A Distributed Scheduling Algorithm for TDMA in Diffusion-Based Molecular Communications: Concept and Practical Consideration

Diffusion based molecular communication (DBMC) acts as an indispensable element of nano-networking and Internet of things based applications. In DBMC, bio-molecules serve as information carriers for nanoscale systems. However, performance of the DBMC is limited by the following factors; nonlinear channel impulse response (CIR) of the DBMC which makes the mapping between the received symbols and transmitted symbols nonlinear, inter-symbol-interference (ISI) due to long tail of CIR of the DBMC which degrades the overall bit error rate (BER) performance, and stochastic movement of the molecules which introduces noise at the receiver. Most of the prior works on receiver design for molecular communication (MC) are based on linear detection algorithms, which are sub-optimal for the nonlinear DBMC system. Thus, to improve the performance of MC system, for the first time, we propose adaptive nonlinear receiver for MC based on the kernel least mean square algorithm, in the reproducing kernel Hilbert space. Numerical results show that the proposed nonlinear receiver improves BER performance as compared to the existing linear detection algorithms-based receiver.

Channel Modeling for Diffusion-Based Molecular MIMO Communications Using Deep Learning

Molecular communication (MC) has emerged as a viable solution for nanonetworks, where bio-molecules are used to transmit the information. However, one of the factors that limits the throughput of diffusion based MC (DBMC) is inter-symbol interference (ISI), which arises due to long tail of channel impulse response (CIR) of the DBMC. In addition to ISI, performance of the DBMC based systems is also limited by the nonlinear CIR of DBMC, which results in nonlinear distortions at the receiver, and degrades the overall bit error rate (BER) performance. Conventional minimum mean square error (MMSE) and decision feedback equalizer (DFE) based receivers deliver suboptimal performance for nonlinear systems. In this paper, for the first time, we propose Volterra-DFE based nonlinear equalizer for mitigating the aforementioned DBMC channel impairments. Numerical results show that the proposed Volterra-DFE algorithm exhibits superior BER performance over the conventional MMSE and DFE based equalizers.

Nanotechnology has allowed building nanomachines capable of performing simple tasks, such as sensing, data storage, and actuation. Nanonetworks, networks of nanomachines, will allow cooperation and information sharing among them, thereby greatly expanding the applications of nanotechnology in the biomedical, environmental, and industrial fields. One of the most promising paradigms to implement nanonetworks is diffusion-based molecular communication (DMC). In DMC, nanomachines transmit information by the emission of molecules that diffuse throughout the medium until they reach their destination. Most of the existing literature in DMC has focused on the analysis of its physical channel. In this work, the key differences of the physical channel of DMC with respect to the wireless electromagnetic channel are reviewed with the purpose of learning how they impact the design of networks using DMC. In particular, we find that the uniqueness of the physical channel of DMC will require revisiting most of the protocols and techniques developed for traditional wireless networks in order to adapt them to DMC networks. Furthermore, guidelines for the design of a novel network architecture for DMC networks, including fundamental aspects such as coding, medium access control, addressing, routing and synchronization, are provided.

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

The ultimate aim of the nano molecular communication networks is to change the living organism behaviors (e.g. intelligent drugs “nano actuators”), and to obtain information from living organisms otherwise not accessible (e.g. nano-scale diagnosis for health monitoring “nano sensors”). Utilizing biological mechanism and/or components to transfer information (e.g., molecular diffusion, neuronal networks, and molecular motors) is a new paradigm for nanomachines to exchange information. Diffusion-based communication refers to the transfer of information using molecules as message carriers whose propagation is based on the law of molecular diffusion. In this paper we briefly propose and discuss the Cognitive- DMC network scheme, and concatenated codes for the Diffusion-based molecular communication. Moreover, we discuss some other aspects and challenges that are related to DMC networks.

Nanonetworking is an emerging field of research, where nanotechnology and communication engineering are applied on a common ground. Molecular Communication (MC) is a bio-inspired paradigm, where Nanonetworks, i.e., the interconnection of devices at the nanoscale, are based on the exchange of molecules. Amongst others, diffusion-based MC is expected to be suitable for covering short distances (nm-μm). In this work, we explore the main characteristics of diffusion-based MC through the use of N3Sim, a physical simulation framework for MC. N3Sim allows for the simulation of the physics underlying the diffusion of molecules for different scenarios. Through the N3Sim results, the Linear Time Invariant (LTI) property is proven to be a valid assumption for the free diffusion-based MC scenario. Moreover, diffusion-based noise is observed and evaluated with reference to already proposed stochastic models. The optimal pulse shape for diffusion-based MC is provided as a result of simulations. Two different pulse-based coding techniques are also compared through N3Sim in terms of available bandwidth and energy consumption for communication.

Diffusion-based physical channel identification in molecular nanonetworks

Diffusion-based molecular communication is a promising bio-inspired paradigm to implement nanonetworks, i.e., the interconnection of nanomachines. The peculiarities of the physical channel in diffusion-based molecular communication require the development of novel models, architectures and protocols for this new scenario, which need to be validated by simulation. With this purpose, we present N3Sim, a simulation framework for diffusion-based molecular communication. N3Sim allows to simulate scenarios where transmitters encode the information by releasing molecules into the medium, thus varying their local concentration. N3Sim models the movement of these molecules according to Brownian dynamics, and it also takes into account their inertia and the interactions among them. Receivers decode the information by sensing the particle concentration in their neighborhood. The benefits of N3Sim are multiple: the validation of channel models for molecular communication and the evaluation of novel modulation schemes are just a few examples.

Molecular communication (MC) is a promising bioinspired paradigm for exchanging molecule information among nanomachines. In this paper, we propose a synchronization-assist photolysis MC system that aims to transmit the biosensing signal of the tumor microenvironment, facilitated by mitigating redundant molecules for improved bit error rate (BER) performance. Benefits from biocompatible MC, biosensors could transmit biosensing signals of the tumor in vivo instead of converting them to electrical signals. Due to diffusion motion’s slow and stochastic nature, intersymbol interference (ISI), resulting from previous symbols’ residual information molecules, inevitably occurs in diffusion-based MC. ISI is one of the challenges in diffusion-based MC, which significantly impacts signal detection. Inspired by on–off keying (OOK) modulation, the proposed modulation implements a switch of molecules and light alternatively. The light emitted is triggered by a synchronization signal, and the photolysis reactions could reduce the redundant molecules. An expression for the relevant channel impulse response (CIR) is derived from a hybrid channel model of diffusion and photolysis reaction. In this paper, we implement the maximum posterior estimation scheme to find the optimal decision threshold and analysis the BER performance in terms of different time intervals of the system. Numerical simulations demonstrate that the proposed method can improve the channel capacity and BER performance. We believe that our work may pave the way for MC application in biosensing.

Diffusion Based Molecular Communication (DBMC) uses messenger molecules to transfer information between nanomachines. A major challenge for DBMC is Inter Symbol Interference (ISI), which is due to the diffusive nature of the molecular channel. By computing lower and upper bounds for the number of received molecules, in this letter we prove that ISI and Bit Error Rate (BER) of a DBMC system depend on a-priori probability of transmitted data. We derive the optimal value of the a-priori probability for which ISI and BER are minimized. A coding technique, called Modified Inverse Source Coding (MISC), is proposed to control the a-priori probability of the transmitted data. We also propose two low complexity receivers for MISC-DBMC. The first is a low complexity Reduced State Sequence Detector (RSSD) based on the Viterbi algorithm. The second is a computationally less intensive Decision Feedback based Maximum A-Posteriori (DF-MAP) threshold detector. Simulation results demonstrate that the DF-MAP receiver has a similar BER performance as that of the RSSD receiver in the ideal scenario, but practically it is limited by error propagation. Also, we show that the MISC-DBMC system using RSSD or DF-MAP receiver has better BER performance, increased range, and lower complexity compared to uncoded DBMC system.

Despite the recent research activities in molecular communication among bio agents, the design of reliable schemes remains an open problem. One of the challenges is to develop suitable coding schemes which meet the molecular communication specific constraints in terms of reliability and complexity. In this paper, we consider diffusion-based molecular communication in which the information is encoded into the concentration (e.g., on/off keying). Such a communication system operates over a completely asymmetric channel where one of the bits can be transmitted without any error while the other can undergo a random error by the channel. Because of the limitations of bio agents, we focus on error-detecting schemes which require far less complexity at the receiver relative to error-correction codes. We model the detection process at the receiver via an erasure channel and propose an algorithm that obtains the optimal codewords efficiently. Then, we consider an error-free sub-family of such codes, namely constant weight codes, and propose an implementation specific to the molecular communication. We analyze the rate of the constant-weight coding scheme and specify the optimal weights and lengths of such codes. We also show that this coding scheme, by design, would enable the nodes to synchronize their communications.

In diffusion-based molecular communications, time synchronization is a major reason for the increase of system structure complexity. In this paper, we consider the asynchronous receiver design for molecular communications with information symbols conveyed in the time of released molecules. The main contribution of this paper is that we develop a detector called clock-free asynchronous receiver design (CFARD), in which the receiver recovers the information symbols without measuring the arrival time of molecules. The theoretical analysis indicates that compared with the synchronous receiver designs, the proposed scheme considerably lowers the structure complexity for information demodulation, which is of great significance to the feasibility of nano-scale molecular communications systems with the limitation of energy and size. The numerical results show that in the comparison of bit error ratio (BER) performance, the proposed asynchronous receiver design outperforms the synchronous linear average filter (LAF) detector and approaches to the synchronous maximum likelihood (ML) detector and first arrival (FA) detector.

<p>Diffusion-based Molecular Communication (DMC) is a feasible method for information transmission in some nano-networks operated in gas or liquid environments. In this paper, we first propose an information modulation scheme for DMC, which is referred to as the Type-Spread Molecular Shift Keying (TS-MoSK). Considering that DMC signals usually experience severe inter-symbol interference (ISI), our TS-MoSK is characterized by introducing extra types of molecules for ISI mitigation (ISIM). Furthermore, we introduce two ISIM methods to the TS-MoSK modulated DMC systems, which are the active ISIM and passive ISIM. We detail their operation principles, and investigate as well as compare their achievable performance. Our studies show that, aided by the extra types of molecules, TS-MoSK outperforms the MoSK without spreading. Both ISIM approaches are effective for further improving the performance of TS-MoSK.</p>

The performance of a molecular signal detector relies on selected value of the detection threshold. In fact, arbitrary choice of detection threshold would increase either the probability of miss detection or the probability of false alarm. Thereby, an appropriate value of detection threshold is required in order to optimize the error performance of a realistic diffusion-based molecular communication (DbMC) system. For this, we come up with a new approach that yields optimal value for convex optimization problem in DbMC using logarithmic barrier followed by modified Karush–Kuhn–Tucker conditions, Newton Raphson method, and finally rounding the solution to the nearest integer value. Previous works on threshold optimization in DbMC either give suboptimal solution or optimal one whereof the convergence depends on choosing the smallest interval that contains the optimal value. Numerical and simulation results reveal that our proposed methodology can provide optimal solution with utmost accuracy in few iterations.