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The proliferation of Low Earth Orbit (LEO) satellite constellations has intensified the challenge of space debris management. This paper introduces DebriSense-THz, a novel Terahertz-Enabled Debris Sensing system for LEO satellites that leverages Integrated Sensing and Communications (ISAC) technology. We present a comprehensive THz channel model for LEO environments, incorporating debris interactions such as reflection, scattering, and diffraction. The DebriSense-THz architecture employs machine learning techniques for debris detection and classification using Channel State Information (CSI) features. Performance evaluation across different frequencies (30 GHz-5 THz), MIMO configurations, debris densities, and SNR levels demonstrates significant improvements in debris detection and classification accuracy (95-99% at 5 THz compared to 62-81% at 30 GHz). Higher SNR configurations enhance sensing performance, particularly at higher frequencies. The system shows robust performance across various debris densities and MIMO size in the THz range, with a noted trade-off between communication reliability and sensing accuracy at lower frequencies. DebriSense-THz represents a significant advance in space situational awareness, paving the way for more effective debris mitigation strategies in increasingly congested LEO environments., Comment: 13 pages, 11 figures, journal

The gut-brain axis is the communication link between the gut and the brain. Although it is known that the gut-brain axis plays a pivotal role in homeostasis, its overall mechanism is still not known. However, for neural synapses, classical molecular communication is described by the formation of ligand-receptor complexes, which leads to the opening of ion channels. Moreover, there are some conditions that need to be fulfilled before the opening of the ion channel. In this study, we will consider the gut-brain axis, where neurotransmitters diffuse through the synaptic cleft, considering molecular communication. On the vagus nerve (VN) membrane, i.e., the post-synaptic membrane of the synapse, it undergoes a quantum communication (QC), which initiates the opening of the ion channel, thus initiating the communication signal from the gut to the brain. It evolves a new paradigm of communication approach, Molecular Quantum (MolQ) communication. Based on the QC model, we theoretically analyzes the output states, and QC is simulated considering the incoming neurotransmitter's concentration and validated by analyzing the entropy and the mutual information of the input, i.e., neurotransmitter's concentration, and output, i.e., ion channel opening., Comment: 7 pages

Biological entities in nature have developed sophisticated communication methods over millennia to facilitate cooperation. Among these entities, plants are some of the most intricate communicators. They interact with each other through various communication modalities, creating networks that enable the exchange of information and nutrients. In this paper, we explore this collective behavior and its components. We then introduce the concept of agent plants, outlining their architecture and detailing the tasks of each unit. Additionally, we investigate the mycorrhizal fungi-plant symbiosis to extract glucose for energy harvesting. We propose an architecture that converts the chemical energy stored in these glucose molecules into electrical energy. We conduct comprehensive analyses of the proposed architecture to validate its effectiveness., Comment: 10 pages, 5 figures, conference

The accelerated pace of global population growth underscores the crucial role of the agricultural sector in mitigating food scarcity, as well as in supporting livelihoods through employment opportunities and bolstering national economies. This sector faces several critical challenges, including resource depletion, socioeconomic issues, gaps in technology and innovation, and the impact of climate change. The introduction of mechanization has significantly transformed agriculture by enhancing sustainability and increasing the productivity of crops. Recently, traditional farming methods have been supplemented with advanced technologies steering the industry towards precision agriculture. The convergence of these advanced technologies has facilitated the automation of various tasks such as water management, crop monitoring, disease management, and harvesting. The concept of Internet of Everything (IoE) has gained traction due to its holistic approach towards integrating various IoT specializations, called IoXs where X referring to a specific domain. This includes areas like the Internet of Sensors (IoS), Internet of Vehicles (IoV), Internet of Energy (IoEn), Internet of Space Things (IoST), Industrial Internet of Things (IIoT), and Internet of Drones (IoD). This paper explores the potential of the Internet of Everything (IoE) in revolutionizing agricultural systems. The focus is on assessing the impact of cutting-edge and novel technologies, such as 6G, molecular communication (MC), Internet of Nano Things (IoNT), Internet of Bio-Nano Things (IoBNT), Internet of Fungus, and designer phages, in significantly improving agricultural yield, efficiency, and productivity. Additionally, the potential of these technologies is evaluated in terms of their applicability, associated challenges, and future research directions within the realm of precision agriculture.

Parkinson's disease (PD) is a progressive neurodegenerative disease, and it is caused by the loss of dopaminergic neurons in the basal ganglia (BG). Currently, there is no definite cure for PD, and available treatments mainly aim to alleviate its symptoms. Due to impaired neurotransmitter-based information transmission in PD, molecular communication-based approaches can be employed as potential solutions to address this issue. Molecular Communications (MC) is a bio-inspired communication method utilizing molecules for carrying information. This mode of communication stands out for developing bio-compatible nanomachines for diagnosing and treating, particularly in addressing neurodegenerative diseases like PD, due to its compatibility with biological systems. This study presents a novel treatment method that introduces an Intelligent Dopamine Rate Modulator (IDRM), which is located in the synaptic gap between the substantia nigra pars compacta (SNc) and striatum to compensate for insufficiency dopamine release in BG caused by PD. For storing dopamine in the IDRM, dopamine compound (DAC) is swallowed and crossed through the digestive system, blood circulatory system, blood-brain barrier (BBB), and brain extracellular matrix uptakes with IDRMs. Here, the DAC concentration is calculated in these regions, revealing that the required exogenous dopamine consistently reaches IDRM. Therefore, the perpetual dopamine insufficiency in BG associated with PD can be compensated. This method reduces drug side effects because dopamine is not released in other brain regions. Unlike other treatments, this approach targets the root cause of PD rather than just reducing symptoms., Comment: 10 pages, 9 figures

Concurrent with advancements in molecular communication (MC), bacterial communication is emerging as a key area of interest. Given the frequent use of bacteria in various MC models, it is essential to have a thorough grasp of their intrinsic communication, signaling, and engineering techniques. Although it is crucial to have a strong understanding of the communication background, the inherent biological variability of bacteria may introduce complexity. Thus, an in-depth understanding of bacteria and their communication is a must for improving and extending the models in which they are utilized. Furthermore, the emerging and evolving domain of bacterial computing provides an exciting opportunity for advancing applications in areas such as environmental monitoring and biological computing networks. By integrating the communication and sensing capabilities, bacterial computing offers a promising framework for enhancing the adaptability and responsiveness of bacteria. This paper provides a comprehensive review of bacterial communication and computing, illustrating their application and the link with the concept of the Internet of Everything (IoE). Through the analysis of these biological systems, we reach a deeper insight on how the small-scale interactions may contribute to the major concept of universal interconnectedness; thus, we make the knowledge to flow and communication stronger between different fields. The discussion include the identification of the different bacterial mechanisms that could revolutionize the traditional communication systems. Thus, this paper offers valuable insights into previously unaddressed aspects of bacterial behavior, suggesting novel avenues for future research and aiming to advance understanding and application of bacterial sensing, communication and computing in MC models., Comment: 24 pages, 9 figures

Molecular communication (MC) has emerged as a promising paradigm employing molecules to transfer information at the nano-scale. In a recent paper, prefix source coding was introduced into the field, through an MC-adapted version of the Huffman coding. We first demonstrate that, although MC-adapted Huffman coding improves symbol error rates compared to Huffman coding, it does not always produce an optimal MC-adapted prefix codebook in terms of expected length and power. Accordingly, we utilise a straightforward brute-force algorithm to find an optimal MC-adapted prefix (MoPC$^{*}$) codebook for any given alphabet. In the context of MC source coding, the major finding of this paper is the Molecular Arithmetic Coding (MoAC) whose algorithmic implementation and code-structure is non-arbitrarily different than that of the widely-known classical arithmetic coding (AC). MoAC is designed to mitigate inter-symbol interference (ISI) for alphabets with known symbol probabilities through, in a highly efficient way, avoiding consecutive 1-bits. However, due to bit precision limitations, unique-decodability of MoAC is not guaranteed. Accordingly, a uniquely-decodable new coding scheme named Molecular Arithmetic with Prefix Coding (MoAPC) is introduced. On two exemplary nucleotide alphabets, we show that MoAPC has a better compression performance than MoPC$^{*}$. Simulation results demonstrate the highly superior word error rate (WER) and symbol error rate (SER) values of MoAPC compared to its arithmetic contenders: AC, and the Substitution Arithmetic Coding (SAC), which is introduced for the first time in this paper, and is a simple and trivial adaption of AC to molecular communication. Simulation results show that on the first alphabet, MoAPC surpasses all given methods in WER and asymptotically in SER; while on the second alphabet, MoPC$^{*}$ surpasses all in SER and WER., Comment: 12 pages, 24 figures, 7 tables

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.

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., Comment: 12 pages, 11 figures

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., Comment: 10 pages, 11 figures

The advancements in nanotechnology, material science, and electrical engineering have shrunk the sizes of electronic devices down to the micro/nanoscale. This brings the opportunity of developing the Internet of Nano Things (IoNT), an extension of the Internet of Things (IoT). With nanodevices, numerous new possibilities emerge in the biomedical, military fields, and industrial products. However, a continuous energy supply is mandatory for these devices to work. At the micro/nanoscale, batteries cannot supply this demand due to size limitations and the limited energy contained in the batteries. Internet of Harvester Nano Things (IoHNT), a concept of Energy Harvesting (EH) integrated with wireless power transmission (WPT) techniques, converts the existing different energy sources into electrical energy and transmits to IoNT nodes. As IoHNTs are not directly attached to IoNTs, it gives flexibility in size. However, we define the size of IoHNTs as up to 10 cm. In this review, we comprehensively investigate the available energy sources and EH principles to wirelessly power IoNTs. We discuss the IoHNT principles, material selections, and state-of-the-art applications of each energy source for different sectoral applications. The different technologies of WPT and how communication is influenced by the incorporation of IoHNTs to power IoNTs are discussed with the future research directions. IoHNTs represent a shift in the nanodevice power supply, leading us towards a future where wireless technology is widespread. Hence, it will motivate researchers to envision and contribute to advancing the following power revolution in IoNT, providing unmatched simplicity and efficiency.

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.

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).

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., Comment: Submitted to the IEEE for possible publication. arXiv admin note: text overlap with arXiv:2301.01049

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.

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.

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., Comment: 12 pages, 8 figures

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.

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.

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., Comment: 17 pages, 10 figures

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., Comment: IEEE Transactions on Molecular, Biological, and Multi-Scale Communications

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., Comment: References fixed

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., Comment: IEEE Reviews in Biomedical Engineering

The Internet of Things (IoT) are interconnected devices for exchanging information through sensors and actuators. One of the main physical sensors to understand the environment beyond the visible world is a radar. Basically, radars have always been a military tool to be used to investigate the environment. However, with the developing technology, radars have become more compact and affordable to use in a building, in a car, in a drone or even in a wristwatch. In the near future, radar-equipped IoT platforms will start to appear increasingly. For each IoT platform, dual use of spectrum with dual aperture is required for sensing and communicating when using conventional approaches. For the radar sensing IoT devices, the emission from the radar and communication circuitry is the main reason of the increase in energy consumption. Furthermore, an increasing number of radars emerges as congested spectrum, and RF convergence between radars and communication systems becomes more likely to present itself. Recent years, there have been numerous researches which propose using the one emission/waveform for perceiving the environment and sending information. They are often called as "Joint Radar-Communication (JRC)" systems. Due to the latest developments in JRC system designs, radar sensing IoT platforms now can be transformed into an "Internet of RAdio Detectors And Rangers (IoR)". In this article, we present a short survey on JRC technologies, possible application areas IoR applications and challenges and future research directions for enabling the concept of IoR., Comment: 7 pages, 5 figures

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., Comment: 17 pages

Inspired by Nature, molecular communications (MC), i.e., use of molecules to encode, transmit and receive information, stands as the most promising communication paradigm to realize nanonetworks. Even though there has been extensive theoretical research towards nanoscale MC, there are no examples of implemented nanoscale MC networks. The main reason for this lies in the peculiarities of nanoscale physics, challenges in nanoscale fabrication and highly stochastic nature of biochemical domain of envisioned nanonetwork applications. This mandates developing novel device architectures and communication methods compatible with MC constraints. To that end, various transmitter and receiver designs for MC have been proposed in literature together with numerable modulation, coding and detection techniques. However, these works fall into domains of a very wide spectrum of disciplines, including but not limited to information and communication theory, quantum physics, materials science, nanofabrication, physiology and synthetic biology. Therefore, we believe it is imperative for the progress of the field that, an organized exposition of cumulative knowledge on subject matter be compiled. Thus, to fill this gap, in this comprehensive survey we review the existing literature on transmitter and receiver architectures towards realizing MC amongst nanomaterial-based nanomachines and/or biological entities, and provide a complete overview of modulation, coding and detection techniques employed for MC. Moreover, we identify the most significant shortcomings and challenges in all these research areas, and propose potential solutions to overcome some of them.

Molecular Communications (MC) uses molecules as information carriers between nanomachines. MC channel in practice can be crowded with different types of molecules, i.e., ligands, which can have similar binding properties causing severe cross-talk on ligand receptors. Simultaneous sensing of multiple ligand types provides opportunities for eliminating interference of external molecular sources and multi-user interference (MUI), and developing new multiple access techniques for MC nanonetworks. In this paper, we investigate channel sensing methods that use only a single type of receptors and exploit the amount of time receptors stay bound and unbound during ligand-receptor binding reaction to concurrently estimate the concentration of multiple types of ligands. We derive the Cram\'er-Rao Lower Bound (CRLB) for multi-ligand estimation, and propose practical and low-complexity suboptimal estimators for channel sensing. We analyze the performance of the proposed methods in terms of normalized mean squared error (NMSE), and show that they can efficiently estimate the concentration of ligands up to $10$ different types with an average NMSE far below $10^{-2}$. Lastly, we propose a synthetic receptor design based on modified kinetic proofreading (KPR) scheme to sample the unbound and bound time durations, and a Chemical Reaction Network (CRN) to perform the required computations in synthetic cells.

A totally new energy harvesting architecture that exploits ambient electric-field (E-field) emitting from fluorescent light fixtures is presented. A copper plate, 50 x 50 cm in size, is placed in between the ambient field to extract energy by capacitive coupling. A low voltage prototype is designed, structured and tested on a conventional ceiling-type 4-light fluorescent troffer operating in 50 Hz 220 V AC power grid. It is examined that the harvester is able to collect roughly 1.25 J of energy in 25 min when a 0.1 F of super-capacitor is employed. The equivalent circuit and the physical model of the proposed harvesting paradigm are provided, and the attainable power is evaluated in both theoretical and experimental manner. The scavenged energy is planned to be utilized for building battery-less Internet of Things (IoT) networks that are obliged to sense environmental parameters, analyze the gathered data, and remotely inform a higher authority within predefined periods.

Molecular communication (MC) is a bio-inspired communication method based on the exchange of molecules for information transfer among nanoscale devices. Although MC has been extensively studied from various aspects, limitations imposed by the physical design of transceiving units have been largely neglected in the literature. Recently, we have proposed a nanobioelectronic MC receiver architecture based on the nanoscale field effect transistor-based biosensor (bioFET) technology, providing noninvasive and sensitive molecular detection at nanoscale while producing electrical signals at the output. In this paper, we derive analytical closed-form expressions for the capacity and capacity-achieving input distribution for a memoryless MC channel with a silicon nanowire (SiNW) FET-based MC receiver. The resulting expressions could be used to optimize the information flow in MC systems equipped with nanobioelectronic receivers., Comment: To be presented at IEEE EMBC 2016, Orlando, FL, USA

Initiation of fourth generation (4G) mobile telecommunication system rollouts fires the starting pistol for beyond 4G research activities. Whereas technologies enhancing spectral efficiency have traditionally been the solution to data rate and network capacity increase demands, due to the already advanced techniques, returns of the even more complicated algorithms hardly worth the complexity increase any longer. In addition, surging number of connected devices now enables operative use of short-range communication methods. Also considering the recently approved standards for the 60 gigahertz (GHz) industrial, scientific and medical radio band, in this paper the transmission windows around 300 GHz is proposed to be utilized for the fifth generation wireless communication systems. Motivations for the low end of the terahertz (THz) band are provided in accordance with market trends, and standardization activities in higher frequencies are listed. Unified mathematical expressions of the electromagnetic wave propagation mechanisms in the low-THz band are presented. THz band device technologies are outlined and a complete survey of the state-of-the-art low-THz band circuit blocks which are suitable for mass market production is given. Future research directions are specified before the conclusion of the paper.

Seamless connection of molecular nanonetworks to macroscale cyber networks is envisioned to enable the Internet of Bio-NanoThings, which promises for cutting-edge applications, especially in the medical domain. The connection requires the development of an interface between the biochemical domain of molecular nanonetworks and the electrical domain of conventional electromagnetic networks. To this aim, in this paper, we propose to exploit field effect transistor based biosensors (bioFETs) to devise a molecular antenna capable of transducing molecular messages into electrical signals. In particular, focusing on the use of SiNW FET-based biosensors as molecular antennas, we develop deterministic and noise models for the antenna operation to provide a theoretical framework for the optimization of the device from communication perspective. We numerically evaluate the performance of the antenna in terms of the Signal-to-Noise Ratio (SNR) at the electrical output., Comment: to appear in Proc. IEEE WF-IoT 2015, Milan, Italy, Dec. 2015

Molecular communications (MC), where molecules are used to encode, transmit, and receive information, is a promising means of enabling the coordination of nanoscale devices. The paradigm has been extensively studied from various aspects, including channel modeling and noise analysis. Comparatively little attention has been given to the physical design of molecular receiver and transmitter, envisioning biological synthetic cells with intrinsic molecular reception and transmission capabilities as the future nanomachines. However, this assumption leads to a discrepancy between the envisaged applications requiring complex communication interfaces and protocols, and the very limited computational capacities of the envisioned biological nanomachines. In this paper, we examine the feasibility of designing a molecular receiver, in a physical domain other than synthetic biology, meeting the basic requirements of nanonetwork applications. We first review the state-of-the-art biosensing approaches to determine whether they can inspire a receiver design. We reveal that nanoscale field effect transistor based electrical biosensor technology (bioFET) is a particularly useful starting point for designing a molecular receiver. Focusing on bioFET-based molecular receivers with a conceptual approach, we provide a guideline elaborating on their operation principles, performance metrics and design parameters. We then provide a simple model for signal flow in silicon nanowire (SiNW) FET-based molecular receiver. Lastly, we discuss the practical challenges of implementing the receiver and present the future research avenues from a communication theoretical perspective.