Search

Unique Word-orthogonal frequency division multiplexing (UW-OFDM) is known to provide various performance benefits over conventional cyclic prefix (CP) based OFDM. Most important, UW-OFDM features excellent spectral sidelobe suppression properties and an outstanding bit error ratio (BER) performance. Carrier frequency offset (CFO) induced impairments denote a challenging task for OFDM systems of any kind. In this work we investigate the CFO effects on UW-OFDM and compare it to conventional multi-carrier and single-carrier systems. Different CFO compensation approaches with different computational complexity are considered throughout this work and assessed against each other. A mean squared error analysis carried out after data estimation reveals a significant higher robustness of UW-OFDM over CP-OFDM against CFO effects. Additionally, the conducted BER simulations generally support this conclusion for various scenarios, ranging from uncoded to coded transmission in a frequency selective environment.

In this paper, we propose novel Transmitter (Tx) models for Molecular Communication (MC) systems based on functionalized Nanoparticles (NPs). Current Tx models often rely on simplifying assumptions for the molecule release and replenishment mechanisms. In contrast, we propose a Tx model where the signaling molecule release is controlled by a switchable membrane driven by an external trigger. Moreover, we propose a reloading mechanism, where signaling molecules are harvested based on an enzymatic reaction. Hence, no repeated injection of signaling molecules is required. For the proposed Tx model, we develop a general mathematical description in terms of a discrete-time transfer function model. Furthermore, we investigate two realizations of the proposed Tx model, i.e., an idealized Tx relying on simplifying assumptions, and a realistic Tx employing practical components for the reloading and release mechanisms. Finally, we numerically evaluate the proposed model and compare our results to stochastic Particle Based Simulations (PBSs)., Comment: 7 pages, 7 figures. submitted to 9th ACM International Conference on Nanoscale Computing and Communication, Barcelona, Catalunya, Spain

Molecular communications is a promising framework for the design of controlled-release drug delivery systems. Under this framework, drug carriers, diseased cells, and the channel are modeled as transmitters, absorbing receivers, and diffusive channel, respectively. In this paper, we investigate diffusion-based spherical matrix-type drug carriers, which are employed in medical applications. In a matrix carrier, the drug molecules are dispersed in the matrix core and diffuse from the inner to the outer layers of the carrier once immersed in a dissolution medium. We derive the channel response of the matrix carrier transmitter for an absorbing receiver and compare our results with commonly used point and transparent spherical transmitters to highlight the necessity of considering practical models. Furthermore, we derive a criterion for evaluating whether the release process or the channel dynamics are more important for the characteristics of the channel response of a drug delivery system. For the limiting regimes, where only the release process or the channel determine the behavior of the end-to-end system, we propose closed-form approximations for the channel response. Finally, we investigate the channel responses for the release of common therapeutic drugs, e.g., doxorubicin, from a diblock copolymer micelle acting as drug carrier., Comment: 30 pages, 8 figures, 2 tables, Submitted for possible journal publication in IEEE Transactions on Molecular, Biological and Multi-Scale Communications. arXiv admin note: text overlap with arXiv:2104.05332

Molecular communications is a promising framework for the design of controlled-release drug delivery systems. In this framework, drug carriers are modeled as transmitters, the diseased cells as absorbing receivers, and the channel between transmitter and receiver as diffusive channel. However, existing works on drug delivery systems consider only simple drug carrier models, which limits their practical applicability. In this paper, we investigate diffusion-based spherical matrix-type drug carriers, which are employed in practice. In a matrix carrier, the drug molecules are dispersed in the matrix and diffuse from the inner to the outer layers of the carrier once immersed in a dissolution medium. We derive the channel response of the matrix carrier transmitter for an absorbing receiver and validate the results through particle-based simulations. Moreover, we show that a transparent spherical transmitter, with the drug molecules uniformly distributed over the entire volume, is as special case of the considered matrix system. For this case, we provide an analytical expression for the channel response. Finally, we compare the channel response of the matrix transmitter with those of point and transparent spherical transmitters to reveal the necessity of considering practical models., Comment: 6 pages, 5 figures, submitted to 2021 IEEE Global Communications Conference

Droplet-based microfluidic systems are a promising platform forlab-on-a-chip (LoC) applications. These systems can also be used toenhance LoC applications with integrated droplet control information or for data transmission scenarios in the context of molecular communication. For both use-cases the detection and characterisation of droplets in small microfluidic channels is crucial. So far, only complex lab setups with restricted capabilities have been presented as detection devices. We present a new low-cost and portable droplet detector. The device is used to confidently distinguish between individual droplets in a droplet-based microfluidic system. Using on-off keying a 16-bit sequence is successfully transmittedfor the first time with such a setup. Furthermore, the devices capabilities to characterise droplets regarding colour and size are demonstrated. Such an application of a spectral sensor in a microfluidic system presents new possibilities, such as colour-coded data transmission or analysis of droplet content.

Unique word-orthogonal frequency division multiplexing (UW-OFDM) is known to provide various performance benefits over conventional OFDM using cyclic prefixes (CP). Most important, UW-OFDM features excellent spectral sidelobe suppression properties and an outstanding bit error ratio performance. Current research has mainly focused on principle performance bounds of UW-OFDM, with less attention on challenges aside from idealized communication scenarios, such as system parameter estimation tasks. In this work we present an approach for including frequency pilots tones into the UW-OFDM signaling scheme, which can then be utilized for these estimation tasks. Suitable optimization criteria are presented and interactions of pilots with data symbols are highlighted. Pilot tone based estimation of a carrier frequency offset (CFO) is conducted as an estimation example, revealing considerable differences to conventional OFDM. Simulation results in a multipath environment demonstrate a significantly increased estimation accuracy in UW-OFDM over CP-OFDM, which becomes even more dominant with an increasing CFO. This performance difference is due to the inherent redundancy present in an UW-OFDM signal.

The derivation of suitable analytical models is an important step for the design and analysis of molecular communication systems. However, many existing models have limited applicability in practical scenarios due to various simplifications (e.g., assumption of an unbounded environment). In this paper, we develop a realistic model for particle diffusion in a bounded sphere and particle transport through a semi-permeable boundary. This model can be used for various applications, such as modeling of inter-/intra-cell communication or the release process of drug carriers. The proposed analytical model is based on a transfer function approach, which allows for fast numerical evaluation and provides insights into the impact of the relevant molecular communication system parameters. The proposed solution of the bounded spherical diffusion problem is formulated in terms of a state-space description and the semi-permeable boundary is accounted for by a feedback loop. Particle-based simulations verify the proposed modeling approach., Comment: 7 pages, 6 figures, Submitted to IEEE International Conference on Communications (ICC 2020), Dublin, Ireland

Stochastic computing (SC) is a promising candidate for fault tolerant computing in digital circuits. We present a novel stochastic computing estimation architecture allowing to solve a large group of estimation problems including least squares estimation as well as sparse estimation. This allows utilizing the high fault tolerance of stochastic computing for implementing estimation algorithms. The presented architecture is based on the recently proposed linearized-Bregman-based Sparse Kaczmarz algorithm. To realize this architecture, we develop a shrink function in stochastic computing and analytically describe its error probability. We compare the stochastic computing architecture to a fixed-point binary implementation and present bit-true simulation results as well as synthesis results demonstrating the feasibility of the proposed architecture for practical implementation.

The complexity of droplet microfluidics grows by implementing parallel processes and multiple functionalities on a single device. This poses a challenge to the engineer designing the microfluidic networks. In today's design processes, the engineer relies on calculations, assumptions, simplifications, as well as his/her experiences and intuitions. In order to validate the obtained specification of the microfluidic network, usually a prototype is fabricated and physical experiments are conducted thus far. In case the design does not implement the desired functionality, this prototyping iteration is repeated - obviously resulting in an expensive and time-consuming design process. In order to avoid unnecessary prototyping loops, simulation methods could help to validate the specification of the microfluidic network before any prototype is fabricated. However, state-of-the-art simulation tools come with severe limitations, which prevent their utilization for practically-relevant applications. More precisely, they are often not dedicated to droplet microfluidics, cannot handle the required physical phenomena, are not publicly available, and can hardly be extended. In this work, we present an advanced simulation approach for droplet microfluidics which addresses these shortcomings and, eventually, allows to simulate practically-relevant applications. To this end, we propose a simulation framework which directly works on the specification of the design, supports essential physical phenomena, is publicly available, and easy to extend. Evaluations and case studies demonstrate the benefits of the proposed simulator: While current state-of-the-art tools were not applicable for practically-relevant microfluidic networks, the proposed solution allows to reduce the design time and costs e.g. of a drug screening device from one person month and USD 1200, respectively, to just a fraction of that., Comment: preprint

In this paper, we consider molecular communications in one-dimensional flow-induced diffusion channels with a perfectly absorbing receiver. In such channels, the random propagation delay until the molecules are absorbed follows an inverse Gaussian (IG) distribution and is referred to as first hitting time. Knowing the distribution for the difference of the first hitting times of two molecules is very important if the information is encoded by a limited set of molecules and the receiver exploits their arrival time and/or order. Hence, we propose a moment matching approximation by a normal inverse Gaussian (NIG) distribution and we derive an expression for the asymptotic tail probability. Numerical evaluations showed that the NIG approximation matches very well with the exact solution obtained by numerical convolution of the IG density functions. Moreover, the asymptotic tail probability outperforms state-of-the-art tail approximations., Comment: This paper has been submitted to IEEE Transactions on Molecular, Biological and Multi-Scale Communications

In this work, we present a novel inner product design for stochastic computing. Stochastic computing is an emerging computing technique, that encodes a number in the probability of observing a one in a random bit stream. This leads to reduced hardware costs and high error tolerance. The proposed inner product design is based on a two-line bipolar encoding format and applies sequential processing of the input in a central accumulation unit. Sequential processing significantly increases the computation accuracy, since it allows for preliminary cancelation of carry bits. Moreover, the central accumulation unit gives a much better scalability compared to conventional adder tree approaches. We show that the proposed inner product design outperforms state-of-the-art designs in terms of hardware costs for high accuracy requirements and fault tolerance., Comment: This paper has been submitted to IEEE Transactions on Circuits and Systems II: Express Briefs

In stochastic computing (SC), a real-valued number is represented by a stochastic bit stream, encoding its value in the probability of obtaining a one. This leads to a significantly lower hardware effort for various functions and provides a higher tolerance to errors (e.g., bit flips) compared to binary radix representation. The implementation of a stochastic max/min function is important for many areas where SC has been successfully applied, such as image processing or machine learning (e.g., max pooling in neural networks). In this work, we propose a novel shift-register-based architecture for a stochastic max/min function. We show that the proposed circuit has a significantly higher accuracy than state-of-the-art architectures at comparable hardware cost. Moreover, we analytically proof the correctness of the proposed circuit and provide a new error analysis, based on the individual bits of the stochastic streams. Interestingly, the analysis reveals that for a certain practical bit stream length a finite optimal shift register length exists and it allows to determine the optimal length.

Motivated by the numerous healthcare applications of molecular communication within Internet of Bio-Nano Things (IoBNT), this work addresses the problem of abnormality detection in a blood vessel using multiple biological embedded computing devices called cooperative biological nanomachines (CNs), and a common receiver called the fusion center (FC). Due to blood flow inside a vessel, each CN and the FC are assumed to be mobile. In this work, each of the CNs perform abnormality detection with certain probabilities of detection and false alarm by counting the number of molecules received from a source, e.g., infected tissue. These CNs subsequently report their local decisions to a FC over a diffusion-advection blood flow channel using different types of molecules in the presence of inter-symbol interference, multi-source interference, and counting errors. Due to limited computational capability at the FC, OR and AND logic based fusion rules are employed to make the final decision after obtaining each local decision based on the optimal likelihood ratio test. For the aforementioned system, probabilities of detection and false alarm at the FC are derived for OR and AND fusion rules. Finally, simulation results are presented to validate the derived analytical results, which provide important insights., Comment: Submitted to IEEE Transactions on Molecular, Biological, and Multi-Scale Communications Letters for possible publication

This work considers the problem of flow-induced diffusive molecular communication under various mobility conditions such as (i) both transmitter (TX) and receiver (RX) nanomachines are mobile, (ii) TX is mobile and RX is fixed, and (iii) TX is fixed and RX is mobile. Closed-form expressions for the probability density function (PDF) of the first hitting time under the aforementioned mobile scenarios are derived, by characterizing the movement of the nanomachines and information molecules using Brownian motion with positive drift. The derived PDF expressions are validated through particle-based simulations. Based on these results, the performance of molecular communication with on-off keying (OOK) modulation in flow-induced diffusive channels is investigated. In particular, closed-form expressions for the probabilities of detection and false alarm with optimal Likelihood ratio test (LRT) based decision rule, probability of error, and the capacity in the presence of inter-symbol interference, counting errors, and noise from the other sources are derived. Simulation results are presented to verify the theoretical results and to yield insights into the system performance for different mobility conditions., Comment: Submitted to IEEE Transactions on Molecular, Biological, and Multi-Scale Communications

Motivated by the numerous healthcare applications of molecular communication (MC) inside blood vessels, this work considers relay/cooperative nanomachine (CN)-assisted mobile MC between a source nanomachine (SN) and a destination nanomachine (DN) where each nanomachine is mobile in a flow-induced diffusive channel. Using the first hitting time model, the impact of an intermediate CN on the performance of the CN-assisted diffusive mobile MC system with fully absorbing receivers is analyzed in the presence of inter-symbol interference, multi-source interference, and counting errors. For this purpose, the likelihood ratio test based optimal symbol detection scheme is obtained at the DN considering the non-ideal nature of CN, i.e., CN can be in error with a finite probability. Further, to characterize the system performance, closed-form expressions for the end-to-end probabilities of detection and false alarm at the DN are derived between the SN-DN pair incorporating the detection performance of the intermediate CN. In addition, the channel capacity expression is also derived for the aforementioned scenario. Simulation results are presented to corroborate the theoretical results derived and also, to yield insights into system performance., Comment: Submitted to 2018 Asilomar Conference

In this work, we consider diffusion-based molecular communication with and without drift between two static nano-machines. We employ type-based information encoding, releasing a single molecule per information bit. At the receiver, we consider an asynchronous detection algorithm which exploits the arrival order of the molecules. In such systems, transposition errors fundamentally undermine reliability and capacity. Thus, in this work we study the impact of transpositions on the system performance. Towards this, we present an analytical expression for the exact bit error probability (BEP) caused by transpositions and derive computationally tractable approximations of the BEP for diffusion-based channels with and without drift. Based on these results, we analyze the BEP when background is not negligible and derive the optimal bit interval that minimizes the BEP. Simulation results confirm the theoretical results and show the error and goodput performance for different parameters such as block size or noise generation rate., Comment: This paper has been submitted to IEEE Transactions on Communications