Improving Diffusion-Based Molecular Communication with Unanchored Enzymes

In this paper, we propose adding enzymes to the propagation environment of a diffusive molecular communication system as a strategy for mitigating intersymbol interference. The enzymes form reaction intermediates with information molecules and then degrade them so that they have a smaller chance of interfering with future transmissions. We present the reaction-diffusion dynamics of this proposed system and derive a lower bound expression for the expected number of molecules observed at the receiver. We justify a particle-based simulation framework, and present simulation results that show both the accuracy of our expression and the potential for enzymes to improve communication performance.Comment: 15 pages, 4 figures, presented at the 7th International Conference on Bio-Inspired Models of Network, Information, and Computing Systems (BIONETICS 2012) in Lugano, Switzerlan

Low-complexity non-coherent signal detection for nano-scale molecular communications

Nano-scale molecular communication is a viable way of exchanging information between nano-machines. In this letter, a low-complexity and non-coherent signal detection technique is proposed to mitigate the intersymbol-interference (ISI) and additive noise. In contrast to existing coherent detection methods of high complexity, the proposed non-coherent signal detector is more practical when the channel conditions are hard to acquire accurately or hidden from the receiver. The proposed scheme employs the concentration difference to detect the ISI corrupted signals and we demonstrate that it can suppress the ISI effectively. The concentration difference is a stable characteristic, irrespective of the diffusion channel conditions. In terms of complexity, by excluding matrix operations or likelihood calculations, the new detection scheme is particularly suitable for nano-scale molecular communication systems with a small energy budget or limited computation resource

Improving Receiver Performance of Diffusive Molecular Communication with Enzymes

This paper studies the mitigation of intersymbol interference in a diffusive molecular communication system using enzymes that freely diffuse in the propagation environment. The enzymes form reaction intermediates with information molecules and then degrade them so that they cannot interfere with future transmissions. A lower bound expression on the expected number of molecules measured at the receiver is derived. A simple binary receiver detection scheme is proposed where the number of observed molecules is sampled at the time when the maximum number of molecules is expected. Insight is also provided into the selection of an appropriate bit interval. The expected bit error probability is derived as a function of the current and all previously transmitted bits. Simulation results show the accuracy of the bit error probability expression and the improvement in communication performance by having active enzymes present.Comment: 13 pages, 8 figures, 1 table. To appear in IEEE Transactions on Nanobioscience (submitted January 22, 2013; minor revision October 16, 2013; accepted December 4, 2013

Local convexity inspired low-complexity non-coherent signal detector for nano-scale molecular communications

Molecular communications via diffusion (MCvD) represents a relatively new area of wireless data transfer with especially attractive characteristics for nanoscale applications. Due to the nature of diffusive propagation, one of the key challenges is to mitigate inter-symbol interference (ISI) that results from the long tail of channel response. Traditional coherent detectors rely on accurate channel estimations and incur a high computational complexity. Both of these constraints make coherent detection unrealistic for MCvD systems. In this paper, we propose a low-complexity and noncoherent signal detector, which exploits essentially the local convexity of the diffusive channel response. A threshold estimation mechanism is proposed to detect signals blindly, which can also adapt to channel variations. Compared to other noncoherent detectors, the proposed algorithm is capable of operating at high data rates and suppressing ISI from a large number of previous symbols. Numerical results demonstrate that not only is the ISI effectively suppressed, but the complexity is also reduced by only requiring summation operations. As a result, the proposed noncoherent scheme will provide the necessary potential to low-complexity molecular communications, especially for nanoscale applications with a limited computation and energy budget

Diffusion-based physical channel Identification for Molecule Nanonetworks

Català: El treball és una exploració del canal de difusió molecular per nanoredes moleculars, en el qual s'identifica la resposta impulsional i en freqüència del canal, es comprova la seva linealitat i invariància i s'extreuen les principals característiques de comunicació. S'avaluen diferents tècniques de modulació.Castellano: El trabajo es una exploración del canal de difusión molecular para nanoredes moleculares, en el cual se identifica la respuesta impulsional y en frecuencia del canal, se comprueba su linealidad e invarianza y se extraen las principales características de comunicación. Se evalúan diferentes técnicas de modulación.English: In this work, the diffusion-based MC channel is explored in order to extract its main communication metrics, such as attenuation and delay with respect to frequency and distance. The LTI property is proven to be a valid assumption for normal diffusion-based single/multi-transmitter scenarios. Different pulse-based modulation techniques are compared by means of throughput, operation range, energy requirements and ISI, and the optimal pulse shape for these modulations is provided. Finally, interferences are evaluated in a broadcast communication scenario and diffusion-based noise is observed and assessed with reference to already proposed stochastic models.The exploration of the physical diffusion-based communication channel is based on simulations

On the scalability limits of communication networks to the nanoscale

Nanosystems, integrated systems with a total size of a few micrometers, are capable of interacting at the nanoscale, but their short operating range limits their usefulness in practical macro-scale scenarios. Nanonetworks, the interconnection of nanosystems, will extend their range of operation by allowing communication among nanosystems, thereby greatly enhancing their potential applications. In order to integrate communication capabilities into nanosystems, their communication subsystem needs to shrink to a size of a few micrometers. There are doubts about the feasibility of scaling down current metallic antennas to such a small size, mainly because their resonant frequency would be extremely high (in the optical domain) leading to a large free-space attenuation of the radiated EM waves. In consequence, as an alternative to implement wireless communications among nanosystems, two novel paradigms have emerged: molecular communication and graphene-enabled wireless communications. On the one hand, molecular communication is based on the exchange of molecules among nanosystems, inspired by communication among living cells. In Diffusion-based Molecular Communication (DMC), the emitted molecules propagate throughout the environment following a diffusion process until they reach the receiver. On the other hand, graphene, a one-atom-thick sheet of carbon atoms, has been proposed to implement graphene plasmonic RF antennas, or graphennas. Graphennas with a size in the order of a few micrometers show plasmonic effects which allow them to radiate EM waves in the terahertz band. Graphennas are the enabling technology of Graphene-enabled Wireless Communications (GWC). In order to answer the question of how communication networks will scale when their size shrinks, this thesis presents a scalability analysis of the performance metrics of communication networks to the nanoscale, following a general model with as few assumptions as possible. In the case of DMC, two detection schemes are proposed: amplitude detection and energy detection. Key performance metrics are identified and their scalability with respect to the transmission distance is found to differ significantly from the case of traditional wireless communications. These unique scaling trends present novel challenges which require the design of novel networking protocols specially adapted to DMC networks. The analysis of the propagation of plasmonic waves in graphennas allows determining their radiation performance. In particular, the resonant frequency of graphennas is not only lower than in metallic antennas, but it also increases more slowly as their length is reduced to the nanoscale. Moreover, the study of parameters such as the graphenna dimensions, the relaxation time of graphene and the applied chemical potential shows the tunability of graphennas in a wide frequency range. Furthermore, an experimental setup to measure graphennas based on feeding them by means of a photoconductive source is described. The effects of molecular absorption in the short-range terahertz channel, which corresponds to the expected operating scenario of graphennas, are analyzed. Molecular absorption is a process in which molecules present in the atmosphere absorb part of the energy of the terahertz EM waves radiated by graphennas, causing impairments in the performance of GWC. The study of molecular absorption allows quantifying this loss by deriving relevant performance metrics in this scenario, which show novel scalability trends as a function of the transmission distance with respect to the case of free-space propagation. Finally, the channel capacity of GWC is found to scale better as the antenna size is reduced than in traditional wireless communications. In consequence, GWC will require lower transmission power to achieve a given performance target. These results establish a general framework which may serve designers as a guide to implement wireless communication networks among nanosystems

Fundamentals of diffusion-based molecular communication in nanonetworks

Molecular communication (MC) is a promising bio-inspired paradigm for the exchange of information among nanotechnology-enabled devices. These devices, called nanomachines, are expected to have the ability to sense, compute and actuate, and interconnect into networks, called nanonetworks, to overcome their individual limitations and benefit from collaborative efforts. MC realizes the exchange of information through the transmission, propagation, and reception of molecules, and it is proposed as a feasible solution for nanonetworks. This idea is motivated by the observation of nature, where MC is successfully adopted by cells for intracellular and intercellular communication. MC-based nanonetworks have the potential to be the enabling technology for a wide range of applications, mostly in the biomedical, but also in the industrial and surveillance fields. The focus of this Ph.D. thesis is on the most fundamental type of MC, i.e., diffusion-based MC, where the propagation of information-bearing molecules between a transmitter and a receiver is realized through free diffusion in a fluid. The objectives of the research presented in this thesis are to analyze the MC paradigm from the point of view of communication engineering and information theory, and to provide solutions to the modeling and design of MC-based nanonetworks. First, a physical end-to-end model is realized to study each component in a basic diffusion-based MC system design, as well as the overall system, in terms of gain and delay. Second, the noise sources affecting a diffusion-based MC are identified and statistically modeled. Third, upper/lower bounds to the capacity are derived to evaluate the information-theoretic performance of diffusion-based MC. Fourth, a stochastic analysis of the interference when multiple transmitters access the diffusion-based MC channel is provided. Fifth, as a proof of concept, a design of a diffusion-based MC system built upon genetically-engineered biological circuits is analyzed. This research provides fundamental results that establish a basis for the modeling, design, and realization of future MC-based nanonetworks, as novel technologies and tools are being developed.Ph.D