Energy model for communication via diffusion in nanonetworks

2011 IEEE Global Telecommunications Conference - GLOBECOM 2011, 2011

Diffusion-based molecular communication is a promising bio-inspired paradigm to implement nanonetworks, i.e., the interconnection of nanomachines. The peculiarities of the physical channel in diffusion-based molecular communication require the development of novel models, architectures and protocols for this new scenario, which need to be validated by simulation. With this purpose, we present N3Sim, a simulation framework for diffusion-based molecular communication. N3Sim allows to simulate scenarios where transmitters encode the information by releasing molecules into the medium, thus varying their local concentration. N3Sim models the movement of these molecules according to Brownian dynamics, and it also takes into account their inertia and the interactions among them. Receivers decode the information by sensing the particle concentration in their neighborhood. The benefits of N3Sim are multiple: the validation of channel models for molecular communication and the evaluation of novel modulation schemes are just a few examples.

2011

Communication via diffusion of molecules is an effective method for transporting information in nanonetworks. In this paper, novel modulation techniques called Concentration Shift Keying (CSK) and Molecule Shift Keying (MoSK) are proposed for coding and decoding information of the so-called messenger molecule concentration waves in nanonetworks. The first technique, CSK, modulates the information via the variation in the concentration of the messenger molecules whereas MoSK utilizes different types of messenger molecules to represent the information. Using simulation, the performance of these modulation techniques is evaluated in terms of susceptibility to noise and transmission power requirements. The new techniques achieve high channel capacity values, in particular, the MoSK technique exhibits more robustness against noise and requires less power.

Abstract—Nanotechnology has allowed building nanomachines capable of performing simple tasks, such as sensing, data storage or actuation. Nanonetworks, networks of nanomachines, will allow cooperation and information sharing among them, thereby greatly expanding the applications of nanotechnology in the biomedical, environmental and industrial fields. One of the most promising paradigms to implement nanonetworks is Diffusion-based Molecular Communication (DMC).

IEEE Transactions on NanoBioscience, 2000

Molecular communication is a new paradigm for communication between biological nanomachines over a nano-and microscale range. As biological nanomachines (or nanomachines in short) are too small and simple to communicate through traditional communication mechanisms (e.g., through sending and receiving of radio or infrared signals), molecular communication provides a mechanism for a nanomachine (i.e., a sender) to communicate information by propagating molecules (i.e., information molecules) that represent the information to a nanomachine (i.e., a receiver). This paper describes the design of an in vitro molecular communication system and evaluates various approaches to maximize the probability of information molecules reaching a receiver(s) and the rate of information reaching the receiver(s). The approaches considered in this paper include propagating information molecules (diffusion or directional transport along protein filaments), removing excessive information molecules (natural decay or receiver removal of excessive information molecules), and encoding and decoding approaches (redundant information molecules to represent information and to decode information). Two types of molecular communication systems are considered: a unicast system in which a sender communicates with a single receiver and a broadcast system in which a sender communicates with multiple receivers. Through exploring tradeoffs among the various approaches on the two types of molecular communication systems, this paper identifies promising approaches and shows the feasibility of an in vitro molecular communication system.

2012 12th International Conference on Computational Science and Its Applications, 2012

Abstract The scale limitations of conventional silicon based electromagnetic systems and the potential benefits of nanoscale devices, have spurred significant interest in studying nano-scale computation, electronics and communication. Nanonetworks, the interconnection of nanomachines, provide the means for cooperation and information sharing among tiny nanomachines, allowing them to fulfill more complex tasks. The ability to create communication networks of biological nanoscale devices has the potential to open up ...

International Journal of Computer Sciences and Engineering, 2017

Molecular Communication via diffusion (MCvD) is a new communication paradigm that uses molecules as the information carrier between the nano-machines. The end to end MolecUlar CommunicatIoN (MUCIN) simulator tool is used to explore the characteristics of the MCvD channel. This simulator considered Binary Concentration Shift Keying (BCSK) technique for modulating binary information symbols, support 1-dimensional environment, and send symbols consecutively. The main issues of MCvD system are the Inter-Symbol Interference that arises when the molecules belonging to the previous symbol come into the current symbol. Conventional MCvD system exhibits a long tail of received molecular histogram, results in higher ISI. In this paper, the displacement of a messenger molecule is increased to reduce the amount of stray molecules in the MCvD channel. The proposed technique shows the first hitting time distribution to determine the highest reception of the information carrying molecules by the receiver. We also evaluate the performance of proposed scheme for different values of step length in terms of Inter-Symbol Interference (ISI), symbol detection and communication delay. Our results indicate that introducing proposed technique significantly improves the performance of MCvD system.

IEEE Journal on Selected Areas in Communications, 2014

In this paper, a diffusion-based molecular communication channel between two nano-machines is considered. The effect of the amount of memory on performance is characterized, and a simple memory-limited decoder is proposed and its performance is shown to be close to that of the best possible imaginable decoder (without any restrictions on the computational complexity or its functional form), using Genie-aided upper bounds. This effect is specialized for the case of Molecular Concentration Shift Keying; it is shown that a four-bits memory achieves nearly the same performance as infinite memory. Then a general class of threshold decoders is considered and shown not to be optimal for a Poisson channel with memory, unless SNR is higher than a value specified in the paper. Another contribution is to show that receiver sampling at a rate higher than the transmission rate, i.e., a multi-read system, can significantly improve the performance. The associated decision rule for this system is shown to be a weighted sum of the samples during each symbol interval. The performance of the system is analyzed using the saddle point approximation. The best performance gains are achieved for an oversampling factor of three.

Proceedings of the 9th EAI International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS), 2016

In diffusion-based molecular communication (DBMC) system, information is encoded in the variation of molecules such as amounts, time shifts, or different molecule types, at a transmitter nanomachine (TN). These molecules are then released and propagated through a channel towards a receiver nanomachine (RN). One of the most important performance matrices in evaluating this system from an information theory perspective is channel capacity. This paper provides a derivation of capacity expression for multilayer DBMC channel in which the propagation of molecules from the TN to the RN through multiple channels follows the Brownian motion and modeled by Fick's equations. The Fourier transforms is employed to convert time to frequency domain functions. The results show that the maximum capacity can be obtained by increasing both the bandwidth and the average transmitted power, and decreasing the TN-RN distance.

2013

A nanonetwork is an interconnection of nano devices that are made up of nano-scale components. Several approaches for designing and implementing nanonetworks have been presented in recent years. Diffusion-based molecular communication is one of these approaches that use molecules as means of transmitting information in network. In diffusion-based molecular communication, molecules or particles diffuse in an aqueous environment under Fick's laws of diffusion to move from transmitter to receiver. In order to have full cooperation among nano devices, there must exist a communication path between every communicating pair. Hence, the primary aim of this study is to employ methods used for analyzing random networks to evaluate connectivity properties of nanonetworks that employ diffusion-based molecular communication techniques. Extensive simulations have been performed to investigate the effects of varying node density, number of particles released per node, and concentration threshold for detection at the nodes. The corresponding results in two and three-dimensional environments have been presented.

International Journal, 2013

Nano machines can be connected together in a nano network. Molecular communication provides the most practical way in which nano machines can communicate with each other. This paper presents a review of pioneering research work in mathematical modelling and channel characterization of molecular communication for nano networks. It is reported that propagation of molecules can be modelled as deterministic as well as stochastic processes. Channel performance metrics like channel capacity, mutual information, gain/delay etc. have been estimated by various research groups. However, these parameters must be validated by evaluation of physical systems. Certain challenging issues like Brownian motion with negative drift, synchronization and inter-symbol interference in molecular channel are still open for investigation. Functionalities of higher network layers like modulation, error correction, routing etc. are yet to be exploited.

2011

Nanonetworking is an emerging field of research, where nanotechnology and communication engineering are applied on a common ground. Molecular Communication (MC) is a bio-inspired paradigm, where Nanonetworks, i.e., the interconnection of devices at the nanoscale, are based on the exchange of molecules. Amongst others, diffusion-based MC is expected to be suitable for covering short distances (nm-µm). In this work, we explore the main characteristics of diffusion-based MC through the use of N3Sim, a physical simulation framework for MC. N3Sim allows for the simulation of the physics underlying the diffusion of molecules for different scenarios. Through the N3Sim results, the Linear Time Invariant (LTI) property is proven to be a valid assumption for the free diffusion-based MC scenario. Moreover, diffusion-based noise is observed and evaluated with reference to already proposed stochastic models. The optimal pulse shape for diffusion-based MC is provided as a result of simulations. Two different pulse-based coding techniques are also compared through N3Sim in terms of available bandwidth and energy consumption for communication.

Transactions on Emerging Telecommunications Technologies, 2016

This paper proposes 2 novel network coding approaches for diffusion-based nanonetworks. In these 2 methods, messages from nanomachines are jointly decoded at the receiver, and in one of the methods multiple molecule types are simultaneously employed to provide simultaneous communications over both nanomachine-to-relay and relay-to-nanomachine channels. As a result of the simultaneous use of the channel, each communication channel is allowed to use longer symbol intervals. This, in turn, results in a drastically reduced intersymbol interference component in all channels and enables communicating over longer ranges with higher data rates. The performance of the proposed communication system is investigated both analytically and via computer simulations.

Computer Networks, 2009

Nanotechnology is an emerging field of science devoted to provide new opportunities in a vast range of areas. In this paper, different techniques are proposed to enable the long range interconnection of nano-machines, deployed over distances from a few centimeters up to several meters. Long range nano-communications will enable the development of applications that could not be implemented using other techniques. The usage of both short-range nano techniques and long range micro techniques are not practical or are unfeasible for a huge application scope. Biologically inspired research provides promising features to long range communication, such as very low power consumption and biocompatibility. In this paper, several bio-inspired techniques are discussed following a twofold taxonomy divided according to whether a fixed physical link is required for signal propagation or not, i.e., either wired or wireless communication. In the first group, pheromones, spores, pollen and light transduction are discussed. In the second group, neuron-based communication techniques and capillaries flow circuit are explored. All proposed techniques offer a good framework for long-range molecular communication, and their components and test-beds can benefit from different research expertise, e.g., entomology for pheromones, mycology for spores, neuroscience for axons, and biochemistry for capillaries.

Simulation Modelling Practice and Theory, 2014

Diffusion-based molecular communication is a promising bio-inspired paradigm to implement nanonetworks, i.e., the interconnection of nanomachines. The peculiarities of the physical channel in diffusion-based molecular communication require the development of novel models, architectures and protocols for this new scenario, which need to be validated by simulation. N3Sim is a simulation framework for nanonetworks with transmitter, receiver, and harvester nodes using Diffusion-based Molecular Communication (DMC). In DMC, transmitters encode the information by releasing molecules into the medium, thus varying their local concentration. N3Sim models the movement of these molecules according to Brownian dynamics, and it also takes into account their inertia and the interactions among them. Harvesters collect molecules from the environment to reuse them for later transmissions. Receivers decode the information by sensing the particle concentration in their neighborhood. The benefits of N3Sim are multiple: the validation of channel models for DMC and the evaluation of novel modulation schemes are just a few examples.