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INTRODUCTION
Molecular Communication (MC) is a new interdisciplinary research area including the nanotechnology, biotechnology and communication technology [1]. In nature, molecular communication is one of the most important biological functions in living organisms to enable biological phenomena to communicate with each other. For example, in an insect colony, insects communicate with each other by means of pheromone molecules. When an insect emits pheromone molecules, some of them bind the receptors of some insects in the colony and these insects convert the bound pheromone molecules to biologically meaningful information. This enables the insects in the colony to communicate with each other. Similar to insects, almost all of the biological systems in nature perform intra-cellular communication through neurotransmitters, and inter-organ communication through hormones [1].
Nanotechnology is one of the most promising technology which enables nano-scale machines called as nano-machines [2]. A nano-machine is an integrated device around 10-100 µm2 in size and able to do simple tasks such as sensing, plain computation, communication and local actuation. A nano-network is formed by connecting nano-machines; therefore it is capable to perform more complicated tasks such as drug delivery, health monitoring and detection of biological or chemical attacks in nano-scale environments by cooperation of nano-machines [3]. The potential of interfacing bio-nano-machines has led to the emerging interdisciplinary research area of molecular communication or nano-networks.
Molecular communication uses molecules (i.e., chemical signals) as an information carrier and allows biological and artificially created nano- or cell-scale entities (e.g., cells) to communicate over a short distance.
Molecular communication is different from the conventional communication paradigm (See Table 1). In the conventional communication, a sender encodes the digital information (such as text, audio or video) onto electromagnetic waves and transmits them to a receiver. The receiver receives the electromagnetic waves and interprets the encoded information. On the other hand, in the molecular communication, a sender encodes the biochemical information (such as phenomena and chemical status) onto molecules and transmits them to a receiver. The receiver receives the information molecules and biochemically reacts to the received molecules (This biochemical reaction represents decoding of the information). The communication speed of molecular communication is slower than that of the conventional communication, and molecular communication is a stochastic communication. However, molecular communication may carry the information that is not feasible to carry with conventional communication (such as the biochemical status of a living organism) between the entities that the conventional communication does not apply (such as biological entities). Molecular communication has unique features that are not seen in the conventional communication and is not competitive but complementary to the conventional communication [4].
A. Expected Characteristics
A variety of characteristics of molecular communication arise from using biological mechanisms and components for communication in an aqueous environment.
Biocompatibility: Since molecular communication uses the same communication mechanisms as biological systems, nano-machines in molecular communication can directly communicate with various natural components in a biological system using encoding and decoding methods available to the biological system. Biocompatibility of molecular communication may enable such application as inserting nano-machines into a biological system for medical applications that require biologically friendly nano-machines [5]
Energy efficiency, low heat dissipation: Molecular communication uses mechanism and materials from biological systems and is therefore expected to be energy efficient and achieve low heat dissipation. The chemical energy necessary for molecular communication is expected to be supplied by the environment in which the bio-nano-machines are deployed [6].
Slow speed, limited range, large jitter and high loss rate: The speed and range of molecular communication are extremely slow and short and vary depending on the biological materials, mechanisms used, and the environment. In addition, molecular communication experiences large signal jitter and a high loss rate because the movement of molecules is often unpredictable and the molecules arrive at a receiver bio-nano-machine after a widely varying period of time. Moreover, the molecules may degrade in the environment and not even arrive at a receiver bio-nano-machine.
B. Molecular Communication Types
Three main types of Molecular Communication as shown in Fig. 1 are walkway-based, the advection-based, and diffusion-based [7].
In walkway-based MC, the molecules propagate through active transport by following pre-defined pathways by using carrier substances, such as molecular motors [8]. This type of communication can be achieved using E.coli bacteria.
In advection-based MC, the molecules propagate in a fluidic medium whose flow and turbulence are guided and predictable. The hormonal communication through blood streams inside the human body is an example of this type of communication [9]
In diffusion-based MC, the molecules propagate through spontaneous diffusion in a fluidic medium. In this case, the molecules can be subject solely to the laws of diffusion or can also be affected by non-predictable turbulence present in the fluidic medium. Pheromonal communication, when pheromones are released into a fluidic medium, such as air or water, is an example of diffusion-based architecture [10].
In Chapter 2, we can understand the architecture of Molecular Communication, the different phases in the communication mechanism and the modulation techniques available for this mode of communication.
In Chapter 3 we will be reviewing the papers submitted on the state-of-the-art while Chapter 4 provides the future research that needs to be done in this area.
MOLECULAR SYSTEM ARCHITECTURE
In this section, we first discuss bio-nano-machines and the molecular communication environment where bio-nano-machines exist and function.
A. Bio-Nanomachines
Bio-nanomachines are defined based on material, size and functionality.
First, a bio-nanomachine is composed of biological materials (e.g., protein, nucleic acid, lipid, biological cell) with or without non-biological materials (e.g., magnetic particles). Second, the size of a bio-nanomachine ranges from the size of a macromolecule to that of a biological cell. Note that our definition of bio-nanomachines includes biological cells, entities typically much larger than what the term “nano” often refers to (i.e., dimensions of 1–100 nm). Third, a bio-nanomachine implements a set of simple functionalities, including simple
Life-sustaining functionalities (e.g., acquiring and expending energy), simple actuation functionalities (e.g., moving along a protein filament), simple molecule processing functionalities (e.g., capturing/storing/releasing molecules, detecting molecules and modifying molecules) [8].
B. Molecular Communication Architecture
Fig. 2 shows an architectural design for molecular communication [7]. It consists of components functioning as information molecules that represent the information to be transmitted, sender bio-nanomachines that release the information molecules, receiver bio-nanomachines that detect the information molecules, and the environment in which the information molecules propagate from the sender bio-nanomachine to the receiver bio-nanomachine. The system may also include transport molecules to move information molecules, guide molecules to direct the movement of the transport molecules to selectively transport information molecules, and addressing molecules (not shown) that are attached to information molecules or interface molecules to specify the receiver bio-nanomachine.
Fig. 2 also shows the general phases of communication: encoding of information into an information molecule by the sender bio-nanomachine, sending of the information molecule into the environment, propagation of the information molecule through the environment, receiving of the information molecule by the receiver bio-nanomachine, and decoding of the information molecule into a chemical reaction at the receiver bio-nanomachine. The basic components involved in each phase of molecular communication are described in more details as follows:
• Encoding is the phase during which a sender bio-nanomachine translates information into information molecules that the receiver bio-nanomachine can detect. Information may be encoded in various forms within the information molecules, such as in the three-dimensional structure of the information molecule (e.g. a specific type of molecule), in the specific molecules that compose the information molecules (e.g. DNA is formed by the specific sequence of nucleotides), or in the concentration of information molecules (i.e. the number of information molecules per unit volume of solvent molecules) modulated over time
Sending is the phase by which a sender bio-nanomachine releases information molecules into the environment. A sender bio-nanomachine may release information molecules by either unbinding information molecules from the sender bio-nanomachine (e.g., by budding vesicles from a biological cell if a sender bio-nanomachine is a biological cell), or by opening a molecular gate that allows the information molecules to diffuse away (e.g., by opening a gap junction channel in the cell membrane of a sender bio-nanomachine). A sender bio-nanomachine may also catalyze a chemical reaction that produces information molecules elsewhere.
• Propagation is the phase during which information molecules move from the sender bio-nanomachine through the environment to the receiver bio-nanomachine. An information molecule may diffuse passively through the environment without using chemical energy, or may bind to a transport molecule (e.g., a molecular motor that generates motion) to actively propagate through the environment by breaking down ATP to form energy. During propagation, an interface molecule may also be necessary to protect information molecules from noise in the environment. For instance, an information molecule may be contained in a vesicle-based interface molecule and propagate through the environment. The vesicle prevents the information molecule from chemically reacting with other molecules outside the vesicle.
• Receiving is the phase during which the receiver bio-nanomachine captures information molecules propagating in the environment. One option for a receiver bio-nanomachine to capture information molecules is to have a surface structure permeable to the information molecules. For instance, a biological cell has a plasma-membrane permeable to some signal molecules and the receptors within the cell directly bind to the information molecules propagating in the environment. Another option is to use surface receptors that are capable of binding with a specific type of information molecule and inducing reactions within the receiver bio-nanomachine. Yet another option is to use surface channels (e.g., chemically gated-channels) that allow information molecules to flow into a receiver bio-nanomachine.
• Decoding is the phase during which the receiver bio-nanomachine, upon capturing information molecules, decodes the received molecules into a chemical reaction. Chemical reactions for decoding at the receiver bio-nanomachine may include the production of new molecules, the performing of a simple task, or the production of another signal (e.g., sending other information molecules).
C. Modulation Techniques
In nano-networks, the information is sent using a sequence of symbols spread over sequential time slots as one symbol in each slot. The symbol sent by the transmitter is called the “intended symbol” and the symbol received at the receiver is called the “received symbol.” A variety of modulation techniques can be used for the mapping between messenger molecule reception and the received symbol, in other words, symbol detection. The symbol can be modulated over various “messenger molecule arrival properties” at the receiver, e.g., concentration, frequency, phase, molecule type, to form a signal.
There are two modulation techniques, CSK and MoSK, based on the unique properties of this communication paradigm.
Concentration Shift Keying (CSK): The concentration of the received messenger molecules is used as the amplitude of the signal. The receiver decodes the intended symbol as “1” if the number of messenger molecules arriving at the receiver during a time slot exceeds a threshold (τ), “0” otherwise. In order to represent different values in symbols, the transmitter releases different number of molecules for each value the symbol can represent: for “0” the transmitter releases n0 molecules whereas for “1”, n1 molecules are released. CSK is analogous to Amplitude Shift Keying (ASK) in classical communication. Instead of using two n values, e.g., n0 and n1, and a single threshold, the symbol can be tailored to represent b bits by using 2b different values with 2b – 1 threshold levels.
CSK can be implemented in practice as BCSK (Binary CSK) or QCSK (Quadruple CSK), depending on the bits per symbol rate.
• If b = 1, CSK is called Binary CSK (BCSK)
• If b = 2, CSK is called Quadruple CSK (QCSK).
This communication system using CSK technique can be affected adversely from Inter Symbol Interference (ISI) which can be caused by the surplus molecules from previous symbols. Due to the diffusion dynamics, some messenger molecules may arrive after their intended time slot. These molecules cause the receiver to decode the next intended symbol incorrectly.
Molecular Shift Keying (MoSK): MoSK utilizes the emission of different types of messenger molecules to represent information. For the transmission of n information bits in one symbol, 2n different molecules are utilized, each representing a combination of the 2n different n bit sequences. The transmitter releases one of these molecules based on the current intended symbol. The receiver decodes the intended symbol based on the type and the concentration of the molecule received during a time slot. If the concentration of a single molecule type exceeds the threshold τ at the receiver, the symbol is decoded based on the bit sequence corresponding to this molecule type. On the other hand, an error is assumed, if the concentration of any molecule types does not exceed the threshold or the concentration of more than one molecule type exceeds the threshold.
Similar to the CSK technique, the surplus molecules from the previous symbols also cause ISI when MoSK technique is used. However, MoSK is less susceptible to ISI effects than the CSK technique when the bits per symbol rate (b) are greater than 1. In this case, a single threshold is used for MoSK whereas b thresholds are required for CSK. However, this advantage of the MoSK technique comes at the cost of the requirement for complex molecular mechanisms at both the transmitter and the receiver for messenger synthesis and decoding purposes, respectively. Also, a corruption in such a messenger molecule may cause some or all of the information in the symbol to get lost. This information corruption may cause severe problems since a corruption may only change the bit sequence inside the messenger molecule and the resulting corrupted molecule may still represent some information albeit not the one sent by the transmitter. Without special mechanisms designed to detect (and/or correct) such errors, the receiver cannot distinguish a correct molecule from a corrupted one. In order to protect the messenger molecules from such environmental corruption, it can be sheathed inside a protective shield, e.g., vesicles, at the transmitter. When the receiver gets the vesicle, it extracts the messenger molecule inside and discards the vesicle [9].
D. Applications Envisioned
Functional applications of molecular communication use bio-nanomachines to sense molecules, transport molecules, and modify molecules. Applications are being considered in biomedical, environmental, and manufacturing areas. Here we briefly discuss how molecular communication may apply to the three areas:
1) Biomedical Applications:
• Lab-on-a-chip: In lab-on-a-chip applications, the chemical analysis of biological samples is performed on a chip with dimensions in the mm to cm range. Analysis of biological samples is required for medical applications to diagnose disease or for general scientific studies of biological samples. Molecular communication provides techniques to transport specific molecules to specific locations of a chip. In one possible implementation, each transport molecule (e.g., a microtubule filament which glides along a surface of molecular motors) has an interface molecule to selectively transport a specific type of molecule of the sample and an addressing molecule (e.g., a single-stranded DNA sequence which binds to a complimentary sequence) for where on the chip to transport the molecule [26]. Molecular communication may have implementation advantages since it uses molecular level mechanisms for directly manipulating the molecules in the sample and does not require translation of information to/from electrical signals. In addition, molecular communication may allow lab-on-a-chip applications to scale further down since molecular communication components can be at the nanometer scale.
• Health monitoring: Monitoring performed within an organism (i.e. human, animal, or plant) enables identification of specific molecules in the body. The existence of specific molecules may serve as a bio-marker for a disease or a certain medical condition. More detailed information such as the spatial distribution of molecules can be used to provide information for further diagnosis. For such applications, bio-nanomachines are implanted in the body, and molecular communication provides potential methods for gathering information about the molecules of the body, aggregating the information, and transmitting it to external devices.
• Drug delivery: Drug delivery systems facilitate the administration and distribution of drugs within an organism. Implanted bio-nanomachines can use molecular signals within the organism, or molecular signals released by other bio-nanomachines, to pinpoint target locations for drug delivery and thereby reduce the potential for side-effects at non-target locations. Existing techniques include the use of capsules that release drugs in response to specific conditions such as temperature. Molecular communication may provide alternative techniques to control the release of drugs such as cooperative drug release by a group of bio-nanomachines.
• Regenerative medicine: Bio-nanomachines made of living cells can divide and grow to form a functional structure (e.g., tissues and organs). Such bio-nanomachines can be applied to aspects of regenerative medicine. As in developmental biology, the formation of a functional structure would progress based on molecular communication among bio-nanomachines. Molecular communication provides techniques to control patterns of communication and thereby affect the growth and differentiation of the bio-nanomachines into specific structures.
2) Environmental Applications:
• Environment monitoring: The environment may be exposed to toxic or radioactive agents. Information about these molecules could help to identify problems and to provide a map for cleaning up the environment in response to illegal contamination or an accidental spill. Bio-nanomachines can be integrated into large or microscale environments to map out the locations of molecules within that environment. Molecular communication provides techniques for the bio-nanomachines to process molecular information from the environment and communicate this information to other bio-nanomachines.
• Waste/pollution control: The monitoring of molecules in the environment may provide information that is only of low-level resolution. Bio-nanomachines could be deployed to monitor molecules in the environment and thus identify more precisely the location of a toxic source. For example, bio-nanomachines can identify and use specific
Types of molecules to tag waste in the environment. They can also move to the source of the toxin or can also amplify molecular signals that in turn guide other bio-nanomachines or larger-scale devices to the location of the molecular signal to degrade the material into a non-toxic or reusable form.
3) Manufacturing Applications:
• Pattern and structure formation: Molecular communication can be used to control the transport of molecules, and can be modified to produce novel patterns of molecules. A system can be programmed to form a specific pattern of molecules by having each location in the system correspond to an address and then transporting bio-nanomachines or specific types of molecules to each address. After the molecules or bio-nanomachines are transported to each address, chemical processes can be activated to complete the structure. It may also be possible to augment a biological system with molecular addresses and transport molecules by the augmented addresses. If patterning processes can be programmed in sequences of molecules, then it may be possible to produce a large variety of shapes and structures while using the same manufacturing machinery.
LITERATURE SURVEY
This section introduces the related work on molecular communication done by various authors.
Baris Atakan, Ozgur B.Akan [1] in their paper have explained about an information theoretical approach for capacity of a molecular communication channel between two nanomachines. A molecular communication model is first introduced. Then, using the principles of mass action kinetics they have given a molecule delivery model for the molecular communication between two nanomachines called as Transmitter Nanomachine (TN) and Receiver Nanomachine (RN). Then, a closed form expression is derived for capacity of the channel between TN and RN. Numerical results show that selecting appropriate molecular communication parameters such as temperature of environment, concentration of emitted molecules, distance between nanomachines and duration of molecule emission, it can be possible to achieve maximum capacity for the molecular communication channel between two nanomachines.
Yuki Moritani, Satoshi Hiyama and Tatsuya Suda [4] in their journal have identified the key research challenges in molecular communication including the design of a receiver, design of a propagation system, design of a communication interface, and the mathematical modeling of the molecular communication system and components.
Tadashi Nakano et al. [6], in their paper has anticipated the creation of future applications such as monitoring the condition of a human body, regenerating biological tissues and organs, and interfacing artificial devices with neural systems from the ability of engineered biological nanomachines to communicate with biological systems at the molecular level. From the viewpoint of communication theory and engineering, molecular communication is proposed as a new paradigm for engineered biological nanomachines to communicate with the natural biological nanomachines which form a biological system. Distinct from the current telecommunication paradigm, molecular communication uses molecules as the carriers of information; sender biological nanomachines encode information on molecules and release the molecules in the environment, the molecules then propagate in the environment to receiver biological nanomachines, and the receiver biological nanomachines biochemically react with the molecules to decode information. Current molecular communication research is limited to small-scale networks of several biological nanomachines. Key challenges to bridge the gap between current research and practical applications include developing robust and scalable techniques to create a functional network from a large number of biological nanomachines. Developing networking mechanisms and communication protocols is anticipated to introduce new avenues into integrating engineered and natural biological nanomachines into a single networked system. In this paper, the authors have presented the state-of-the-art in the area of molecular communication by discussing its architecture, features, applications, design, engineering, and physical modeling. They have also discussed the challenges and opportunities in developing networking mechanisms and communication protocols to create a network from a large number of bio-nanomachines for future applications.
Tadashi Nakano et al. [11], in their paper have developed a layered architecture of molecular communication and describe research issues that molecular communication faces at each layer of the architecture. Specifically, this paper applies a layered architecture approach, traditionally used in communication networks, to molecular communication, decomposes complex molecular communication functionality into a set of manageable layers, identifies basic functionalities of each layer, and develops a descriptive model consisting of key components of the layer for each layer. This paper also discusses open research issues that need to be addressed at each layer. In addition, this paper provides an example design of targeted drug delivery, a nanomedical application, to illustrate how the layered architecture helps design an application of molecular communication. The primary contribution of this paper is to provide an in-depth architectural view of molecular communication. Establishing a layered architecture of molecular communication helps organize various research issues and design concerns into layers that are relatively independent of each other, and thus accelerates research in each layer and facilitates the design and development of applications of molecular communication.
M.S.Kuran, H.B. Yilmaz, T.Tugcu and I.F. Akyildiz [12], in their paper have proposed novel modulation techniques called Concentration Shift Keying (CSK) and Molecule Shift Keying (MoSK) for coding and decoding information of the so-called messenger molecule concentration waves in nanonetworks. The first technique, CSK, modulates the information via the variation in the concentration of the messenger molecules whereas MoSK utilizes different types of messenger molecules to represent the information. Using simulation, the performance of these modulation techniques is evaluated in terms of susceptibility to noise and transmission power requirements. The new techniques achieve high channel capacity values, in particular, the MoSK technique exhibits more robustness against noise and requires less power.
M S Kuran, H B Yilmaz and T Tugcu [13], in their paper have described Communication via diffusion as an effective and energy efficient method for transmitting information in nanonetworks. However, the histogram of the molecules hitting at the receiver has a long tail. The molecules constituting this long tail significantly decrease the data rate since the selection of high symbol duration becomes mandatory to have acceptable bit error rates. In this paper, a novel signal shaping technique for nanonetworking is proposed. This technique aims to decrease the variance of the hitting times via special so-called “destroyer molecules”. This system is inspired by the neuromuscular junction in biology, in which Acetylcholinesterase molecules are used to clean the channel for further transmissions. A molecular communication channel where a tunnel composed of destroyer molecules exists between the communicating pair is discussed. Simulation results show that the inclusion of such destroyer molecules decrease both the mean and the variance of the hitting time distribution, allowing better time-responsiveness and higher data rate for the communication via diffusion system.
M. Pieobon and Ian F Akyidiz [14], in their paper provides a closed-form expression for the information capacity of an MC system based on the free diffusion of molecules, which is of primary importance to understand the performance of the MC paradigm. The provided capacity expression is independent from any coding scheme and takes into account the two main effects of the diffusion channel: the memory and the molecular noise. For this, the diffusion is decomposed into two processes, namely, the Fick’s diffusion and the particle location displacement, which are analyzed as a cascade of two separate systems. The Fick’s diffusion captures solely the channel memory, while the particle location displacement isolates the molecular noise. The MC capacity expression is obtained by combining the two systems as function of the diffusion coefficient, the temperature, the transmitter–receiver distance, the bandwidth of the transmitted signal, and the average transmitted power. Numerical results show that a few kilobits per second can be reached within a distance range of tenth of micrometer and for an average transmitted power around 1 pW.
Y Chahibi et al. [15] have provided a model of the Antibody-Medicated Drug Delivery System (ADDS). (ADDS) is emerging as one of the most encouraging therapeutic solutions for treating several diseases such as human cancers. ADDS use small molecules (antibodies) that propagate in the body and bind selectively to their corresponding receptors (antigens) expressed at the surface of the diseased cells. In this paper, the Molecular Communication (MC) paradigm, where information is conveyed through the concentration of molecules, is advocated for the engineering of ADDS and modeling their complex behavior, to provide a realistic model without the over-complication of system biology models, and the limitations of experimental approaches. The peculiarities of antibodies, including their anisotropic transport and complex electrochemical structure, are taken into account to develop an analytical model of the ADDS transport and antigen binding kinetics. The end-to-end response of ADDS, from the drug injection to the drug absorption, is mathematically derived based on the geometry of the antibody molecule, the electrochemical structure of the antibody-antigen complex, and the physiology of the patient. The accuracy of the MC model is validated by finite element simulations. The implications of the complex interplay between the transport and kinetics parameters on the performance of ADDS are effectively captured by the proposed MC model. The MC model of ADDS will enable the discovery and optimization of drugs in a versatile, cost-efficient, and reliable manner.
N Farshad et al. [16] in their journal have confined space molecular communication system, where molecules or information carrying particles are used to transfer information on a microfluidic chip. Considering that information-carrying particles can follow two main propagation schemes: passive transport, and active transport, it is not clear which achieves a better information transmission rate. Motivated by this problem, they have compared and analyzed both propagation schemes by deriving a set of analytical and mathematical tools to measure the achievable information rates of the on-chip molecular communication systems employing passive to active transport. They have also used this toolbox to optimize design parameters such as the shape of the transmission area, to increase the information rate. Furthermore, the effect of separation distance between the transmitter and the receiver on information rate is examined under both propagation schemes, and a guidepost to design an optimal molecular communication setup and protocol is presented.
Atakan, B. [17] in his paper has described molecular communication as a promising nanoscale communication paradigm that enables nanomachines to exchange information by using molecules as communication carrier. Up to now, the molecular communication channel between a transmitter nanomachine (TN) and a receiver nanomachine (RN) has been modeled as either concentration channel or timing channel. However, these channel models necessitate exact time synchronization of the nanomachines and provide a relatively low communication bandwidth. In this paper, the Molecular Array- based Communication (MARCO) scheme is proposed, in which the transmission order of different molecules is used to convey molecular information without any need for time synchronization. The MARCO channel model is first theoretically derived, and the intersymbol interference and error probabilities are obtained. Based on the error probability, achievable communication rates are analytically obtained. Numerical results and performance comparisons reveal that MARCO provides significantly higher communication rate, i.e., on the scale of 100 Kbps, than the previously proposed molecular communication models without any need for synchronization. More specifically, MARCO can provide more than 250 Kbps of molecular communication rate if intersymbol time and internode distance are set to 2 μs and 2 nm, respectively.
Moore, M.J et al. [18] in their paper describes the design of an in vitro molecular communication system and evaluates various approaches to maximize the probability of information molecules reaching a receiver(s) and the rate of information reaching the receiver(s). The approaches considered in this paper include propagating information molecules (diffusion or directional transport along protein filaments), removing excessive information molecules (natural decay or receiver removal of excessive information molecules), and encoding and decoding approaches (redundant information molecules to represent information and to decode information). Two types of molecular communication systems are considered: a unicast system in which a sender communicates with a single receiver and a broadcast system in which a sender communicates with multiple receivers. Through exploring tradeoffs among the various approaches on the two types of molecular communication systems, this paper identifies promising approaches and shows the feasibility of an in vitro molecular communication system.
Ling-San Meng et al. [19] in their paper have proposed various diversity techniques for Multi-Input Multi-Output (MIMO) transmissions based on molecular diffusion to improve the communication performance in nano-networks in the presence of Multi-User Interference (MUI). Analogous to radio communication, the concept of diversity and Spatial Multiplexing (SM) can be successfully applied in molecular communication. This paper is the first which investigates the aspects of MIMO transmissions for molecular communication. Numerical results show that the proposed diversity techniques can successfully lower the error rate. Further performance improvement can be obtained by properly allocating molecules among the transmission nodes if the Channel State Information (CSI) is available at the transmitter end. To optimize the system throughput, a dynamic switching mechanism between the diversity mode and the Spatial Multiplexing (SM) mode can be employed.
Einolghozati, A et al. [20] in their paper have proposed that a population of bacteria in a cluster is considered as a node capable of molecular transmission and reception. This proposition enables them to form a reliable node out of many unreliable bacteria. The bacteria inside a node sense the environment and respond accordingly. In this paper, the communication between two nodes, one acting as the transmitter and the other as the receiver is studied. The case in which the information is encoded in the concentration of molecules by the transmitter is considered. The molecules produced by the bacteria in the transmitter node propagate in the environment via the diffusion process. Then, their concentration sensed by the bacteria in the receiver node would decode the information. The randomness in the communication is caused by both the error in the molecular production at the transmitter and the reception of molecules at the receiver. The theoretical limits of the information transfer rate in such a setup versus the number of bacteria per node are studied. Finally M-ary modulation schemes are considered and the achievable rates and their error probabilities are studied.
Farsad N et al [21], in their paper have reviewed table top molecular communication platform that has been developed for transmitting short text messages across a room. The end-to-end system impulse response for this platform does not follow previously published theoretical works because of imperfect receiver, transmitter, and turbulent flows. Moreover, it is observed that this platform resembles a nonlinear system, which makes the rich body of theoretical work that has been developed by communication engineers not applicable to this platform. In this work, they have first introduced corrections to the previous theoretical models of the end-to-end system impulse response based on the observed data from experimentation. Using the corrected impulse response models, they formulated the nonlinearity of the system as noise and showed that through simplifying assumptions it can be represented as Gaussian noise. Through formulating the system's nonlinearity as the output a linear system corrupted by noise, the rich toolbox of mathematical models of communication systems, most of which are based on linearity assumption, can be applied to this platform
CONCLUSION AND FUTURE SCOPE
Molecular communication integrates techniques from biology for interacting with biological systems, from nanotechnology for enabling nano- to microscale interactions, and from computer science for designing scalable and robust networks.
Molecular communication has high potential capacity for impact, since biological systems pervade many environments and applications, but the current techniques available for molecular communication are limited. The area of molecular communication is in its infancy and numerous challenges and opportunities exist to advance this area.
Recent research in molecular communication remains limited to the design and analysis of small-scale networks of several bio-nanomachines with simplistic assumptions about bionanomachines and the environment. A key challenge to advance the area of molecular communication to the next stage is to develop robust and scalable techniques to create large-scale networks which function in the environment of practical applications