Molecular Communication System Research Articles

Bioinspired molecular communications system for targeted drug delivery with IoBNT-based sustainable biocyber interface

This paper presents a sustainable biocyber interface approach for an intelligent targeted drug delivery system (TDDS). The proposed approach employs a bioinspired molecular communications (MC) system in which molecules are used as information carriers and a multi-input multi-output (MIMO) Forster resonance energy transfer (FRET) nanorelay to efficiently transfer therapeutic drugs from extravascular (outside blood vessels) to intravascular (within blood vessels) sites that are targeting diseased tissue. The proposed approach consists of a number of bio-nano things (BNTs) implanted inside the human intra-body nanonetwork near the diseased site. The communication among BNTs is accomplished by a sequential multistep FRET, and the nanonetwork is controlled by the Internet of Bio-Nano Thing (IoBNT) paradigm sustained by an uplink/downlink biocyber interface. The bit error rate (BER) and molecular channel capacity are utilized to evaluate the performance of the proposed approach. In addition, a Markov model decision in terms of the number of nanomachines is presented to calculate the successful probability of drug delivery and the average delay time. The numerical results show how effective the suggested method is at transmitting therapeutic medication information with an attainable bit-rate error.

Energy Allocation for Multiuser Cooperative Molecular Communication Systems in Internet of Bio-Nano Things

Energy Allocation for Multiuser Cooperative Molecular Communication Systems in Internet of Bio-Nano Things

Molecular communication data augmentation and deep learning based detection

This manuscript presents a novel model for generating synthetic data for a biological molecular communication (MC) system to train a Neural Network (NN) for the purpose of discriminating transmitted bits. To achieve this, a deep learning algorithm was trained using the synthetic data and tested against experimentally measured data. The polynomial curve fitting coefficients are chosen as features. The featurization stage is followed by a NN that captures different aspects of the temporal correlation of the received signals. The real data was collected from an MC testbed that employed transfected Escherichia coli (E. coli) bacteria expressing the light-driven proton pump gloeorhodopsin from Gloeobacter violaceus. By stimulating the bacteria with externally controlled light, protons were secreted, which changed the pH level of the environment. A pH detector was then used to measure the pH of the environment. We propose the use of a deep convolutional neural network to detect the transmitted bits. This paper discusses the data augmentation, processing, and NNs that are pertinent to practical MC problems. The trained algorithm demonstrated an accuracy of over 99.9% in detecting transmitted bits from received signals at a bit rate of 1 bit/min, without requiring any specific knowledge of the underlying channel.

On Secrecy Performance in D-MoSK-Based 3-D Diffusive Molecular Communication System.

This paper studies the secrecy performance in a 3-D diffusive molecular communication system with the general depleted molecule shift keying (D-MoSK) modulation, where a point transmitter Alice transmits through diffusion multiple types of molecules modulation to a legitimate absorbing receiver Bob, suffering the eavesdropping from an absorbing eavesdropper Eve. We first develop a solid theoretical framework to determine the probabilistic distributions for the number of molecules absorbed by Bob and Eve, respectively. Based on the results, we then derive the average symbol error rate (SER) as well as the mutual information of Alice-Bob and Alice-Eve, and further apply the Shannon theory to determine the secrecy capacity of Alice-Bob transmission. We also develop the closed-form results for the optimal detection threshold at Bob to achieve the secrecy capacity, and thus devise a complete algorithm for secrecy capacity maximization. Finally, we provide numerical results to illustrate the secrecy performance in the concerned system.

An Effective Constellation Design for Concentration Shift Keying in Molecular Communication Systems

An Effective Constellation Design for Concentration Shift Keying in Molecular Communication Systems

Assessing Molecular Throughput and Efficiency through Simulation in Diffusion-Based Molecular Communication

Objectives: This study investigates the correlation of critical factors influencing throughput and efficiency in diffusion-based molecular communication systems. Method: The study presents a simulation model for 3-D diffusion-based molecular communication, incorporating essential parameters such as molecule size, transmission rate, diffusion rate, and transmitter-receiver distance. Findings: Through comprehensive simulations, the study reveals the effects of different parameters on throughput and efficiency in diffusion-based molecular communication. It highlights the critical trade-offs associated with system design and optimization. The study reveals the key factors influencing the transmission capabilities, the receiver congestion, and the overall efficiency of the communication system. Novelty: In this study, we give a study overview of the latest work of performance metrics in the field of molecular communication. A novel algorithm is proposed to find the throughput and efficiency of molecular communication. The proposed framework analyzes the intricate relationship between system parameters and performance metrics, emphasizing the potential for system optimization. Our simulation work demonstrates how the model parameters influence the performance of the molecular communication system, providing insights for enhancing the system's performance in applications such as targeted drug delivery in the future. Keywords: Molecular Communication, Diffusion, Transmission Rate, Throughput, Efficiency

Towards practical implementation of molecular communication: A cost‐effective experimental platform based on the human circulatory system

AbstractRecently, there have been numerous studies exploring the field of molecular communication (MC) systems. However, due to the high cost and limited availability of advanced micro/nano‐scale equipment, most of these works remain purely theoretical, with only a few being examined through experimental platforms. Additionally, the absence of a suitable model for flow‐assisted MC‐based systems poses another significant challenge. This research focuses on the potential applications of MC technology within the human body. To address the limitations mentioned above, a closed‐loop experimental platform based on the human circulatory system is proposed. This platform offers a cost‐effective and accessible solution for studying MC systems. The implementation process involves a brief discussion about the circulatory system model. By varying flow rates and the quantity of released information particles, channel impulse responses are obtained. Based on the observed experimental data, the authors have successfully developed a new theoretical model that accurately fits the experimental data. The model demonstrates a strong level of agreement with the observed results. This model demonstrates its suitability for flow‐assisted MC‐based systems.

GLADIATOR: Transforming Glioblastoma Care

We spoke to Professor Costas Pitris about GLADIATOR, a project that aims to revolutionise brain pathology diagnosis and treatment by using Molecular Communications systems. This theranostic solution, focused on glioblastoma, integrates autonomous molecular nanonetworks of engineered cells and innovative bio-electronics for personalised interventions, marking a paradigm shift in oncology research.

Molecular Communication Systems in Cylindrical Channels With Non-Newtonian Fluid Flows in IoBNT

Molecular Communication Systems in Cylindrical Channels With Non-Newtonian Fluid Flows in IoBNT

Emission rate optimization in diffusion-based molecular communication among mobile bacteria

In quorum sensing (QS), bacteria exchange information by using molecular signals to work together. In this paper, we study diffusion-based molecular communication with the QS mechanism between the transmitter node and receiver node which are composed of a population of mobile bacteria in a cluster, respectively. The expression of average bit error probability (BEP) at a receiver bacterium is derived. Furthermore, we use the projected gradient descent (PGD) algorithm to solve the optimization problem whose objective is to minimize the average BEP under emission rate constraints which require that the emission rate of each transmitter bacterium has lower and upper bounds. Finally, the numerical results show the PGD algorithm has good convergence behaviors and it is more efficient in finding the optimal emission rate with fewer iterations than genetic algorithm. The obtained results are expected to provide guidance in designing QS-based molecular communication system with lower average BEP.

Real-time signal processing via chemical reactions for a microfluidic molecular communication system

Signal processing over the molecular domain is critical for analysing, modifying, and synthesising chemical signals in molecular communication systems. However, the lack of chemical signal processing blocks and the wide use of electronic devices to process electrical signals in existing molecular communication platforms can hardly meet the biocompatible, non-invasive, and size-miniaturised requirements of applications in various fields, e.g., medicine, biology, and environment sciences. To tackle this, here we design and construct a liquid-based microfluidic molecular communication platform for performing chemical concentration signal processing and digital signal transmission over distances. By specifically designing chemical reactions and microfluidic geometry, the transmitter of our platform is capable of shaping the emitted signals, and the receiver is able to threshold, amplify, and detect the chemical signals after propagation. By encoding bit information into the concentration of sodium hydroxide, we demonstrate that our platform can achieve molecular signal modulation and demodulation functionalities, and reliably transmit text messages over long distances. This platform is further optimised to maximise data rate while minimising communication error. The presented methodology for real-time chemical signal processing can enable the implementation of signal processing units in biological settings and then unleash its potential for interdisciplinary applications.

Impact of Evanescence Process on Three-Dimensional Sub-Diffusion based Molecular Communication Channel.

In most of the existing works of molecular communication (MC), the standard diffusion environment is taken into account where the mean square displacement (MSD) of an information molecule (IM) scales linearly with time. On the contrary, this work considers the sub-diffusion motion that appears in crowded and complex (porous or fractal) environments (movement of the particles in the living cells) where the particle's MSD scales as a fractional order power law in time. Moreover, we examine an additional evanescence process resulting from which the molecules can degrade before hitting the boundary of the receiver (RX). Thus, in this work, we present a 3D MC system with a point transmitter (TX) and the spherical RX with the sub-diffusive behavior of an IM along with its evanescence. Furthermore, an IM's closed-form expressions for the arrival probability and the first passage time density (FPTD) are emulated in the above context. Additionally, we investigate the performance of MC by using the concentration-based modulation technique in a sub-diffusion channel. Finally, the considered MC channel is exploited in terms of the probability of detection, probability of false alarm, and probability of error for different parameters such as the reaction rate, fractional power, and radius of the RX.

Temporal Convolutional Network-Based Signal Detection for Magnetotactic Bacteria Communication System.

Molecular communication (MC) aims to use signaling molecules as information carriers to achieve communication between biological entities. However, MC systems severely suffer from inter symbol interference (ISI) and external noise, making it virtually difficult to obtain accurate mathematical models. Specifically, the mathematically intractable channel state information (CSI) of MC motivates the deep learning (DL) based signal detection methods. In this paper, a modified temporal convolutional network (TCN) is proposed for signal detection for a special MC communication system which uses magnetotactic bacteria (MTB) as information carriers. Results show that the TCN-based detector demonstrates the best overall performance. In particular, it achieves better bit error rate (BER) performance than sub-optimal maximum a posteriori (MAP) and deep neural network (DNN) based detectors. However, it behaves similarly to the bidirectional long short term memory (BiLSTM) based detector that has been previously proposed and performs worse than the optimal MAP detector. When both BER performance and computational complexity are taken into account, the proposed TCN-based detector outperforms BiLSTM-based detectors. Furthermore, in terms of robustness evaluation, the proposed TCN-based detector outperforms all other DL-based detectors.

A Control-Theoretic Model for Bidirectional Molecular Communication Systems

A Control-Theoretic Model for Bidirectional Molecular Communication Systems

Probabilistic Constellation Shaping for Molecular Communications

Molecular communication (MC) is an emerging field aiming at realizing information exchange via chemical signals between nanomachines in nanonetworks. Information transmission that is energy-efficient and relies on relatively low-complexity transceiver techniques is of practical importance for MC systems. Based on the fact that constellation shaping can improve energy efficiency, in this paper, we propose a molecular shell mapping (MSM) scheme to implement the probabilistic constellation shaping for MC. The MSM method is designed to exploit the concentration sequences with the lowest sum sequence weight, which results in an energy-efficient signal constellation. Furthermore, we propose an algorithm for selecting and sorting the concentration sequences to mitigate inter-symbol interference. For information detection, we design a genie-aided maximum-likelihood (ML) detector and a realistic ML detector to leverage the constructive effect of intra-sequence interference, as well as derive their bit error rates and achievable rates. Additionally, for the applications using large blocklength sequences, a low-complexity ML detection method is proposed. Numerical simulation results confirm that the shaped signaling using the MSM method is more energy-efficient than the conventional equiprobable signaling, achieving shaping gains of up to 1.5 dB at an ultra-short blocklength of 4.

Interfacing of Molecular Communication System With Various Communication Systems Over Internet of Every Nano Things

The communication system for health-monitoring applications is a substantial research area considering its practical limitations. One of the potential suggested technologies is internet-of-every-nano-thing (IoENT). Through this work, we demonstrate the different aspects of interfacing of molecular communication (MC) with other nano-communication systems such as human body communication (HBC), acoustic communication (AC), and tera-Hertz (Thz) communication systems for IoENT. Moreover, we also emphasized eclectic possibilities and various issues related to the applications of IoENT. First, we explored each of the nano-communication systems in detail by showing their mathematical frameworks. Subsequently, we are also concerned about different ways to interface MC with other nano-communication systems, one-by-one. In the end, we also discuss various likely challenges and possible future directions, e.g., availability of devices, mobility of devices and synchronization, etc in the context of interfacing of diverse technologies.

Detection and ISI mitigation in mobile molecular communication system for targeted drug delivery

This paper proposes a targeted drug delivery system based on mobile molecular communication (MMC). The system consists of a mobile transmitter and a mobile reactive receiver. The transmitter can sense the required drug concentration and send commands to the receiver for drug delivery in the extracellular fluid (ECF). The commands are sent in the form of bits and the received signal is prone to noise and inter-symbol interference (ISI). Hence, at the receiver, two detection techniques, differential amplitude detector (DAD) and differential energy detector (DED) with ISI mitigation are proposed for MMC. Manchester-coded bits are transmitted using modified concentration shift keying (MCSK). In the proposed detection mechanism, an adaptive threshold technique is used for estimating the number of signaling molecules using the maximum a posteriori probability (MAP) rule. Further in each bit interval, dynamic distance estimation, signal reconstruction, and ISI mitigation are performed. Particle-based simulation for reactive receiver is also carried out to validate the results. A low bit error rate (BER) in the MMC system signifies the promising performance of the drug delivery system.

Interference Mitigation-Enabled Signal Detection in Diffusive Molecular Communications Systems With Molecular-Type Spreading

To accomplish complex tasks, several nano-machines may need to communicate via multiple-access channel with one access point, where information fusion is carried out. However, multiple-access Diffusive Molecular Communications (DMC) systems suffer from severe Multiple-Access Interference (MAI) and Inter-Symbol Interference (ISI), which should be effectively mitigated at receiver in order to achieve acceptable performance. Built on two fundamental single-user detection schemes, namely Threshold assisted Majority Vote Detection (TMVD) and Equal Gain Combination Detection (EGCD), we first propose three low-complexity interference cancellation schemes, which are the TMVD-assisted Iterative Interference Cancellation (TMVD-IIC), TMVD-based Minimum-Distance Decoding assisted Interference Cancellation (TMVD-MDDIC) and the EGCD-assisted N-order Iterative Interference Cancellation (EGCD-NIIC), for operation in the Molecular Type Spread assisted Molecular Shift Keying (MTS-MoSK) DMC systems. Then, following the principle of maximum likelihood detection, we propose a Simplified Approximate Maximum Likelihood (SAML) detection scheme. The error performance of the MTS-MoSK DMC systems employing respectively the considered detection schemes is comprehensively investigated and compared. Furthermore, the complexities of the detection schemes are analyzed and discussed in terms of the complexity-performance trade-off. Our studies and results show that, compared with the single-user TMVD and EGCD schemes, the proposed interference cancellation schemes are capable of mitigating efficiently the effect of MAI and enabling significant performance improvement at the slightly increased complexity.

Channel Modeling for Multi-Receiver Molecular Communication Systems

Channel Modeling for Multi-Receiver Molecular Communication Systems

A Survey for Possible Technologies of Micro/Nanomachines Used for Molecular Communication Within 6G Application Scenarios

The Internet of bio-nanothings (IoBNT) is one of the potential application scenarios in the 6th generation (6G) mobile network, which envisions the interaction between biological cells or nanodevices and the Internet. Molecular communication (MC) may offer an appropriate communication method for the nanodevices using chemical molecules as the information carriers. However, due to the complexity of experiments and insufficient interdisciplinary cooperation, MC study mainly focuses on theoretical research, which seriously hinders the MC’s advancement and further applications. Therefore, it is crucial to explore methods for constructing transmitter and receiver nanomachines to realize practical MC systems. Based on the research progress of micro/nanomachines (MNMs) in recent years, this paper summarizes the possible technologies for implementing MNMs used for MC systems within 6G application scenarios.