are envisioned to have a broad range of applications, such as in the Internet of Bio-nano Things, targeted drug delivery, and agricultural monitoring. Despite the rapid development of the field, with an increasing number of theoretical models and experimental testbeds established by researchers, a fundamental aspect of the field has often been sidelined, namely, the nature of the molecule in molecular communication. The potential information molecules could exhibit a wide range of properties, making them require drastically different treatments when being modeled and experimented upon. Therefore, in this paper, we delve into the intricacies of commonly used information molecules, examining their fundamental physical characteristics, associated communication systems, and potential applications in a more realistic manner, focusing on the influence of their own properties. Through this comprehensive survey, we aim to offer a novel yet essential perspective on molecular communication, thereby bridging the current gap between theoretical research and real-world applications.

eess.SP↗

arXiv2023

Odor Intensity Shift Keying (OISK) and Channel Capacity of Odor-based Molecular Communications in Internet of Everything

Molecular communication is a new, active area of research that has created a paradigm shift in the way a communication system is perceived. An artificial molecular communication network is created using biological molecules for encoding, transmitting and decoding the symbols to convey information. In addition to typical biological molecules, we are also exploring other classes of molecules that possess unique distinctive features which can be potentially exploited for establishing reliable communications. Odor molecules are one such class of molecules which possess several distinctive features such as Intensity, Headonic tone which provides a basis to convey the information in an olfactory communication system. In our work, we investigate the ICT (information and communication theory) perspective of the olfactory communications by evaluating the channel capacity of an odor molecular communication (OMC) system with the help of a novel modulation scheme viz. odor intensity shift keying (OISK), where information is being conveyed from the intensity level of an odor. Furthermore, we also analyse the effects of critical parameters like temperature and noise on the achievable channel capacity to provide an insight about the resilience of the proposed OMC system towards any such anomaly faced by it.

cs.ET↗

arXiv2023

Data-Agnostic Model Poisoning against Federated Learning: A Graph Autoencoder Approach

This paper proposes a novel, data-agnostic, model poisoning attack on Federated Learning (FL), by designing a new adversarial graph autoencoder (GAE)-based framework. The attack requires no knowledge of FL training data and achieves both effectiveness and undetectability. By listening to the benign local models and the global model, the attacker extracts the graph structural correlations among the benign local models and the training data features substantiating the models. The attacker then adversarially regenerates the graph structural correlations while maximizing the FL training loss, and subsequently generates malicious local models using the adversarial graph structure and the training data features of the benign ones. A new algorithm is designed to iteratively train the malicious local models using GAE and sub-gradient descent. The convergence of FL under attack is rigorously proved, with a considerably large optimality gap. Experiments show that the FL accuracy drops gradually under the proposed attack and existing defense mechanisms fail to detect it. The attack can give rise to an infection across all benign devices, making it a serious threat to FL.

cs.LG↗

arXiv2023

Received Signal and Channel Parameter Estimation in Molecular Communications

Molecular communication (MC) is a paradigm that employs molecules as information transmitters, hence, requiring unconventional transceivers and detection techniques for the Internet of Bio-Nano Things (IoBNT). In this study, we provide a novel MC model that incorporates a spherical transmitter and receiver with partial absorption. This model offers a more realistic representation than receiver architectures in literature, e.g. passive or entirely absorbing configurations. An optimization-based technique utilizing particle swarm optimization (PSO) is employed to accurately estimate the cumulative number of molecules received. This technique yields nearly constant correction parameters and demonstrates a significant improvement of 5 times in terms of root mean square error (RMSE). The estimated channel model provides an approximate analytical impulse response; hence, it is used for estimating channel parameters such as distance, diffusion coefficient, or a combination of both. We apply iterative maximum likelihood estimation (MLE) for the parameter estimation, which gives consistent errors compared to the estimated Cramer-Rao Lower Bound (CLRB).

cs.NI↗

arXiv2023

Frequency-Domain Detection for Molecular Communication with Cross-Reactive Receptors

Molecular Communications (MC) is a bio-inspired communication paradigm that uses molecules as information carriers, requiring unconventional transceivers and modulation/detection techniques. Practical MC receivers (MC-Rxs) can be implemented using field-effect transistor biosensor (bioFET) architectures, where surface receptors reversibly react with ligands. The time-varying concentration of ligand-bound receptors is translated into electrical signals via field effect, which is used to decode the transmitted information. However, ligand-receptor interactions do not provide an ideal molecular selectivity, as similar ligand types, i.e., interferers, co-existing in the MC channel, can interact with the same type of receptors. Overcoming this molecular cross-talk in the time domain can be challenging, especially when Rx has no knowledge of the interferer statistics or operates near saturation. Therefore, we propose a frequency-domain detection (FDD) technique for bioFET-based MC-Rxs that exploits the difference in binding reaction rates of different ligand types reflected in the power spectrum of the ligand-receptor binding noise. We derive the bit error probability (BEP) of the FDD technique and demonstrate its effectiveness in decoding transmitted concentration signals under stochastic molecular interference compared to a widely used time-domain detection (TDD) technique. We then verified the analytical performance bounds of the FDD through a particle-based spatial stochastic simulator simulating reactions on the MC-Rx in microfluidic channels.

eess.SP↗

arXiv2023

Graphene and Related Materials for the Internet of Bio-Nano Things

Internet of Bio-Nano Things (IoBNT) is a transformative communication framework, characterized by heterogeneous networks comprising both biological entities and artificial micro/nano-scale devices, so-called Bio-Nano Things (BNTs), interfaced with conventional communication networks for enabling innovative biomedical and environmental applications. Realizing the potential of IoBNT requires the development of new and unconventional communication technologies, such as molecular communications, as well as the corresponding transceivers, bio-cyber interfacing technologies connecting the biochemical domain of IoBNT to the electromagnetic domain of conventional networks, and miniaturized energy harvesting and storage components for the continuous power supply to BNTs. Graphene and related materials (GRMs) exhibit exceptional electrical, optical, biochemical, and mechanical properties, rendering them ideal candidates for addressing the challenges posed by IoBNT. This perspective article highlights recent advancements in GRM-based device technologies that are promising for implementing the core components of IoBNT. By identifying the unique opportunities afforded by GRMs and aligning them with the practical challenges associated with IoBNT, particularly in the materials domain, our aim is to accelerate the transition of envisaged IoBNT applications from theoretical concepts to practical implementations, while also uncovering new application areas for GRMs.

cs.ET↗

arXiv2023

Frequency-Domain Detection for Molecular Communications

Molecular Communications (MC) is a bio-inspired communication paradigm which uses molecules as information carriers, thereby requiring unconventional transmitter/receiver architectures and modulation/detection techniques. Practical MC receivers (MC-Rxs) can be implemented based on field-effect transistor biosensor (bioFET) architectures, where surface receptors reversibly react with ligands, whose concentration encodes the information. The time-varying concentration of ligand-bound receptors is then translated into electrical signals via field-effect, which is used to decode the transmitted information. However, ligand-receptor interactions do not provide an ideal molecular selectivity, as similar types of ligands, i.e., interferers, co-existing in the MC channel can interact with the same type of receptors, resulting in cross-talk. Overcoming this molecular cross-talk with time-domain samples of the Rx's electrical output is not always attainable, especially when Rx has no knowledge of the interferer statistics or it operates near saturation. In this study, we propose a frequency-domain detection (FDD) technique for bioFET-based MC-Rxs, which exploits the difference in binding reaction rates of different types of ligands, reflected to the noise spectrum of the ligand-receptor binding fluctuations. We analytically derive the bit error probability (BEP) of the FDD technique, and demonstrate its effectiveness in decoding transmitted concentration signals under stochastic molecular interference, in comparison to a widely-used time-domain detection (TDD) technique. The proposed FDD method can be applied to any biosensor-based MC-Rxs, which employ receptor molecules as the channel-Rx interface.

eess.SP↗

arXiv2022

Energy-Efficient Transmission Range and Duration for Cognitive Radio Sensor Networks

Cognitive Radio (CR) promises an efficient utilization of radio spectrum resources by enabling dynamic spectrum access to overcome the spectrum scarcity problem. Cognitive Radio Sensor Networks (CRSNs) are one type of Wireless Sensor Networks (WSNs) equipped with CR capabilities. CRSN nodes need to operate energy-efficiently to extend network lifetime due to their limited battery capacity. In this paper, for the first time in literature, we formulate the problem of finding a common energy-efficient transmission range and transmission duration for all CRSN nodes and network deployment that would minimize the energy consumed per goodput per meter toward the sink in a greedy forwarding scenario. Results reveal non-trivial relations for energy-efficient CRSN transmission range and duration as a function of nine critical network parameters such as primary user activity levels. These relations provide valuable insights for detailed CRSN designs prior to deployment.

cs.NI↗

arXiv2021

Terahertz Wireless Communications in Space

The New Space Era has increased communication traffic in space by new space missions led by public space agencies and private companies. Mars colonization is also targeted by crewed missions in the near future. Due to increasing space traffic near Earth and Mars, the bandwidth is getting congested. Moreover, the downlink performance of the current missions is not satisfactory in terms of delay and data rate. Therefore, to meet the increasing demand in space links, Terahertz band (0.1-10 THz) wireless communications are proposed in this study. In line with this, we discuss the major challenges that the realization of THz band space links pose and possible solutions. Moreover, we simulate Mars-space THz links for the case of a clear Mars atmosphere, and a heavy dust storm to show that even in the worst conditions, a large bandwidth is available for Mars communication traffic.

cs.ET↗

arXiv2021

Universal Transceivers: Opportunities and Future Directions for the Internet of Everything (IoE)

The Internet of Everything (IoE) is a recently introduced information and communication technology (ICT) framework promising for extending the human connectivity to the entire universe, which itself can be regarded as a natural IoE, an interconnected network of everything we perceive. The countless number of opportunities that can be enabled by IoE through a blend of heterogeneous ICT technologies across different scales and environments and a seamless interface with the natural IoE impose several fundamental challenges, such as interoperability, ubiquitous connectivity, energy efficiency, and miniaturization. The key to address these challenges is to advance our communication technology to match the multi-scale, multi-modal, and dynamic features of the natural IoE. To this end, we introduce a new communication device concept, namely the universal IoE transceiver, that encompasses transceiver architectures that are characterized by multi-modality in communication (with modalities such as molecular, RF/THz, optical and acoustic) and in energy harvesting (with modalities such as mechanical, solar, biochemical), modularity, tunability, and scalability. Focusing on these fundamental traits, we provide an overview of the opportunities that can be opened up by micro/nanoscale universal transceiver architectures towards realizing the IoE applications. We also discuss the most pressing challenges in implementing such transceivers and briefly review the open research directions. Our discussion is particularly focused on the opportunities and challenges pertaining to the IoE physical layer, which can enable the efficient and effective design of higher-level techniques. We believe that such universal transceivers can pave the way for seamless connection and communication with the universe at a deeper level and pioneer the construction of the forthcoming IoE landscape.

cs.NI↗

arXiv2021

Detection in Molecular Communications with Ligand Receptors under Molecular Interference

Molecular Communications (MC) is a bio-inspired communication technique that uses molecules to transfer information among bio-nano devices. In this paper, we focus on the detection problem for biological MC receivers employing ligand receptors to infer the transmitted messages encoded into the concentration of molecules, i.e., ligands. In practice, receptors are not ideally selective against target ligands, and in physiological environments, they can interact with multiple types of ligands at different reaction rates depending on their binding affinity. This molecular cross-talk can cause a substantial interference on MC. Here we consider a particular scenario, where there is non-negligible concentration of interferer molecules in the channel, which have similar receptor-binding characteristics with the information molecules, and the receiver employs single type of receptors. We investigate the performance of four different detection methods, which make use of different statistics of the ligand-receptor binding reactions: instantaneous number of bound receptors, unbound time durations of receptors, bound time durations of receptors, and combination of unbound and bound time durations of receptors within a sampling time interval. The performance of the introduced detection methods are evaluated in terms of bit error probability for varying strength of molecular interference, similarity between information and interferer molecules, number of receptors, and received concentration difference between bit-0 and bit-1 transmissions. We propose synthetic receptor designs that can convert the required receptor statistics to the concentration of intracellular molecules, and chemical reaction networks that can chemically perform the computations required for detection.

cs.ET↗

arXiv2021

Molecular Communication Theoretical Modeling and Analysis of SARS-CoV2 Transmission in Human Respiratory System

Severe Acute Respiratory Syndrome-CoronaVirus 2 (SARS-CoV2) caused the ongoing pandemic. This pandemic devastated the world by killing more than a million people, as of October 2020. It is imperative to understand the transmission dynamics of SARS-CoV2 so that novel and interdisciplinary prevention, diagnostic, and therapeutic techniques could be developed. In this work, we model and analyze the transmission of SARS-CoV2 through the human respiratory tract from a molecular communication perspective. We consider that virus diffusion occurs in the mucus layer so that the shape of the tract does not have a significant effect on the transmission. Hence, this model reduces the inherent complexity of the human respiratory system. We further provide the impulse response of SARS-CoV2-ACE2 receptor binding event to determine the proportion of the virus population reaching different regions of the respiratory tract. Our findings confirm the results in the experimental literature on higher mucus flow rate causing virus migration to the lower respiratory tract. These results are especially important to understand the effect of SARS-CoV2 on the different human populations at different ages who have different mucus flow rates and ACE2 receptor concentrations in the different regions of the respiratory tract.

physics.bio-ph↗

arXiv2021

Information and Communication Theoretical Understanding and Treatment of Spinal Cord Injuries: State-of-the-art and Research Challenges

Among the various key networks in the human body, the nervous system occupies central importance. The debilitating effects of spinal cord injuries (SCI) impact a significant number of people throughout the world, and to date, there is no satisfactory method to treat them. In this paper, we review the major treatment techniques for SCI that include promising solutions based on information and communication technology (ICT) and identify the key characteristics of such systems. We then introduce two novel ICT-based treatment approaches for SCI. The first proposal is based on neural interface systems (NIS) with enhanced feedback, where the external machines are interfaced with the brain and the spinal cord such that the brain signals are directly routed to the limbs for movement. The second proposal relates to the design of self-organizing artificial neurons (ANs) that can be used to replace the injured or dead biological neurons. Apart from SCI treatment, the proposed methods may also be utilized as enabling technologies for neural interface applications by acting as bio-cyber interfaces between the nervous system and machines. Furthermore, under the framework of Internet of Bio- Nano Things (IoBNT), experience gained from SCI treatment techniques can be transferred to nano communication research.

q-bio.NC↗

arXiv2020

Graphene-based Nanoscale Molecular Communication Receiver: Fabrication and Microfluidic Analysis

Bio-inspired molecular communications (MC), where molecules are used to transfer information, is the most promising technique to realise the Internet of Nano Things (IoNT), thanks to its inherent biocompatibility, energy-efficiency, and reliability in physiologically-relevant environments. Despite a substantial body of theoretical work concerning MC, the lack of practical micro/nanoscale MC devices and MC testbeds has led researchers to make overly simplifying assumptions about the implications of the channel conditions and the physical architectures of the practical transceivers in developing theoretical models and devising communication methods for MC. On the other hand, MC imposes unique challenges resulting from the highly complex, nonlinear, time-varying channel properties that cannot be always tackled by conventional information and communication tools and technologies (ICT). As a result, the reliability of the existing MC methods, which are mostly adopted from electromagnetic communications and not validated with practical testbeds, is highly questionable. As the first step to remove this discrepancy, in this study, we report on the fabrication of a nanoscale MC receiver based on graphene field-effect transistor biosensors. We perform its ICT characterisation in a custom-designed microfluidic MC system with the information encoded into the concentration of single-stranded DNA molecules. This experimental platform is the first practical implementation of a micro/nanoscale MC system with nanoscale MC receivers, and can serve as a testbed for developing realistic MC methods and IoNT applications.

cs.ET↗

arXiv2020

Capacity Analysis for Joint Radar-Communication Capable Coherent MIMO Radars

Recently, huge attention is attracted to the concept of integrating communication and radar missions within the same platform. Joint radar-communications (JRC) system gives an important opportunity to reduce spectrum usage and product cost while doing concurrent operation, as target sensing via radar processing and establishing communication links. A JRC-capable coherent MIMO radar system have been proposed recently in the literature. Several methods are introduced to reach dual goal as a notable null level towards the direction of interest of the radar and MIMO radar waveform orthogonality. Due to the limitations originated form the JRC operation, communication channel may encounter unwanted amplitude variations. This unwanted modulation normally affects the communication performance by its nature, due to the fades on radiated signal amplitude towards the direction of communication. However, the effect of this unintentional modulation on communication channel is yet to be investigated. In this paper, the communication channel for JRC capable phase-coded coherent MIMO radars is analyzed and investigated under additive white Gaussian noise and Rayleigh/Rician fading conditions. Communication capacity is evaluated for each channel condition. The results reveal that, using the single-side limited null direction fixed waveform generation method displays the best capacity performance under all channel conditions.

eess.SP↗