Using Dimensional Analysis to Assess Scalability and Accuracy in Molecular Communication

In this paper, we apply dimensional analysis to study a diffusive molecular communication system that uses diffusing enzymes in the propagation environment to mitigate intersymbol interference. The enzymes bind to information molecules and then degrade them so that they cannot interfere with the detection of future transmissions at the receiver. We determine when it is accurate to assume that the concentration of information molecules throughout the receiver is constant and equal to that expected at the center of the receiver. We show that a lower bound on the expected number of molecules observed at the receiver can be arbitrarily scaled over the environmental parameters, and generalize how the accuracy of the lower bound is qualitatively impacted by those parameters.Comment: 6 pages, 2 figures, will be presented at the 3rd IEEE International Workshop on Molecular and Nanoscale Communications (MoNaCom 2013) in Budapest, Hungar

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

Optimal Receiver Design for Diffusive Molecular Communication With Flow and Additive Noise

In this paper, we perform receiver design for a diffusive molecular communication environment. Our model includes flow in any direction, sources of information molecules in addition to the transmitter, and enzymes in the propagation environment to mitigate intersymbol interference. We characterize the mutual information between receiver observations to show how often independent observations can be made. We derive the maximum likelihood sequence detector to provide a lower bound on the bit error probability. We propose the family of weighted sum detectors for more practical implementation and derive their expected bit error probability. Under certain conditions, the performance of the optimal weighted sum detector is shown to be equivalent to a matched filter. Receiver simulation results show the tradeoff in detector complexity versus achievable bit error probability, and that a slow flow in any direction can improve the performance of a weighted sum detector.Comment: 14 pages, 7 figures, 1 appendix. To appear in IEEE Transactions on NanoBioscience (submitted July 31, 2013, revised June 18, 2014, accepted July 7, 2014

On the Statistics of Reaction-Diffusion Simulations for Molecular Communication

A molecule traveling in a realistic propagation environment can experience stochastic interactions with other molecules and the environment boundary. The statistical behavior of some isolated phenomena, such as dilute unbounded molecular diffusion, are well understood. However, the coupling of multiple interactions can impede closed-form analysis, such that simulations are required to determine the statistics. This paper compares the statistics of molecular reaction-diffusion simulation models from the perspective of molecular communication systems. Microscopic methods track the location and state of every molecule, whereas mesoscopic methods partition the environment into virtual containers that hold molecules. The properties of each model are described and compared with a hybrid of both models. Simulation results also assess the accuracy of Poisson and Gaussian approximations of the underlying Binomial statistics.Comment: 6 pages, 1 table, 10 figures. Submitted to the 2nd ACM International Conference on Nanoscale Computing and Communication (ACM NANOCOM 2015) on May 16, 201

Diffusive Molecular Communication with Disruptive Flows

In this paper, we study the performance of detectors in a diffusive molecular communication environment where steady uniform flow is present. We derive the expected number of information molecules to be observed in a passive spherical receiver, and determine the impact of flow on the assumption that the concentration of molecules throughout the receiver is uniform. Simulation results show the impact of advection on detector performance as a function of the flow's magnitude and direction. We highlight that there are disruptive flows, i.e., flows that are not in the direction of information transmission, that lead to an improvement in detector performance as long as the disruptive flow does not dominate diffusion and sufficient samples are taken.Comment: 7 pages, 1 table, 5 figures. Will be presented at the 2014 IEEE International Conference on Communications (ICC) in Sydney, Australia, on September 12, 201

Bounds on Distance Estimation via Diffusive Molecular Communication

This paper studies distance estimation for diffusive molecular communication. The Cramer-Rao lower bound on the variance of the distance estimation error is derived. The lower bound is derived for a physically unbounded environment with molecule degradation and steady uniform flow. The maximum likelihood distance estimator is derived and its accuracy is shown via simulation to perform very close to the Cramer-Rao lower bound. An existing protocol is shown to be equivalent to the maximum likelihood distance estimator if only one observation is made. Simulation results also show the accuracy of existing protocols with respect to the Cramer-Rao lower bound.Comment: 7 pages, 5 figures, 1 table. Will be presented at the 2014 IEEE Global Communications Conference (GLOBECOM) in Austin, TX, USA, on December 9, 201

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

A Unifying Model for External Noise Sources and ISI in Diffusive Molecular Communication

This paper considers the impact of external noise sources, including interfering transmitters, on a diffusive molecular communication system, where the impact is measured as the number of noise molecules expected to be observed at a passive receiver. A unifying model for noise, multiuser interference, and intersymbol interference is presented, where, under certain circumstances, interference can be approximated as a noise source that is emitting continuously. The model includes the presence of advection and molecule degradation. The time-varying and asymptotic impact is derived for a series of special cases, some of which facilitate closed-form solutions. Simulation results show the accuracy of the expressions derived for the impact of a continuously-emitting noise source, and show how approximating intersymbol interference as a noise source can simplify the calculation of the expected bit error probability of a weighted sum detector.Comment: 14 pages, 7 figures, 4 tables, 1 appendix. To appear in IEEE Journal on Selected Areas in Communications (JSAC). Submitted October 21, 2013, revised April 21, 2014, accepted June 3, 201

Multi-Scale Stochastic Simulation for Diffusive Molecular Communication

Recently, hybrid models have emerged that combine microscopic and mesoscopic regimes in a single stochastic reaction-diffusion simulation. Microscopic simulations track every individual molecule and are generally more accurate. Mesoscopic simulations partition the environment into subvolumes, track when molecules move between adjacent subvolumes, and are generally more computationally efficient. In this paper, we present the foundation of a multi-scale stochastic simulator from the perspective of molecular communication, for both mesoscopic and hybrid models, where we emphasize simulation accuracy at the receiver and efficiency in regions that are far from the communication link. Our multi-scale models use subvolumes of different sizes, between which we derive the diffusion event transition rate. Simulation results compare the accuracy and efficiency of traditional approaches with that of a regular hybrid method and with those of our proposed multi-scale methods.Comment: 7 pages, 2 tables, 6 figures. Will be presented at the 2015 IEEE International Conference on Communications (ICC) in June 201

Encoding and Decoding Mixed Bandlimited Signals using Spiking Integrate-and-Fire Neurons

Conventional sampling focuses on encoding and decoding bandlimited signals by recording signal amplitudes at known time points. Alternately, sampling can be approached using biologically-inspired schemes. Among these are integrate-and-fire time encoding machines (IF-TEMs). They behave like simplified versions of spiking neurons and encode their input using spike times rather than amplitudes. Moreover, when multiple of these neurons jointly process a set of mixed signals, they form one layer in a feedforward spiking neural network. In this paper, we investigate the encoding and decoding potential of such a layer. We propose a setup to sample a set of bandlimited signals, by mixing them and sampling the result using different IF-TEMs. We provide conditions for perfect recovery of the set of signals from the samples in the noiseless case, and suggest an algorithm to perform the reconstruction.Comment: To appear in ICASSP 2020. Code is available at https://github.com/karenadam/Multi-Channel-Time-Encodin