Massimiliano Pierobon

A physical end-to-end model for molecular communication in nanonetworks

Molecular communication is a promising paradigm for nanoscale networks. The end-to-end (including the channel) models developed for classical wireless communication networks need to undergo a profound revision so that they can be applied for nanonetworks. Consequently, there is a need to develop new end-to-end (including the channel) models which can give new insights into the design of these nanoscale networks. The objective of this paper is to introduce a new physical end-to-end (including the channel) model for molecular communication. The new model is investigated by means of three modules, i.e., the transmitter, the signal propagation and the receiver. Each module is related to a specific process involving particle exchanges, namely, particle emission, particle diffusion and particle reception. The particle emission process involves the increase or decrease of the particle concentration rate in the environment according to a modulating input signal. The particle diffusion provides the propagation of particles from the transmitter to the receiver by means of the physics laws underlying particle diffusion in the space. The particle reception process is identified by the sensing of the particle concentration value at the receiver location. Numerical results are provided for three modules, as well as for the overall end-to-end model, in terms of normalized gain and delay as functions of the input frequency and of the transmission range.

Diffusion-Based Noise Analysis for Molecular Communication in Nanonetworks

Molecular communication (MC) is a promising bio-inspired paradigm, in which molecules are used to encode, transmit and receive information at the nanoscale. Very limited research has addressed the problem of modeling and analyzing the MC in nanonetworks. One of the main challenges in MC is the proper study and characterization of the noise sources. The objective of this paper is the analysis of the noise sources in diffusion-based MC using tools from signal processing, statistics and communication engineering. The reference diffusion-based MC system for this analysis is the physical end-to-end model introduced in a previous work by the same authors. The particle sampling noise and the particle counting noise are analyzed as the most relevant diffusion-based noise sources. The analysis of each noise source results in two types of models, namely, the physical model and the stochastic model. The physical model mathematically expresses the processes underlying the physics of the noise source. The stochastic model captures the noise source behavior through statistical parameters. The physical model results in block schemes, while the stochastic model results in the characterization of the noises using random processes. Simulations are conducted to evaluate the capability of the stochastic model to express the diffusion-based noise sources represented by the physical model.

Nanonetworks: a new frontier in communications

Nanotechnology is enabling the development of devices in a scale ranging from one to a few one hundred nanometers. Nanonetworks, i.e., the interconnection of nano-scale devices, are expected to expand the capabilities of single nano-machines by allowing them to cooperate and share information. Traditional communication technologies are not directly suitable for nanonetworks mainly due to the size and power consumption of existing transmitters, receivers and additional processing components. All these define a new communication paradigm that demands novel solutions such as nano-transceivers, channel models for the nano-scale, and protocols and architectures for nanonetworks. In this talk, first the state-of-the-art in nano-machines, including architectural aspects, expected features of future nano-machines, and current developments are presented for a better understanding of the nanonetwork scenarios. Moreover, nanonetworks features and components are explained and compared with traditional communication networks. Novel nano-antennas based on nano-materials as well as the terahertz band are investigated for electromagnetic communication in nanonetworks. Furthermore, molecular communication mechanisms are presented for short-range networking based on ion signaling and molecular motors, for medium-range networking based on flagellated bacteria and nanorods, as well as for long-range networking based on pheromones and capillaries. Finally, open research challenges such as the development of network components, molecular communication theory, and new architectures and protocols, which need to be solved in order to pave the way for the development and deployment of nanonetworks within the next couple of decades are presented.

Capacity of a Diffusion-Based Molecular Communication System With Channel Memory and Molecular Noise

Molecular Communication (MC) is a communication paradigm based on the exchange of molecules. The implicit biocompatibility and nanoscale feasibility of MC make it a promising communication technology for nanonetworks. This paper provides a closed-form expression for the information capacity of an MC system based on the free diffusion of molecules, which is of primary importance to understand the performance of the MC paradigm. Unlike previous contributions, the provided capacity expression is independent from any coding scheme and takes into account the two main effects of the diffusion channel: the memory and the molecular noise. For this, the diffusion is decomposed into two processes, namely, the Ficks diffusion and the particle location displacement, which are analyzed as a cascade of two separate systems. The Ficks diffusion captures solely the channel memory, while the particle location displacement isolates the molecular noise. The MC capacity expression is obtained by combining the two systems as function of the diffusion coefficient, the temperature, the transmitter-receiver distance, the bandwidth of the transmitted signal, and the average transmitted power. Numerical results show that a few kilobits per second can be reached within a distance range of tenth of micrometer and for an average transmitted power around 1 pW.

The internet of Bio-Nano things

The Internet of Things (IoT) has become an important research topic in the last decade, where things refer to interconnected machines and objects with embedded computing capabilities employed to extend the Internet to many application domains. While research and development continue for general IoT devices, there are many application domains where very tiny, concealable, and non-intrusive Things are needed. The properties of recently studied nanomaterials, such as graphene, have inspired the concept of Internet of NanoThings (IoNT), based on the interconnection of nanoscale devices. Despite being an enabler for many applications, the artificial nature of IoNT devices can be detrimental where the deployment of NanoThings could result in unwanted effects on health or pollution. The novel paradigm of the Internet of Bio-Nano Things (IoBNT) is introduced in this paper by stemming from synthetic biology and nanotechnology tools that allow the engineering of biological embedded computing devices. Based on biological cells, and their functionalities in the biochemical domain, Bio-NanoThings promise to enable applications such as intra-body sensing and actuation networks, and environmental control of toxic agents and pollution. The IoBNT stands as a paradigm-shifting concept for communication and network engineering, where novel challenges are faced to develop efficient and safe techniques for the exchange of information, interaction, and networking within the biochemical domain, while enabling an interface to the electrical domain of the Internet.

Noise Analysis in Ligand-Binding Reception for Molecular Communication in Nanonetworks

Molecular communication (MC) will enable the exchange of information among nanoscale devices. In this novel bio-inspired communication paradigm, molecules are employed to encode, transmit and receive information. In the most general case, these molecules are propagated in the medium by means of free diffusion. An information theoretical analysis of diffusion-based MC is required to better understand the potential of this novel communication mechanism. The study and the modeling of the noise sources is of utmost importance for this analysis. The objective of this paper is to provide a mathematical study of the noise at the reception of the molecular information in a diffusion-based MC system when the ligand-binding reception is employed. The reference diffusion-based MC system for this analysis is the physical end-to-end model introduced in a previous work by the same authors, where the reception process is realized through ligand-binding chemical receptors. The reception noise is modeled in this paper by following two different approaches, namely, through the ligand-receptor kinetics and through the stochastic chemical kinetics. The ligand-receptor kinetics allows to simulate the random perturbations in the chemical processes of the reception, while the stochastic chemical kinetics provides the tools to derive a closed-form solution to the modeling of the reception noise. The ligand-receptor kinetics model is expressed through a block scheme, while the stochastic chemical kinetics results in the characterization of the reception noise using stochastic differential equations. Numerical results are provided to demonstrate that the analytical formulation of the reception noise in terms of stochastic chemical kinetics is compliant with the reception noise behavior resulting from the ligand-receptor kinetics simulations.

A Molecular Communication System Model for Particulate Drug Delivery Systems

The goal of a drug delivery system (DDS) is to convey a drug where the medication is needed, while, at the same time, preventing the drug from affecting other healthy parts of the body. Drugs composed of micro- or nano-sized particles (particulate DDS) that are able to cross barriers which prevent large particles from escaping the bloodstream are used in the most advanced solutions. Molecular communication (MC) is used as an abstraction of the propagation of drug particles in the body. MC is a new paradigm in communication research where the exchange of information is achieved through the propagation of molecules. Here, the transmitter is the drug injection, the receiver is the drug delivery, and the channel is realized by the transport of drug particles, thus enabling the analysis and design of a particulate DDS using communication tools. This is achieved by modeling the MC channel as two separate contributions, namely, the cardiovascular network model and the drug propagation network. The cardiovascular network model allows to analytically compute the blood velocity profile in every location of the cardiovascular system given the flow input by the heart. The drug propagation network model allows the analytical expression of the drug delivery rate at the targeted site given the drug injection rate. Numerical results are also presented to assess the flexibility and accuracy of the developed model. The study of novel optimization techniques for a more effective and less invasive drug delivery will be aided by this model, while paving the way for novel communication techniques for Intrabody communication networks.

Detection Techniques for Diffusion-based Molecular Communication

Nanonetworks, the interconnection of nanosystems, are envisaged to greatly expand the applications of nanotechnology in the biomedical, environmental and industrial fields. However, it is still not clear how these nanosystems will communicate among them. This work considers a scenario of Diffusion-based Molecular Communication (DMC), a promising paradigm that has been recently proposed to implement nanonetworks. In a DMC network, transmitters encode information by the emission of molecules which diffuse throughout the medium, eventually reaching the receiver locations. In this scenario, a pulse-based modulation scheme is proposed and two techniques for the detection of the molecular pulses, namely, amplitude detection and energy detection, are compared. In order to evaluate the performance of DMC using both detection schemes, the most important communication metrics in each case are identified. Their analytical expressions are obtained and validated by simulation. Finally, the scalability of the obtained performance evaluation metrics in both detection techniques is compared in order to determine their suitability to particular DMC scenarios. Energy detection is found to be more suitable when the transmission distance constitutes a bottleneck in the performance of the network, whereas amplitude detection will allow achieving a higher transmission rate in the cases where the transmission distance is not a limitation. These results provide interesting insights which may serve designers as a guide to implement future DMC networks.

Information capacity of diffusion-based molecular communication in nanonetworks

Molecular Communication (MC) is a promising bio-inspired paradigm in which molecules are transmitted, propagated and received between nanoscale machines. One of the main challenges is the theoretical study of the maximum achievable information rate (capacity). The objective of this paper is to provide a mathematical expression for the capacity in MC nanonetworks when the propagation of the information relies on the free diffusion of molecules. Solutions from statistical mechanics and thermodynamics are used to derive a closed-form expression for the capacity as function of physical parameters, such as the size of the system, the temperature and the number of molecules as well as of the bandwidth of the system and the transmitted power. An extremely high order of magnitude of the capacity numerical values demonstrates the enormous potential of the diffusion-based MC systems.

A routing framework for energy harvesting wireless nanosensor networks in the Terahertz Band

Wireless NanoSensor Networks (WNSNs) will allow novel intelligent nanomaterial-based sensors, or nanosensors, to detect new types of events at the nanoscale in a distributed fashion over extended areas. Two main characteristics are expected to guide the design of WNSNs architectures and protocols, namely, their Terahertz Band wireless communication and their nanoscale energy harvesting process. In this paper, a routing framework for WNSNs is proposed to optimize the use of the harvested energy to guarantee the perpetual operation of the WNSN while, at the same time, increasing the overall network throughput. The proposed routing framework, which is based on a previously proposed medium access control protocol for the joint throughput and lifetime optimization in WNSNs, uses a hierarchical cluster-based architecture that offloads the network operation complexity from the individual nanosensors towards the cluster heads, or nano-controllers. This framework is based on the evaluation of the probability of saving energy through a multi-hop transmission, the tuning of the transmission power of each nanosensor for throughput and hop distance optimization, and the selection of the next hop nanosensor on the basis of their available energy and current load. The performance of this framework is also numerically evaluated in terms of energy, capacity, and delay, and compared to that of the single-hop communication for the same WNSN scenario. The results show how the energy per bit consumption and the achievable throughput can be jointly maximized by exploiting the peculiarities of this networking paradigm.