Showing papers in "IEEE Transactions on Molecular, Biological, and Multi-Scale Communications in 2020"

A Comprehensive Survey on Hybrid Communication in Context of Molecular Communication and Terahertz Communication for Body-Centric Nanonetworks

Abstract: With the huge advancement of nanotechnology over the past years, the devices are shrinking into micro-scale, even nano-scale. Additionally, the Internet of nano-things (IoNTs) are generally regarded as the ultimate formation of the current sensor networks and the development of nanonetworks would be of great help to its fulfilment, which would be ubiquitous with numerous applications in all domains of life. However, the communication between the devices in such nanonetworks is still an open problem. Body-centric nanonetworks are believed to play an essential role in the practical application of IoNTs. BCNNs are also considered as domain specific like wireless sensor networks and always deployed on purpose to support a particular application. In these networks, electromagnetic and molecular communications are widely considered as two main promising paradigms and both follow their own development process. In this survey, the recent developments of these two paradigms are first illustrated in the aspects of applications, network structures, modulation techniques, coding techniques and security to then investigate the potential of hybrid communication paradigms. Meanwhile, the enabling technologies have been presented to apprehend the state-of-art with the discussion on the possibility of the hybrid technologies. Additionally, the inter-connectivity of electromagnetic and molecular body-centric nanonetworks is discussed. Afterwards, the related security issues of the proposed networks are discussed. Finally, the challenges and open research directions are presented.

3-D Diffusive Molecular Communication With Two Fully-Absorbing Receivers: Hitting Probability and Performance Analysis

Abstract: Exact analytical channel models for molecular communication via diffusion (MCvD) systems involving multiple fully absorbing receivers (FARs) in a three-dimensional (3-D) medium are hard to obtain due to the mathematical intractability of corresponding diffusion equations. Therefore, this work considers an MCvD system with two spherical FARs in a 3-D diffusion-limited medium and develop several insights using an approximate analytical expression for the hitting probability of information molecule (IM). Further, based on the hitting probability, a novel approximate closed-form analytical expression for the area under the receiver operating characteristic curve (AUC) is derived to analyze the detection performance at each FAR in the presence of other FAR. Finally, simulation results are presented to validate the analytical results using the particle-based and Monte-Carlo simulations and to yield important insights into the MCvD system performance with two FARs.

Generalized Molecular-Shift Keying (GMoSK): Principles and Performance Analysis

Abstract: A generalized molecular-shift keying (GMoSK) modulation scheme is proposed for supporting diffusive molecular communication (DMC). Instead of activating one type of molecules in the traditional molecule shift keying (MoSK) modulation, GMoSK simultaneously activates several types of molecules, with the objective to increase data rate and the potential to further mitigate inter-symbol interference (ISI) beyond MoSK. For signal detection in the GMoSK-modulated DMC (GMoSK-DMC) systems, we first derive a symbol-based idealized maximum likelihood (IML) detector, from which we then deduce two practical detection schemes, namely, the zero-level decision feedback maximum likelihood (ZDF/ML) detector and the one-level decision feedback maximum likelihood (1DF/ML) detector. The error performance of the GMoSK-DMC systems with the IML- and ZDF/ML-detectors is mathematically analyzed. Furthermore, the error performance of the GMoSK-DMC systems with our proposed detection schemes is investigated and compared, which is also compared with that of the DMC systems employing the legacy MoSK modulation, the binary concentration shift keying (BCSK) modulation, the depleted MoSK (D-MoSK) modulation, and the Molecule-as-a-Frame (MaaF) modulation. Our studies and performance results demonstrate that GMoSK has the potential to achieve the performance beyond the above four modulation schemes, and employs the merit of high-flexibility for attaining relatively high data rate and also for ISI mitigation.

Is Information in the Brain Represented in Continuous or Discrete Form

Abstract: The question of continuous-versus-discrete information representation in the brain is a fundamental yet unresolved question. Historically, most analyses assume a continuous representation without considering the discrete alternative. Our work explores the plausibility of both, answering the question from a communications systems engineering perspective. Using Shannon’s communications theory, we posit that information in the brain is represented in discrete form. We address this hypothesis using 2 approaches. First, we identify the fundamental communication requirements of the brain. Second, we estimate the symbol error probability and channel capacity for a continuous information representation. Our work concludes that information cannot be communicated and represented reliably in the brain using a continuous representation – it has to be in a discrete form. This is a major demarcation from conventional and current wisdom. We apply this discrete result to the 4 major neural coding hypotheses, and illustrate the use of discrete ISI neural coding in analyzing electrophysiology experimental data. We further posit and illustrate a plausible direct link between Weber’s Law and discrete neural coding. We end by outlining a number of key research questions on discrete neural coding.

Molecular Type Permutation Shift Keying for Molecular Communication

Abstract: Molecular communication (MC) via diffusion is envisioned to be a new paradigm for information exchange in the future nanonetworks. However, the strong inter-symbol interference (ISI) caused by the diffusion channel significantly deteriorates the performance of MC systems. To this end, we propose a novel modulation technique to reduce the ISI effect, termed as molecular type permutation shift keying (MTPSK), which encodes information on the permutations of multiple types of molecules. We design a Genie-aided maximum-likelihood detector and a conventional maximum-likelihood detector, and analyze their performance in terms of bit error rate (BER). Aiming at lower computational complexity, we further design a low-complexity maximum-likelihood detector using a Viterbi-like algorithm with compromised error performance. BER simulation results corroborate that the proposed MTPSK can outperform the prevailing modulation schemes for MC, including molecular shift keying (MoSK), concentration shift keying, depleted MoSK, and pulse position modulation.

Capacities and Optimal Input Distributions for Particle-Intensity Channels

Abstract: This work introduces the particle-intensity channel (PIC) as a new model for molecular communication systems that includes imperfections at both transmitter and receiver and provides a new characterization of the capacity limits as well as properties of the optimal (capacity-achieving) input distributions for such channels. In the PIC, the transmitter encodes information, in symbols of a given duration, based on the probability of particle release, and the receiver detects and decodes the message based on the number of particles detected during the symbol interval. In this channel, the transmitter may be unable to control precisely the probability of particle release, and the receiver may not detect all the particles that arrive. We model this channel using a generalization of the binomial channel and show that the capacity-achieving input distribution for this channel always has mass points at probabilities of particle release of zero and one. To find the capacity-achieving input distributions, we develop a novel and efficient algorithm we call dynamic assignment Blahut-Arimoto (DAB). For diffusive particle transport, we also derive the conditions under which the input with two mass points is capacity-achieving.

All-Optical Cochlear Implants

Abstract: In the present work, we introduce a novel cochlear implant (CI) architecture, namely all-optical CI (AOCI), which directly converts acoustic to optical signals capable of stimulating the cochlear neurons. First, we describe the building-blocks (BBs) of the AOCI, and explain their functionalities as well as their interconnections. Next, we present a comprehensive system model that incorporates the technical characteristics and constraints of each BB, the transdermal-optical-channel particularities, i.e., optical path-loss and external-implanted device stochastic pointing-errors, and the cochlear neurons biological properties. Additionally, in order to prove the feasibility of the AOCI architecture, we conduct a link-budget analysis that outputs novel closed-form expressions for the instantaneous and average photon flux that is emitted on the cochlear neurons. Likewise, we define three new key-performance-indicators (KPIs), namely probability of hearing, probability of false-hearing, and probability of neural damage. The proposed theoretical framework is verified through respective simulations, which not only quantify the efficiency of the proposed architecture, but also reveal an equilibrium between the optical transmission power and the patient’s safety, as well as the AOCI BBs specifications. Finally, it is highlighted that the AOCI approach is greener and safer than the conventional CIs.

Wireless Communication in Nanonetworks: Current Status, Prospect and Challenges

Abstract: As candidate new wireless communication schemes, the molecular communication (MC) and nano-electromagnetic communication (NEC) get more and more attention. Benefit from the special communication framework, several high-value applications like healthcare monitoring and drug delivery, plants and animals monitoring, and detect and manage the corrosion of pipe can be imaged which serve the people, environment and industry from the view of nanoscale transmission. However, considered the specific information carrier, new channel characters and nanoscale transmitter and receiver, obviously the gap from theory to practice can also be imaged. In this paper, we firstly describe the requirements for MC and NEC from the vision of next generation wireless communication. Based on the requirements, five potential applications have been presented and finally, we point out some challenges from theory to practice. We hope to find out the nearest path of MC and NEC from academic research to people’s real life.

Anomaly Detection in Molecular Communications With Applications to Health Monitoring Networks

Abstract: Early detection of diseases such as cancer plays a crucial role in their successful treatment Motivated by this, anomaly detection in molecular nano-networks is studied The proposed anomaly detection is, in fact, a two-tier network of artificial cells (ACs) in the first tier and a bio-cyber interface (BC) in the second tier The ACs detect anomaly by variation in concentration of the biomarker molecules released by diseased cells (DCs) to the channel ending to ACs This channel is modeled by a molecular communication (MC) paradigm In the second tier, the ACs transmit a molecular message to a BC through the cardiovascular network, which is modeled again by the MC paradigm A decision is made in the BC, which is implemented on the body skin, based on the received messages from different ACs Due to the nature of the problem, a suboptimum design of detectors in the first and second tiers are provided We use a Neyman-Pearson (NP) framework to analyze the detection performance of a health monitoring network Based on bounding likelihood ratio (LR) a lower bound for the probability of detection and an upper bound for false alarm of each AC is derived Next, taking into account the effect of ACs-BC channels, the overall performance of anomaly detection is analyzed in terms of probabilities of detection and false alarm

Analysis of Multi-Chemical Transmission in the Macro-Scale

Abstract: Molecular communications (MC) offers an alternative to established methods (i.e., electromagnetic waves), in areas where the latter might prove ineffective (e.g., underwater or underground) due to the environment’s effect on the transmitted signal. In such environments the use of particle (i.e., chemical) based communication may offer a better solution. One of the unique attributes of MC is its ability to employ chemicals as messengers, and transmitting multiple chemicals concurrently offers the potential to significantly increase the information content of the message. In this work, for the first time, the transmission of multiple chemicals with unique mass-to-charge ratios, was studied experimentally and modeled theoretically. Three modulation methods have been proposed and analyzed based on exploiting the uniqueness of the messenger chemicals. Molecular transmission was achieved using an in-house-built odor generator and detection was accomplished by means of a quadrupole mass analyzer. The noise was analyzed for multi-MC and was shown to possess additive white Gaussian noise characteristics with different mean ( $\mu $ ), but similar variance ( $\sigma ^{2}$ ) values. It was shown experimentally that multiple chemical transmission is both feasible and advantageous compared to single chemical transmission and the proposed modulation methods exhibit unique advantages that can be used for different scenarios.

Signal Detection for Molecular MIMO Communications With Asymmetrical Topology

Abstract: Molecular communication (MC) has attracted people’s attention due to its potential applications at the micro- to nano-scale. In MC, the transmission rate is usually very low due to the slow diffusion of information molecules and therefore multiple-input multiple-output (MIMO) system is introduced. However, severe interference occurs when the same types of information molecules are used at different transmission antennas. Up to now, most literature focuses on MIMO systems with symmetrical topology. In this paper, a molecular MIMO communication system with asymmetrical topology, where the number of transmission antennas is not equal to that of the reception antennas, is investigated. The zero-forcing (ZF) detection approach is proposed and discussed for three cases, i.e., the number of transmission antennas is smaller than, equal to and larger than the number of the reception antennas. Considering the inter-link interference (ILI) and the inter-symbol interference (ISI), the error probability of ZF detection is derived and comparisons are made with existing molecular MIMO detection method. Besides, the adaptive observation time for each reception antenna is derived for better performance. Numerical results show that ZF detection performs better than the existing molecular MIMO detection method when the ILI is large.

Closed-Loop Neuromodulation for Parkinson’s Disease: Current State and Future Directions

Abstract: Deep brain stimulation (DBS) refers to a neurosurgical process in which electrical stimulation is delivered via electrodes implanted within deep brain regions. DBS has become the most established clinical therapy for patients with movement disorders, although recent studies have investigated its application in a broad range of neurological and psychiatric disorders as well. Moreover, DBS has proven effective in controlling symptoms in patients with Parkinson’s disease (PD). While early DBS systems were capable of stimulation only, technological advancements have allowed for the direct assessment of dysfunctional brain activity and subsequent stimulation of the pathological circuitry. DBS can also be combined with neurochemical stimulation to address decreased concentrations of dopamine in the brain. Given that both electrical and neurochemical treatments for PD aim to rectify abnormalities in neural activity, the general term “neuromodulation” is considered more accurate and comprehensive. Recent improvements in signal detection and information processing techniques have provided further insight into PD mechanisms, which may aid in the development of personalized biomarkers and in the prediction of symptoms. In this comprehensive review, we discuss various aspects of neuromodulation in patients with PD, including basic theories, stimulation paradigms, and current challenges in the field.

Optimal Detection Interval for Absorbing Receivers in Molecular Communication Systems With Interference

Abstract: We consider a molecular communication system comprised of a transmitter, an absorbing receiver, and an interference source. Assuming amplitude modulation, we analyze the dependence of the bit error rate (BER) on the detection interval, which is the time within one transmission symbol interval during which the receiver is active to absorb and detect the number of information-carrying molecules. We then propose efficient algorithms to determine the optimal detection interval that minimizes the BER of the molecular communication system assuming no inter-symbol interference (ISI). Simulation and numerical evaluations are provided to highlight further insights into the optimal results. For example, we demonstrate that the optimal detection interval can be very small compared to the transmission symbol interval. Moreover, our numerical results show that significant BER improvements are achieved by using the optimal detection interval for systems without and with ISI.

Inference in Turbulent Molecular Information Channels Using Support Vector Machine

Abstract: Inference of transmitter side information is essential to communication In Molecular Communication (MC), whilst the Bayesian inference of mass diffusion channel parameters is well established, turbulent diffusion (TD) channels are not well-understood Cascading vortices rapidly transform transmitted momentum (molecular information puffs) into heat, which raises the challenge of receiver inferring transmitter information Our initial results found that in TD channels, inferring transmitted molecular concentration or timing is challenging As such, we were motivated to infer transmitter velocity from a flexible receiver sample area In this paper, we consider an unbounded scenario of Molecular Communication via Turbulent Diffusion (MCvTD) where a transmitter injects several molecular puffs with different velocities We first developed a time difference concentration (TDC) method based on large-scale support vector machine (SVM) to distinguish the injection velocities To trade-off the prediction accuracy and number of receiver spatial samples, we propose the stepwise maximum variance (SMV) algorithm to select the limited dominant receiver sampling locations The overall performance can achieve 100% accuracy in transmitter velocity information recovery, with excellent error vs receiver size trade-off (eg, 5% error for 74% area reduction) The research results indicate that velocity modulation at transmitter and TDC with SVM receiver should be used in MCvTD channels

On Molecular Flow Velocity Meters

Abstract: Flow velocity is an important characteristic of the fluidic mediums. In this paper, we introduce a molecular based flow velocity meter consisting of a molecule releasing node and a receiver that counts these molecules. We consider both flow velocity detection and estimation problems, which are employed in different applications. For the flow velocity detection, we obtain the maximum a posteriori (MAP) decision rule. To analyze the performance of the proposed flow velocity detector, we obtain the error probability, its Gaussian approximation and Chernoff information (CI) upper bound, and investigate the optimum and sub-optimum sampling times accordingly. We show that, for binary hypothesis, the sub-optimum sampling times using CI upper bound are the same. Further, the sub-optimum sampling times are close to the optimum sampling times. For the flow velocity estimation, we obtain the MAP and minimum mean square error (MMSE) estimators. We consider the mean square error (MSE) to investigate the error performance of the flow velocity estimators and obtain the Bayesian Cramer-Rao (BCR) and expected Cramer-Rao (ECR) lower bounds. Further, we obtain the optimum sampling times for each estimator. It is seen that the optimum sampling times for each estimator are nearly the same. The proposed flow velocity meter can be used to design a new modulation technique in molecular communication (MC), where information is encoded in the flow velocity of the medium instead of the concentration, type, or release time of the molecules. The setup and performance analysis of the proposed flow velocity detector and estimator for molecular communication system need further investigation.

Molecular Signal Tracking and Detection Methods in Fluid Dynamic Channels

Abstract: This method and data paper sets out the macro-scale experimental techniques to acquire fluid dynamic knowledge to inform molecular communication performance and design. Fluid dynamic experiments capture latent features that allow the receiver to detect coherent signal structures and infer transmitted parameters for optimal decoding. This paper reviews two powerful fluid dynamical measurement methodologies that can be applied beneficially in the context of molecular signal tracking and detection techniques. The two methods reviewed are Particle Image Velocimetry (PIV) and Planar Laser-Induced Fluorescence (PLIF). Step-by-step procedures for these techniques are outlined as well as comparative evaluation in terms of performance accuracy and practical complexity is offered. The relevant data is available on IEEE DataPort to help in better understanding of these methods.

Impacts of Unintended Nanomachine in Diffusion-Based Molecular Communication System

Abstract: The effect of unintended nanomachine (UN) on the performance of a 3-dimensional (3-D) diffusive point-to-point molecular communication system is investigated in this article. To analyze the impacts of the presence of UN, two different scenarios are considered. In the first scenario, UN is considered as an unintended transmitter nanomachine (UTN). The expression for arrival probability of molecules received at the spherical absorbing receiver, considering exponential molecular degradation, is obtained. Moreover, this scenario is analyzed in terms of average probability of error (APoE) and maximum achievable rate (MAR), with and without Genie-aided assumptions. Further, in the second scenario, wherein we consider UN as a unintended receiver nanomachine (URN), the system is analyzed in terms of information leakage and maximum achievable secrecy rate (MASR). In second scenario, we consider two different models to find the arrival probability of molecules at the intended receiver nanomachine (IRN). In the first model, independence of the particle death in URN and IRN is assumed, and in second model, mutual influences of URN and IRN on each other are assumed. Moreover, in both the scenarios, to optimize the system performance, an optimal detector is used. In the end, the derived analytical expressions are verified through particle-based and Monte-Carlo simulations.

Information Devices Based on Quantized Liénard-Hermite Oscillators

Abstract: Information has both theoretical and natural importance. At it’s roots from both a theoretical and quantum mechanical perspective, information is a dynamical process that is governed by a coupled relationship between energy and entropy. This research will investigate means for synthesizing information that is consistent with both quantum mechanical and dynamical processes. Such an approach is expected to be more consistent with naturally occurring systems, such as chemical and biological ones. The precise relationship between multiple stable equilibriums, energy quanitzation and stable information bearing patterns in the phase plane are examined. Relationships to information theory are a logical application of these results. The theorem provided allows for physical realizations of actual continuous-time quantized computational devices that are consistent with atomic and molecular dynamical processes. This pursuit can be thought of as the development of an electronic device that behaves according to quantum dynamical behaviors similar to molecular orbit phenomenology. The motivation for such devices is derived from an interest in developing a dynamical process that adheres to what will be described as physical means for representing the dynamical process of information. Results from actually synthesized physical devices are also provided. Collectively, these results represent the first known characterization and synthesis of a quantum mechanical facsimile for a naturally occurring information bearing dynamical system.

Iterative Signal Detection for Diffusion-Based Molecular Communications

Abstract: Inter-symbol interference (ISI) due to slow-moving molecules is one of the key limitations affecting throughput of a diffusion based molecular communication (MC) In this paper, we propose novel ISI mitigation approaches for diffusion based MC systems The first approach uses weighted sum (WS) to enhance the received signal-to-ISI plus noise ratio (SINR) by exploiting the apriori characteristics of the diffusion channel impulse response In the second approach, an iterative method estimates the ISI in a frame using the block-wise data symbol detection and subtracts this estimated ISI before the signal detection Both the proposed methods improve the MC system’s performance as compared to the conventional signal detection method Further, we have analyzed the combined WS and iterative method, resulting in further improvement in the performance Furthermore, the effect of various system parameters such as frame duration, diffusion coefficient, and the distance between transmitter and receiver is analyzed

2-D Channel Characterization of a Molecular Motor Signal

Abstract: In this article, a two-dimensional channel characterization of a molecular motor signal in a diffusive fluid environment is provided by deriving the first hitting time probability density function of the motor signal to an absorbing lattice point. A temporal modulation scheme to establish communication between two nodes using the motor signal is also proposed. Detection of the motor signal is achieved by using the maximum likelihood detector with erasures for a negligible or no-interference scenario. On the other hand, for motor signal reception with inter-symbol interference, the reception process is modeled as a hidden Markov model, and a Viterbi sequence detection algorithm is devised for decoding the sequence of input Markov states. Efficient criteria to determine the memory length of a diffusive molecular communication (MC) system are defined, which address the problem of choosing a detector for a given MC system. It is demonstrated using numerical results that the hitting probability and, consequently, the error performance of the motor signal worsens with an increase in the unbound probability ( $\epsilon /2$ ). Furthermore, it is also quantitatively established, as to, why in nature directed signals are preferred for communication over purely random diffusive signals at larger distances.

Investigating Instabilities in the Mammalian Cochlea Using a Stochastic Uncertainty Model

Abstract: We examine the problem of mean-square stability in a dynamical model of the mammalian cochlea with stochastically uncertain parameters. The cochlea is a mechanical spectrum analyzer with an adaptive gain amplification mechanism that gives it a very large dynamic range as an acoustic sensor. This adaptive gain mechanism has been conjectured to be responsible for occasional instabilities that can be clinically significant. We model the cochlea as a spatio-temporal dynamical system made up of a spatially distributed array of coupled oscillators incorporating an adaptive amplification mechanism. We consider settings where the cochlear amplifier has spatially and temporally varying stochastic parameters. It is shown that relatively small parameter variations (few orders of magnitude smaller than the nominal values) are sufficient to destabilize the dynamics and induce spontaneous oscillations. This extreme sensitivity of the cochlear dynamics appears to be due to a combination of the local cochlear amplification mechanism, as well as the spatial coupling of the distributed resonators. The analysis technique used in this work allows for a simulation-free prediction of the stability thresholds and the statistics of the spontaneous oscillations. Theoretical predictions are verified using full nonlinear stochastic simulations that demonstrate a good agreement with the theoretical predictions.

A Novel Framework for Capacity Analysis of Diffusion-Based Molecular Communication Incorporating Chemical Reactions

Abstract: In recent years, molecular communication (MC) is considered as a transformative paradigm in the communication theory and a promising solution to future nanoscale communication networks. In this article, a novel framework is introduced for diffusion-based MC and is shown how its capacity is impacted by the effects of chemical reactions which were neglected in the existing literature. Particularly, the chemical reactions corresponding to complex balanced chemical reaction networks are studied in this work. With an information-theoretic approach, the capacity is introduced where the effects of chemical reactions are taken into account. Then, the individual entropy derivations are addressed where the chemical reactions at the transmitter are considered with the chemical reaction network theory. Finally, the mutual information is derived based on these entropy derivations and the analytical capacity expressions are introduced accordingly. Numerical results exhibit the interactions between different parameters and show that the capacity actually decreases when the effects of chemical reactions are considered, implying that the capacity derived without chemical reactions was overestimated in previous studies. Consequently, the proposed framework analyzes the fundamental limits of diffusion-based MC and provides a more realistic capacity derivation comprising limitations imposed by chemical reactions, hence applicable to various more realistic MC scenarios.