Design and analysis of molecular relay channels: an information theoretic approach

Molecular communication network and its applications in crop sciences

Plant molecular biology and bacterial behaviour research in the future could focus on using genetically engineered bacteria as a sensor, hormonal/disease detector, and target gene expression, as well as establishing a bioluminescence feedback communication system. Over the last two decades, understanding plant signal transduction pathways of plant hormones has become an active research field to understand plant behavior better. To accomplish signal transduction, plants use a variety of hormones for inter- and intra-communication, and biotic or abiotic stressors activate those. Signal transduction pathways refer to the use of various communication methods by effectors to elicit a response at the molecular level. Research methodologies such as inter-kingdom signaling have been introduced to study signal transduction and communication pathways, or what we can term plant molecular communication. However, stochastic qualities are inherent in most technologies used to monitor these biological processes. Molecular communication (MC) is a new research topic that uses the natural features of biological organisms to communicate and aims to manipulate their stochastic nature to achieve the desired results. MC is a multidisciplinary research field inspired by the use of molecules to store, spread, and receive information between biological organisms known as "Biological Nanomachines." It has been used to demonstrate how biological entities may be characterised, modelled, and engineered as communication devices in the same manner as traditional communication technologies are. We attempted to link MC and PLANT'S MC in this study and we believe that reasonable combined efforts may be made to use the functional applications of MC for detecting and understanding molecular-level activities such as signaling transduction pathways in crops.

A survey of 5G millimeter wave, massive multiple‐input multiple‐output, and vehicle‐to‐vehicle channel measurements and models

There is no doubt that the world evolves nowadays in the digital communications era. This opens the horizon to research and investment in new promising technologies like 5G and beyond cellular networks that are able to increase the subscribers' data rates in all communication systems. The aim of 5G and beyond cellular networks is to provide anywhere and anytime connectivity. By combining the enormous available bandwidth in millimeter wave (mmWave) frequencies with high multiplexing gains achieved by large antenna arrays in multiple‐input multiple‐output (MIMO) systems, these technologies can significantly improve network throughput, increase network power, boost energy and spectral efficiency, and enhance network coverage. Furthermore, ultra‐reliable vehicular communication and high capacity would be essential features of communication networks beyond 5G. Fortunately, when vehicles are moving on the road and communicating with each other, the vehicular communication issue becomes more challenging. Among the several new technologies expected to play significant roles in the 5G and beyond systems, this paper focused on summarizing the state‐of‐the‐art mmWave, vehicle‐to‐vehicle (V2V), and massive MIMO measurements and models. We introduce a detailed overview of each of the three technologies individually. Besides, novel taxonomies for the 5G channel measurements, objectives, and model types are provided. We expect that mmWave‐based massive MIMO technology enables real‐time channel estimation and ultra‐precise beamforming, and thus enables better service coverage. Finally, challenges and future research directions for 5G channel measurements and models are presented.

Improving Reliability Performance of Molecular Communication Based on Drift Diffusion with Ratio Detection Algorithm

Reliability is a vital issue in the area of communication. In this paper, we particularly investigate the reliability issue for molecular communication based on drift diffusion (MCD2). Since molecules easily accumulate in the channel to produce strong internal symbol interference (ISI), the receiver nanomachine will generate high bit error rate (BER) for the process of decode information. Based on this problem, on the premise of considering channel diffusion noise and ISI noise, the expression of channel BER is deduced to analyze reliability. Then a ratio detection algorithm (RDA) is proposed to reduce BER to improve the reliability performance that enables the receiver nanomachine to adapt the channel condition. Furthermore, an expression of signal to interference plus noise ratio is defined in numerical simulation to verify our goal with different parameters, as well as with the adoption of RDA. The results indicate that the performance of RDA in reducing BER works well in general case in improving reliability performance for MCD2.

Design Methodology of Passive In-Line Relays for Molecular Communication in Flow-Induced Microfluidic Channel

Molecular communication is a bioinspired communication that enables macro-scale, micro-scale and nano-scale devices to communicate with each other. The molecular communication system is prone to severe signal attenuation, dispersion and delay, which leads to performance degradation as the distance between two communicating devices increases. To mitigate these challenges, relays are used to establish reliable communication in microfluidic channels. Relay assisted molecular communication systems can also enable interconnection among various entities of the lab-on-chip for sharing information. Various relaying schemes have been proposed for reliable molecular communication systems, most of which lack practical feasibility. Thus, it is essential to design and develop relays that can be practically incorporated into the microfluidic channel. This paper presents a novel design of passive in-line relay for molecular communication system that can be easily embedded in the microfluidic channel and operate without external energy. Results show that geometric modification in the microfluidic channel can act as a relay and restore the degraded signal up-to 28%.

Algorithm for Mesoscopic Advection-Diffusion

In this paper, an algorithm is presented to calculate the transition rates between adjacent mesoscopic subvolumes in the presence of flow and diffusion. These rates can be integrated in stochastic simulations of reaction-diffusion systems that follow a mesoscopic approach, i.e., that partition the environment into homogeneous subvolumes and apply the spatial stochastic simulation algorithm (spatial SSA). The rates are derived by integrating Fick's second law over a single subvolume in 1D and are also shown to apply in 3D. The proposed algorithm corrects the derived rates to ensure that they are physically meaningful and it is implemented in the AcCoRD Simulator (Actor-based Communication via Reaction-Diffusion). Simulations using the proposed method are compared with a naive mesoscopic approach, microscopic simulations that track every molecule, and analytical results that are exact in 1D and an approximation in 3D. By choosing subvolumes that are sufficiently small, such that the Péclet number associated with a subvolume is sufficiently less than two, the accuracy of the proposed method is comparable with microscopic method, thus enabling the simulation of advection-reaction-diffusion systems with the spatial SSA.

Performance Evaluation and Optimal Detection of Relay-Assisted Diffusion-Based Molecular Communication With Drift

In this paper, we consider a decode-and-forward (DF) relay-assisted diffusion-based molecular communication system inside one of the blood vessels of a human body with positive drift from transmitter to receiver. We use the normal approximation to the distribution of the number of received molecules and derive a closed-form expression for the end-to-end bit error probability of the system. We then propose an optimization problem that aims at minimizing the bit error probability of the system and solve it at the receiver nanomachine by an algorithm based on the bisection method to determine the optimal detection threshold. Furthermore, we study the impact of the system parameters, such as drift velocity, position of the relay node and number of allocated molecules on the performance of the system. The numerical results show that with a constant molecular budget, DF relying strategy can considerably improve the system performance.

Linear Channel Modeling and Error Analysis for Intra/Inter-Cellular Ca2+ Molecular Communication

The use of intra/inter-cellular calcium ion (Ca²⁺) signaling for molecular communication (MC) is investigated in this paper. In particular, the elevation of the intracellular Ca²⁺ concentration upon the external excitation, i.e., Ca²⁺ wave generation, and the intercellular propagation of Ca²⁺ wave over consecutive cells are studied for information transmission. The main objective of this paper is to develop a linear channel model for intra/inter-cellular Ca²⁺ MC. In this context, the end-to-end Ca²⁺ MC system is studied under three blocks: the wave generation, the gap junctional (intercellular) propagation, and the intracellular propagation. The wave generation block captures the intracellular Ca²⁺ signaling pathway including the release of Ca²⁺ from the organelles and the buffers inside a cell, and the intake from the extracellular space. The gap junctional (intercellular) propagation block captures the Ca²⁺ transition through the gap junctions between the touching cells. The intracellular propagation block defines the effect of the cytoplasmic diffusion. Using the developed blocks for the different biophysical phenomena, the end-to-end channel gain and delay formulas are derived. Furthermore, the bit error probability is studied to reveal the impact of the detection threshold. This work provides the basis for the modeling, analysis and the design of Ca²⁺ MC systems.

A Molecular Communications Model for Drug Delivery

This paper considers the scenario of a targeted drug delivery system, which consists of deploying a number of biological nanomachines close to a biological target (e.g., a tumor), able to deliver drug molecules in the diseased area. Suitably located transmitters are designed to release a continuous flow of drug molecules in the surrounding environment, where they diffuse and reach the target. These molecules are received when they chemically react with compliant receptors deployed on the receiver surface. In these conditions, if the release rate is relatively high and the drug absorption time is significant, congestion may happen, essentially at the receiver site. This phenomenon limits the drug absorption rate and makes the signal transmission ineffective, with an undesired diffusion of drug molecules elsewhere in the body. The original contribution of this paper consists of a theoretical analysis of the causes of congestion in diffusion-based molecular communications. For this purpose, it is proposed a reception model consisting of a set of pure loss queuing systems. The proposed model exhibits an excellent agreement with the results of a simulation campaign made by using the Biological and Nano-Scale communication simulator version 2 (BiNS2), a well-known simulator for molecular communications, whose reliability has been assessed through in vitro experiments. The obtained results can be used in rate control algorithms to optimally determine the optimal release rate of molecules in drug delivery applications.

Error performance of diffusion-based molecular communication using pulse-based modulation

Diffusion-based molecular communication (DMC) is a promising technique for nanonetworks. The main objective of this paper is to evaluate the error performance of DMC employing pulse-based modulation scheme. We derive closed-form expressions for error probability using energy detection and amplitude detection techniques. The error performance model accounts for diffusion noise and intersymbol interference (ISI) effects. We compare the performance of both detection techniques along with investigating the effect of different parameters on error performance. We also evaluate the channel capacity of pulse modulated DMC.

Collision bottleneck throughput in bacterial conjugation-based nanonetworks

Bacterial conjugation-based nanonetwork has been recently proposed as a novel molecular communication paradigm, in which the bacteria act as carriers. This is the foundational work proposing the phenomenon of collision which occurs in the form of multi-conjugation of multiple carrier bacteria at the side of receiver nanodevice. We show the effect of this conjugation-based collision on the maximum achievable throughput of the network, using a simple graph-theoretic approach, namely, Maximum Weight Bipartite Matching. One of the several interesting results that emerges concerns the maximum achievable throughput, which is bounded by Θ(n/p) in case of homogeneous nodes, where n and p refer to the total number of nodes, and the vertical layers in the network, respectively.

Using information metrics and molecular communication to detect cellular tissue deformation

Calcium-signaling-based molecular communication has been proposed as one form of communication for short range transmission between nanomachines. This form of communication is naturally found within cellular tissues, where Ca(2+) ions propagate and diffuse between cells. However, the naturally flexible structure of cells usually leads to the cells dynamically changing shape under strain. Since the interconnected cells form the tissue, a change in shape of one cell will change the shape of the neighboring cells and the tissue as a whole. This will in turn dramatically impair the communication channel between the nanomachines. We propose a process for nanomachines utilizing Ca(2+) based molecular communication to infer and detect the state of the tissue, which we term the Molecular Nanonetwork Inference Process. The process employs a threshold based classifier that identifies its threshold boundaries based on a training process. The inference/detection mechanism allows the destination nanomachine to determine: i) the type of tissue deformation; ii) the amount of tissue deformation; iii) the amount of Ca(2+) concentration emitted from the source nanomachine; and iv) its distance from the destination nanomachines. We evaluate the use of three information metrics: mutual information, mutual information with generalized entropy and information distance. Our analysis, which is conducted on two different topologies, finds that mutual information with generalized entropy provides the most accurate inferencing/detection process, enabling the classifier to obtain 80% of accuracy on average.

Tabletop molecular communication: text messages through chemical signals

In this work, we describe the first modular, and programmable platform capable of transmitting a text message using chemical signalling – a method also known as molecular communication. This form of communication is attractive for applications where conventional wireless systems perform poorly, from nanotechnology to urban health monitoring. Using examples, we demonstrate the use of our platform as a testbed for molecular communication, and illustrate the features of these communication systems using experiments. By providing a simple and inexpensive means of performing experiments, our system fills an important gap in the molecular communication literature, where much current work is done in simulation with simplified system models. A key finding in this paper is that these systems are often nonlinear in practice, whereas current simulations and analysis often assume that the system is linear. However, as we show in this work, despite the nonlinearity, reliable communication is still possible. Furthermore, this work motivates future studies on more realistic modelling, analysis, and design of theoretical models and algorithms for these systems.