Nanoscale Communication Paradigm Research Articles

Design of Plasmonic Yagi-Uda Nanoantennas for Chip-Scale Optical Wireless Communications.

Optical wireless transmission has recently become a major cutting-edge alternative for on-chip/inter-chip communications with higher transmission speeds and improved power efficiency. Plasmonic nanoantennas, the building blocks of this new nanoscale communication paradigm, require precise design to have directional radiation and improved communication ranges. Particular interest has been paid to plasmonic Yagi–Uda, i.e., the optical analog of the conventional Radio Frequency (RF) Yagi–Uda design, which may allow directional radiation of plasmonic fields. However, in contrast to the RF model, an overall design strategy for the directional and optimized front-to-back ratio of the radiated far-field patterns is lacking. In this work, a guide for the optimized design of Yagi–Uda plasmonic nanoantennas is shown. In particular, five different design conditions are used to study the effects of sizes and spacing between the constituent parts (made of Au). Importantly, it is numerically demonstrated (using the scattered fields) that closely spaced nanoantenna elements are not appropriated for directional light-to-plasmon conversion/radiation. In contrast, if the elements of the nanoantenna are widely spaced, the structure behaves like a one-dimensional array of nanodipoles, producing a funnel-like radiation pattern (not suitable for on-chip wireless optical transmission). Therefore, based on the results here, it can be concluded that the constituent metallic rib lengths must be optimized to exhibit the resonance at the working wavelength, whilst their separations should follow the relation , where indicates the effective wavelength scaling for plasmonic nanostructures.

Impact of Long Term Plasticity on Information Transmission Over Neuronal Networks.

The realization of bio-compatible nanomachines would pave the way for developing novel diagnosis and treatment techniques for the dysfunctions of intra-body nanonetworks and revolutionize the traditional healthcare methodologies making them less invasive and more efficient. The network of these nanomachines is aimed to be used for treating neuronal diseases such as developing an implant that bridges over the injured spinal cord to regain its normal functionality. Thus, nanoscale communication paradigms are needed to be investigated to facilitate communication between nanomachines. Communication among neurons is one of the most promising nanoscale communication paradigm, which necessitates the thorough communication theoretical analysis of information transmission among neurons. The information flow in neuro-spike communication channel is regulated by the ability of neurons to change synaptic strengths over time, i.e. synaptic plasticity. Thus, the performance evaluation of the nervous nanonetwork is incomplete without considering the influence of synaptic plasticity. In this paper, we focus on information transmission among hippocampal pyramidal neurons and provide a comprehensive channel model for MISO neuro-spike communication, which includes axonal transmission, vesicle release process, synaptic communication and spike generation. In this channel, the spike timing dependent plasticity (STDP) model is used to cover both synaptic depressiofan and potentiation depending on the temporal correlation between spikes generated by input and output neurons. Since synaptic strength changes depending on different physiological factors such as spiking rate of presynaptic neurons, number of correlated presynaptic neurons and the correlation factor among them, we simulate this model with correlated inputs and analyze the evolution of synaptic weights over time. Moreover, we calculate average mutual information between input and output of the channel and find the impact of plasticity and correlation among inputs on the information transmission. The simulation results reveal the impact of different physiological factors related to either presynaptic or postsynaptic neurons on the performance of MISO neuro-spike communication. Moreover, they provide guidelines for selecting the system parameters in a bio-inspired neuronal network according to the requirements of different applications.

Signal reconstruction in diffusion‐based molecular communication

AbstractMolecular 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.

Sum Rate of MISO Neuro-Spike Communication Channel With Constant Spiking Threshold.

Communication among neurons, known as neuro-spike communication, is the most promising technique for realization of a bio-inspired nanoscale communication paradigm to achieve biocompatible nanonetworks. In neuro-spike communication, the information, encoded into spike trains, is communicated to various brain regions through neuronal network. An output neuron needs to receive signal from multiple input neurons to generate a spike. Hence, in this paper, we aim to quantify the information transmitted through the multiple-input single-output (MISO) neuro-spike communication channel by considering models for axonal propagation, synaptic transmission, and spike generation. Moreover, the spike generation and propagation in each neuron requires opening and closing of numerous ionic channels on the cell membrane, which consumes considerable amount of ATP molecules called metabolic energy. Thus, we evaluate how applying a constraint on available metabolic energy affects the maximum achievable mutual information of this system. To this aim, we derive a closed form equation for the sum rate of the MISO neuro-spike communication channel and analyze it under the metabolic cost constraints. Finally, we discuss the impacts of changes in number of pre-synaptic neurons on the achievable rate and quantify the tradeoff between maximum achievable sum rate and the consumed metabolic energy.

Information Capacity of Vesicle Release in Neuro-Spike Communication

Information transmission in the nervous system is performed through the propagation of spikes among neurons, which is done by vesicle release to chemical synapses. Understanding the fundamentals of this communication can lead to the implementation of bio-inspired nanoscale communication paradigms. In this letter, we utilize a realistic pool-based model for vesicle release and replenishment in hippocampal pyramidal neurons and evaluate the capacity of information transmission in this process by modeling it as a binary channel with memory. Then, we derive a recurrence relation for the number of available vesicles, which is used to find successful bit transmission probabilities and mutual information between input and output. Finally, we evaluate the spiking probability that maximizes mutual information and derive the capacity of the channel.

A Communication Theoretical Modeling of Axonal Propagation in Hippocampal Pyramidal Neurons.

Understanding the fundamentals of communication among neurons, known as neuro-spike communication, leads to reach bio-inspired nanoscale communication paradigms. In this paper, we focus on a part of neuro-spike communication, known as axonal transmission, and propose a realistic model for it. The shape of the spike during axonal transmission varies according to previously applied stimulations to the neuron, and these variations affect the amount of information communicated between neurons. Hence, to reach an accurate model for neuro-spike communication, the memory of axon and its effect on the axonal transmission should be considered, which are not studied in the existing literature. In this paper, we extract the important factors on the memory of axon and define memory states based on these factors. We also describe the transition among these states and the properties of axonal transmission in each of them. Finally, we demonstrate that the proposed model can follow changes in the axonal functionality properly by simulating the proposed model and reporting the root mean square error between simulation results and experimental data.

Genetically Engineered Bacteria-Based BioTransceivers for Molecular Communication

Molecular Communication (MC) is a nano-scale communication paradigm where the information is carried by molecular signals. To establish information transmission using molecules, biological nanomachines can be utilized as transmitters and receivers. A bacteria can be programmed as a biotransceiver by modifying their genetic code to implement biological circuits. In this paper, genetically engineered bacteria-based biotransceivers are investigated for MC, where bacteria can generate and respond to the molecular signals. A biochemical model of biological circuits is presented, and both analog and digital signaling are studied. The challenges in connecting basic biological circuits to build these blocks are revealed. A biotransceiver architecture is introduced that combines sensing, transmitting, receiving and processing blocks. Furthermore, biological circuit design framework is proposed for transmission of signals with M-ary pulse amplitude modulation. The biological circuits designed for biotransceiver are elaborated via numerical results based on biochemical parameters of the genetically engineered bacteria. The provided results show that using biological circuits, bacteria can function as a transmitter and receiver node for MC. Our work stands as a basis for future biotransceiver design for MC.

TeraNets: ultra-broadband communication networks in the terahertz band

Terahertz Band communication is envisioned as a key technology to satisfy the data rate requirements of future wireless communication networks, and enable new applications both in classical networking domains as well as in novel nanoscale communication paradigms. Major recent advancements in THz Band technologies are helping to finally close the so called THz Gap and bring practical THz Band communication networks one step closer. This paper surveys the state of the art in THz Band device technologies, and highlights the challenges and potential solutions from the communication and networking perspective as well as in terms of experimental testbeds. Ultimately, a roadmap is defined for the development of THz Band systems as the new frontier in wireless communications.

Terahertz band: Next frontier for wireless communications

This paper provides an in-depth view of Terahertz Band (0.1–10 THz) communication, which is envisioned as a key technology to satisfy the increasing demand for higher speed wireless communication. THz Band communication will alleviate the spectrum scarcity and capacity limitations of current wireless systems, and enable new applications both in classical networking domains as well as in novel nanoscale communication paradigms. In this paper, the device design and development challenges for THz Band are surveyed first. The limitations and possible solutions for high-speed transceiver architectures are highlighted. The challenges for the development of new ultra-broadband antennas and very large antenna arrays are explained. When the devices are finally developed, then they need to communicate in the THz band. There exist many novel communication challenges such as propagation modeling, capacity analysis, modulation schemes, and other physical and link layer solutions, in the THz band which can be seen as a new frontier in the communication research. These challenges are treated in depth in this paper explaining the existing plethora of work and what still needs to be tackled.

A Brief Survey on Molecular and Electromagnetic Communications in Nano-Networks

Recent advancement in physics and nanotechnology have paved the way for manufacturing of processor, memory, batteries, transceiver, antenna and sensing units at nano-scale. A nanomachine is an integrated device with dimensions in nano-scale, and able to do simple tasks. By networking of nano-machines, they are able to perform the more complicated tasks by the cooperative manner and can play an important role in applications such as biomedical, environmental monitoring, industrial and military. Many novel nano-scale communication options have been currently proposed. However, there are four main nano-scale communication techniques: nanomechanical, acoustic, chemical or molecular and electromagnetic communications. However, this paper focuses on the molecular and electromagnetic communications as the promising nanoscale communication approaches, and then will be reviewed the novel nano-scale communication paradigms that are currently presented.

Optimal Transmission Probability in Binary Molecular Communication

Molecular communication (MC) is a promising nanoscale communication paradigm that enables nanomachines to share information by using messenger molecules. 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.

Rate-Delay Tradeoff With Network Coding in Molecular Nanonetworks

Molecular communication is a novel nanoscale communication paradigm, in which information is encoded in messenger molecules for transmission and reception. However, molecular communication is unreliable and has highly varying long propagation delays mainly due to the stochastic behavior of the freely diffusing molecules. Thus, it is essential to analyze its delay characteristics, as well as the tradeoff between the rate and delay, in order to reveal the capabilities and limitations of molecular information transmission in nanonetworks. In this paper, first, a new messenger-based molecular communication model, which includes a nanotransmitter sending information to a nanoreceiver, is introduced. The information is encoded on a polyethylene molecule, CH3 (CHX)n CH2F, where X stands for H and F atoms representing 0 and 1 bits, respectively. The emission of the molecules is modeled by puffing process which is inspired by the alarm pheromone release by animals in dangerous situations. In this work, the rate-delay characteristics of this messenger-based molecular communication model are explored. Then, a Nano-Relay is inserted in the model, which XOR's the incoming messages from two different nanomachines. Performance evaluation shows that indeed, a simple network coding mechanism significantly improves the rate given delay of the system, and vice versa.

A Simulation Framework for Neuron-based Molecular Communication

Molecular communication is a nanoscale communication paradigm that utilizes molecules as a communication medium between nanoscale devices. Development and availability of simulators is critical in this emerging research area since research on molecular communication heavily depends on simulations as the only means to evaluate analytical models and protocols. This paper proposes a simulation framework for neuron-based molecular communication, which utilizes electrochemical signals through neuronal networks. The proposed framework is designed to integrate various simulation components such as visualizers and editors for neuronal networks, media access controllers to neuronal networks and communication schedulers for neuronal signal transmissions. This paper describes key simulation components in the proposed framework and validates them with a case study that implements a TDMA-based signaling protocol in a simulated neuronal network and examines its performance characteristics with evolutionary multiobjective optimization algorithms.

Nanoscale Communication With Molecular Arrays in Nanonetworks

Molecular communication is a promising nanoscale communication paradigm that enables nanomachines to exchange information by using molecules as communication carrier. Up to now, the molecular communication channel between a transmitter nanomachine (TN) and a receiver nanomachine (RN) has been modeled as either concentration channel or timing channel. However, these channel models necessitate exact time synchronization of the nanomachines and provide a relatively low communication bandwidth. In this paper, the Molecular ARray-based COmmunication (MARCO) scheme is proposed, in which the transmission order of different molecules is used to convey molecular information without any need for time synchronization. The MARCO channel model is first theoretically derived, and the intersymbol interference and error probabilities are obtained. Based on the error probability, achievable communication rates are analytically obtained. Numerical results and performance comparisons reveal that MARCO provides significantly higher communication rate, i.e., on the scale of 100 Kbps, than the previously proposed molecular communication models without any need for synchronization. More specifically, MARCO can provide more than 250 Kbps of molecular communication rate if intersymbol time and internode distance are set to 2 μs and 2 nm, respectively.

Body area nanonetworks with molecular communications in nanomedicine

Recent developments in nano and biotechnology enable promising therapeutic nanomachines (NMs) that operate on inter- or intracellular area of human body. The networks of such therapeutic NMs, body area nanonetworks (BAN <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> s), also empower sophisticated nanomedicine applications. In these applications, therapeutic NMs share information to perform computation and logic operations, and make decisions to treat complex diseases. Hence, one of the most challenging subjects for these sophisticated applications is the realization of BAN <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> through a nanoscale communication paradigm. In this article, we introduce the concept of a BAN <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> with molecular communication, where messenger molecules are used as communication carrier from a sender to a receiver NM. The current state of the art of molecular communication and BAN <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> in nanomedicine applications is first presented. Then communication theoretical efforts are reviewed, and open research issues are given. The objective of this work is to introduce this novel and interdisciplinary research field and highlight major barriers toward its realization from the viewpoint of communication theory.

A Physical Channel Model and Analysis for Nanoscale Molecular Communications With Förster Resonance Energy Transfer (FRET)

In this study, a novel and physically realizable nanoscale communication paradigm is introduced based on a well-known phenomenon, Förster resonance energy transfer (FRET), for the first time in the literature. FRET is a nonradiative energy transfer process between fluorescent molecules based on the dipole-dipole interactions of molecules. Energy is transferred rapidly from a donor to an acceptor molecule in a close proximity such as 0 to 10 nm without radiation of a photon. Low dependence on the environmental factors, controllability of its parameters, and relatively wide transfer range make FRET a promising candidate to be used for a high-rate nanoscale communication channel. In this paper, the simplest form of the FRET-based molecular communication channel comprising a single transmitter-receiver nanomachine pair and an extended version of this channel with a relay nanomachine for long-range applications are modeled considering nanomachines as nanoscale electromechanical devices with some sensing, computing, and actuating capabilities. Furthermore, using the information theoretical approach, the capacities of these communication channels are investigated and the dependence of the capacity on some environmental and intrinsic parameters is analyzed. It is shown that the capacity can be increased by appropriately selecting the donor-acceptor pair, the medium, the intermolecular distance, and the orientation of the molecules.

NanoNS: A nanoscale network simulator framework for molecular communications

A number of nanomachines that cooperatively communicate and share molecular information in order to achieve specific tasks is envisioned as a nanonetwork. Due to the size and capabilities of nanomachines, the traditional communication paradigms cannot be used for nanonetworks in which network nodes may be composed of just several atoms or molecules and scale on the orders of few nanometers. Instead, molecular communication is a promising solution approach for the nanoscale communication paradigm. However, molecular communication must be thoroughly investigated to realize nanoscale communication and nanonetworks for many envisioned applications such as nanoscale body area networks, and nanoscale molecular computers. In this paper, a simulation framework (NanoNS) for molecular nanonetworks is presented. The objective of the framework is to provide a simulation tool in order to create a better understanding of nanonetworks and facilitate the development of new communication techniques and the validation of theoretical results. The NanoNS framework is built on top of core components of a widely used network simulator (ns-2). It incorporates the simulation modules for various nanoscale communication paradigms based on a diffusive molecular communication channel. The details of NanoNS are discussed and some functional scenarios are defined to validate NanoNS. In addition to this, the numerical analyses of these functional scenarios and their experimental results are presented. The validation of NanoNS is shown via comparative evaluation of these experimental and numerical results.

Carbon nanotube-based nanoscale ad hoc networks

Recent developments in nanoscale electronics allow current wireless technologies to function in nanoscale environments. Especially due to their incredible electrical and electromagnetic properties, carbon nanotubes are promising physical phenomenon that are used for the realization of a nanoscale communication paradigm. This provides a very large set of new promising applications such as collaborative disease detection with communicating in-vivo nanosensor nodes and distributed chemical attack detection with a network of nanorobots. Hence, one of the most challenging subjects for such applications becomes the realization of nanoscale ad hoc networks. In this article, we define the concept of carbon nanotube-based nanoscale ad hoc networks for future nanotechnology applications. Carbon nanotube-based nanoscale Ad hoc NETworks (CANETs) can be perceived as the down-scaled version of traditional wireless ad hoc networks without downgrading its main functionalities. The objective of this work is to introduce this novel and interdisciplinary research field and highlight major barriers toward its realization.