A Tunnel-based Approach for Signal Shaping in ... - Semantic Scholar

IEEE International Conference on Communications 2013: IEEE ICC'13 - 3rd International Workshop on Molecular and Nanoscale Communication (MoNaCom)

A Tunnel-based Approach for Signal Shaping in Molecular Communication Mehmet S¸u¨ kr¨u Kuran, H. Birkan Yilmaz, T. Tugcu Department of Computer Engineering Bogazici University 34342, Bebek, Istanbul, TURKEY e-mail: {sukru.kuran, birkan.yilmaz, tugcu}@boun.edu.tr

Abstract—Communication via diffusion is 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 a 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. We consider a molecular communication channel where a tunnel composed of destroyer molecules exist between the communicating pair. 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. Index Terms—nanonetworks, communication via diffusion, molecular communication, acetylcholinesterase, signal shaping

I. I NTRODUCTION Molecular communication (MC) is a new interdisciplinary research paradigm including nanotechnology, biotechnology, and the Information and Communications Technology [1]. MC systems are mainly inspired by the vital communication functions observed in living organisms and they are indispensable for enabling micro- and/or nano-scale machines to communicate with each other. These fine-scale machines are capable of performing simple tasks such as actuation and sensing. Clusters composed of such machines cooperating with each other are expected to enable the realization of applications such as Health Monitoring, Nanomedicine, Tissue Engineering, and Environment Monitoring [1]. In the literature, various MC systems, such as Communication via Diffusion (CvD), calcium signalling, microtubules, pheromone signaling, and bacterium-based communication are proposed ( [2]–[6] ). Among these systems, CvD is an effective and energy efficient method for transporting information in nanonetworks [7]. In CvD, the information is transmitted via the propagation of messenger molecules through the environment where the transmitter and the receiver reside. Similar to the other well-known systems, the CvD system is also composed of five main processes: encoding, transmission, propagation, reception, and decoding. In the first step, the transmitter encodes the information onto a physical property of a molecular signal (e.g., concentration of molecules). Then, these molecules are released into the environment to form the

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transmitted signal. Following the physical characteristics of the channel, these molecules propagate through the environment. Some of these molecules arrive at the receiver (i.e., hit the receiver), and they form chemical bonds with the ligand receptors on the surface of the receiver. The properties of these received molecules (e.g., concentration, type) constitute the received signal. Finally, based on this signal the receiver decodes the information that is initially sent from the transmitter. Propagation of the messenger molecules obeys diffusion dynamics when released from the transmitter. Based on the properties of the environment and the type of molecules, some of these molecules reach the receiver while the rest dissipate in the environment. However, the histogram of the molecules hitting the receiver depicts that the hitting times of some molecules are too high [7]. These high hitting times have adverse effects over the communication system, such as high amounts of Intersymbol Interference (ISI), necessitating the selection of long symbol durations. As a result, the effective data rate of the CvD system is considerably reduced. Therefore, a shaping method for the received signal is necessary in the CvD system. At the first glance, as in the electromagnetic case, it can be argued that the shape of the received signal can be easily controlled by changing the shape of the transmitted signal. However as shown in [8] by Garralda et al., usage of different shapes of transmitted signals do not change the received signal significantly in such a system since the diffusion dynamics are extremely dominant in this communication channel. In this paper, an alternative approach for shaping the received signal is proposed. We elaborate on using a second type of molecule in the environment, which we call “Destroyer Molecules”, in order to shape the received signal, and as a result, reducing the variance of the hitting times of molecules. We adapt the concept from the Acetylcholine (ACh) - Acetylcholinesterase (AChE) relationship that is observed in the Neuromuscular Junctions (NMJ) of living organisms. The NMJ connects a nerve cell to a muscle cell via a gap called the synaptic cleft. After sending a contraction signal, in order to return the muscle cell to their resting state, AChE molecules destroy the messenger ACh molecules. This event reduces the variance of the signal and cleans the communication channel for the next contraction signal [9]. We consider a system that has a boundary of AChE-like destroyer molecules enclosing the intercellular space to form a tunnel between the transmitter and the receiver. This tunnel can be seen

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Fig. 1.

Neuromuscular junction (NMJ)

as guidance for messenger molecules and it decreases the variance of the signal. Hence, the proposed system eliminates the high variance in hitting times, and increases the channel capacity significantly via reducing the symbol duration and ISI. The rest of the paper is organized as follows. In Chapter 2, we explain the NMJ system and its components as a baseline to our proposed solution. In Chapter 3, we describe the tunnelbased environment for the CvD system that is proposed to shape the received signal and show the effect of the destroyer molecules over the properties of the hitting event. In Chapter 4, the channel capacity of such a system is evaluated using a binary channel and the Concentration Shift Keying modulation we developed in our previous work [10]. Finally, Chapter 5 concludes this paper. II. N EUROMUSCULAR J UNCTION NMJ is one of the many occurrences in biological systems where two cells communicate with each other using an intermediary molecule that propagates in the extracellular environment following diffusion dynamics. It is a semi-closed environment between a pair of nerve and muscle cell, with a typical length of (10 to 100) nm, and is used for the communication between these two different cell types ( [9], [11] ). When muscles in a specific part of the body need to be contracted, the nerve cells in that region send a signal to the muscle tissue through these junctions to trigger the contraction [12]. At the start of the muscle contraction procedure, a triggered nerve cell releases pre-synthesized special neurotransmitter molecules called ACh to the NMJ. These molecules propagate in this environment and when they get close to the cell membrane of the muscle cell, they form a bond with transmembrane receptors called ACh receptors (AChRs). This allows the opening up of ion channels at the cell membrane which in turn allows the passage of N a+ and K + ions. The increased

cytosolic concentration of these ions causes the muscle cell to be contracted. The neurotransmitters stay in the bounded state for some time after which the bond degrades and the ACh molecules are again set free to the NMJ. The degradation of this bond is crucial to the muscle contraction procedure, allowing the muscle to relax and gradually revert back to its original resting position, awaiting further contraction signals. As seen in Figure 1, the NMJ is a semi-closed environment and the molecules inside usually move between the two cells. Hence, after the degradation of the bonds between ACh and AChR, the neurotransmitter molecules are highly likely to re-bond with the receptors. Such an occurrence causes further unwanted muscle contractions, and after a few muscle contraction signals the NMJ will be filled with ACh molecules. This causes the ion channels linked to the AChRs to become inactive, which in turn blocks all further contraction signals. To keep the communication between the nerve and muscle cell couple, the ACh molecules in the environment should be removed from the NMJ after the muscle cell is successfully contracted. This cleaning process is achieved through the use of a secondary type of molecule, called AChE, which reside in the muscle cell part of the NMJ environment. AChE is a special kind of enzyme that is capable of attracting and hydrolyzing the ACh molecules into their two building blocks: Acetate and Choline. Since both of these substructures are incapable of forming bonds with AChR, we can say that in practice AChE molecules remove (or destroy) the ACh molecules from the NMJ. Thus, AChE molecules enable the muscle cell to be capable of responding to further contraction signals. AChE is a highly catalytic enzyme, a single AChE molecule can degrade 25,000 ACh molecules per second. Thus, the concentration and placement of AChE molecules in the NMJ is crucial. If there are too many AChE molecules in the NMJ or the nerve cell emits a low number of neurotransmitters, very few of these molecules reach to the AChRs and the muscle cells will not be triggered at all. Thus,

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the nerve cell releases a high number of molecules to the environment anticipating that some of these molecules will be destroyed before triggering the AChRs. In summary, it can be said that the nerve cell is responsible of making sure that the signal is transmitted to the muscle cell. On the other hand, both the reception of the neurotransmitter molecules and their removal afterwards to clean up the NMJ are the responsibilities of the muscle cell. III. C OMMUNICATION VIA D IFFUSION T UNNEL - BASED E NVIRONMENT

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(a) Logarithmic scale hitting time distribution Fig. 2.

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IN A

As shown in our previous work [7], the hitting time of a messenger molecule in case of a single transmitter single receiver (STSR) topology exhibits a right long-tailed distribution (in Figure 2, note that the X axis is in log scale). Due to the diffusion dynamics, a molecule released from the transmitter will follow a path close to the shortest path to the receiver with a high probability, especially if the distance between the transmitter and the receiver (d) is short. However, some molecules will stray off the shortest path and wander in the environment before reaching the receiver. Based on this result, we observe that a molecule released from the transmitter has a high probability of reaching the receiver pretty quickly, hence the spike-like part seen in Figure 2. However, there is a considerable probability that its reception will occur in a long time (e.g. where d = 8µm, P (Thit > 2500) = 0.19). In case where the transmitter emits many molecules, some of them arrive at the receiver late causing significant ISI and forcing the system to choose a long symbol duration to avoid high incorrect reception probabilities. A. Model Description If we look at the biological NMJ system from a communication perspective, the receiver can be considered utilizing specialized so-called “Destroyer Molecules” to control the shape of the signal and eliminate the undesired components

of a signal. Also, the usage of these molecules reduces or eliminates the effects of the ISI and allows the selection of shorter symbol durations. From a topological point of view, the destroyer molecules can be deployed in the environment in many different ways. In this work, following biological extensions such as filopodia and cytoneme, we choose to deploy these molecules to form a cylindrical tunnel-like structure that forms a spatially restricted path between the transmitter and the receiver (Figure 3). When a messenger molecule hits a destroyer molecule on this tunnel, it is assumed to be destroyed and removed from the environment.

Fig. 3.

Cylindrical tunnel environment for CvD

The main idea behind this type of deployment is to get rid of the stray messenger molecules in the environment so that only the ones that contribute to the spike in the reception time distribution remain while other molecules are eliminated in the environment. As in the case of AchE, we assume that these destroyer molecules are bigger in size compared to the messenger molecules and they are connected to one of the communicating pair through other destroyer molecules. We also assume that they are immobile in the environment. Due to the chemical attraction between the messenger and the destroyer molecules, when a messenger molecule gets close

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to a destroyer molecule, it is attracted by the destroyer and removed from the environment. The cylindrical tunnel has a radius of rtn , which is a variable in the simulations. In order to simplify the analysis, we assume that the whole tunnel is composed of destroyer molecules and any molecule that diverts from the shortest path between the transmitter and the receiver more than rtn is destroyed. B. Analysis of the Hitting Event In order to analyze the communication capability of this deployment scenario, we analyze two hitting properties: the probability to hit the receiver (Phit ) and hitting time at the receiver (Thit ). We simulate a STSR topology using Monte Carlo simulations whose parameters are given in Table I, and for each different combination of the rtn and d values, the simulations are repeated 1,000,000 times. The simulations are carried out by our own diffusion simulator which is written in the C language.

Phit values, one should keep that in mind that a biological celllike transmitter machine is capable of synthesizing millions of molecules in a second [7]. When we analyze the average hitting times at the receiver, decreasing rtn also decreases the average Thit value. Choosing rtn close to d reduces the average Thit value roughly ten times (Figure 5). This is again due to the elimination of slow moving molecules from the environment by the destroyer molecules. The last curve (rtn = 2µm) does not yield any results since no molecules arrive at the receiver when the d/rtn value is too high (i.e., all of them destroyed due to the narrowness of the tunnel). If the data points for d = 32µm would be analyzed, in addition to the rtn = 2µm curve, the rtn = 5µm curve is also expected to have no data point for this distance due to the same reason. 2

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Although the average hitting times give us some insight on the time-related effect of the destroyer molecules, for more detail the hit time distribution of the received molecules should be investigated. In Figure 6, we observe that the decrease in rtn not only reduces the spread of the distribution over time, but also straightens up the distribution. According to the hitting time figures, the cylindrical tunnel alters the shape and spread of the received molecular signal.

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IV. E VALUATION OF C HANNEL C APACITY

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As shown in Figure 4, the Phit value decreases as the radius of the cylindrical tunnel decrease. This is due to the fact that the molecules wandering off too much from the shortest path between the transmitter and receiver are destroyed by the destroyer molecules. A cylindrical tunnel with a small radius yields very low Phit values. It can be argued that for a given d value, rtn should be selected at least close to the d value in order to avoid extremely low hitting probabilities. Although the existence of destroyer molecules considerably reduce the

Based on the hitting properties, we evaluate the channel capacity and the data rate of this deployment scenario. We use a binary channel in which each symbol represents a single bit and according to the bit value of the current symbol the transmitter emits a number of molecules to the environment (no molecules, in case of a binary value of “0”; and n1 molecules in case of a binary value of “1”). Time is divided into equal parts called symbol durations (denoted as ts ), and a single symbol is transmitted during each ts . Similar to our previous work in [7], we choose the duration where α percent of the hitting molecules arrive at the receiver as the ts . The α value is selected as 80, which yields acceptable symbol

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calculated using the Phit values and the Bayesian rule for the marginal properties as below

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where x and y stands for the encoded transmitted symbol and the decoded received symbol respectively. The PX,Y (x, y) can be evaluated as below  P (Nt ≥ τ |sp , X = x), if y = 1 PX,Y (x, y) = PX (x) P (Nt ≤ τ |sp , X = x), if y = 0 (5) We assume that the transmitter sends a bit value of “0” and “1” with equal probability (i.e., PX (0) = PX (1)). Considering the ISI effect for different values of sp , we find the channel capacity (C(d, rtn , ts )) as C0 (d, rtn , ts ) + C1 (d, rtn , ts ) . (6) 2 By dividing the channel capacity with the symbol duration gives us the final data rate of the system C(d, rtn , ts ) =

using the distance between the transmitter and receiver (d), the radius of the cylindrical destroyer molecule tunnel (rtn ), the appropriate symbol duration (ts ), and the diffusion coefficient (D). Since in all the simulations conducted in this paper D is kept constant, we use Phit (d, rtn , ts ) notation for ’probability of hit the receiver’ in the rest of the paper. Assuming molecules propagate in the environment independently, if n molecules are released from the transmitter at the beginning of at a symbol duration, the number of molecules hit the receiver is a binomial random variable and can be written as Nc ∼ B(n, Phit (d, rtn , ts )).

(2)

As we show in [7], some of the surplus molecules belonging to the previous symbols arrive at the receiver during the current symbol duration. These molecules constitute the ISI in this system. Among those molecules, only the molecules from the last symbol have a significant effect on the current symbol. Similar to Equation 2, the number of molecules hitting at the receiver belonging to the previous symbol can be formulated as Np ∼ B(n, Phit (d, rtn , 2ts )) − B(n, Phit (d, rtn , ts )).

C(d, rtn , ts ) . (7) ts We evaluate the data rate for different values of rtn where n1 is selected as 500 which is well below a cell-like machine’s molecule synthesis capabilities [7]. As seen in Figure 7, deploying the destroyer molecules as a cylindrical tunnel considerably increases the data rate. The drop in the Phit values are compensated by the reduction in the Thit values. After d = 4µm, the data rate of cylindrical tunnel with rtn = 2µm drops very quickly. A similar drop is also apparent in case of rtn = 5µm, starting from d = 6µm. These drops are due to the fact that in these environments the path becomes too tight and molecules hit the receiver with only a very small probability. Thus, similar to the analysis of Phit , the d/rtn value becomes a critical parameter in achieving optimum data rate.

(3)

The summation of these two random variables give the total number of molecules arriving at the receiver within a given symbol duration, denoted as Nt . We use Gaussian approximation of the Binomial distributions in order to evaluate Nt . The receiver decides on the bit value of the symbol by comparing Nt with a given threshold τ . If Nt ≥ τ , then the symbol is decoded as “1”; if not, as “0”. Using a binary channel model, the channel capacity (Csp (d, rtn , ts )) for a given previous symbol (sp ) value is

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durations and considerably reduces the interference effect of surplus molecules onto the next symbol. We define a single molecule’s probability of hit the receiver as Phit (d, rtn , ts , D) (1)

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Effect of cylindrical tunnel environment on data rate

V. C ONCLUSION In this paper, we propose a tunnel-based environment for signal shaping in molecular communication using special molecules called destroyer molecules. This system is inspired from the neuromuscular junction in biology and aims to reduce the high variance in the hit time distribution of the CvD system which causes high propagation delays. We propose the deployment of the destroyer molecules in a cylindrical tunnel shaped structure between the communicating pair to control the shape of the received signal. We evaluate the performance of this environment in terms of probability to hit and hitting time to the receiver as well as the data rate of the system. Although the tunnel-based environment decreases the probability of hitting the receiver, it also reduces the mean and variance of the hitting time to the receiver considerably. This reduction in time enables the system to achieve higher data rates compared to a free diffusion environment. As the future work, we plan to extend this work by including the effect of energy consumption to the data rate calculation using the energy model we developed in our previous work. We also aim to analyze the effect of other tunnel shapes (e.g., half-conical) for destroyer molecule deployment which have less infrastructural requirements.

[8] N. Garralda, I. Llatser, A. Cabellos-Aparicio, and M. Pierobon, “Simulation-based evaluation of the diffusion-based physical channel in molecular nanonetworks,” in Computer Communications Workshops (INFOCOM WKSHPS), 2011 IEEE Conference on. IEEE, 2011, pp. 443–448. [9] R. D. Keynes and D. J. Aidley, Nerve and Muscle. Cambridge University Press, 2001. [10] M. S. Kuran, H. B. Yilmaz, T. Tugcu, and I. F. Akyildiz, “Modulation Techniques for Communication via Diffusion in Nanonetworks,” in 2011 IEEE International Conference on Communications (ICC). IEEE, 2011, pp. 1–5. [11] R. A. Freitas, Nanomedicine, Vol. I: Basic Capabilities, 1st ed. Landes Bioscience, 1999. [12] B. Alberts, A. Johnson, J. Lewis, M. Raff, K. Roberts, and P. Walter, Molecular Biology of the Cell, 5th ed. Garland Science, November 2007.

ACKNOWLEDGMENT This work is supported by the Scientific and Technical Research Council of Turkey (TUBITAK) under grant number 112E011, State Planning Organization of Turkey under grant number 2007K120610, (“TAM” project), and Bogazici University Research Fund (BAP) under grant number 6024. We also thank Emrecan Cakir for his assistance in the illustrations of this paper. R EFERENCES [1] S. Hiyama, Y. Moritani, T. Suda, R. Egashira, A. Enomoto, M. Moore, and T. Nakano, “Molecular communication,” Journal-Institute of Electronics Information and Communication Engineers, vol. 89, no. 2, p. 162, 2006. [2] T. Suda, M. Moore, T. Nakano, R. Egashira, and A. Enomoto, “Exploratory research on molecular communication between nanomachines,” in Genetic and Evolutionary Computaion Conference, (GECCO ’05). ACM, June 2005. ¨ [3] M. S. Kuran, T. Tugcu, and B. Ozerman Edis, “Calcium signaling: overview and research directions of a molecular communication paradigm,” Wireless Communications, IEEE, vol. 19, no. 5, pp. 20–27, 2012. [4] A. Enomoto, M. Moore, T. Nakano, R. Egashira, and T. Suda, “A molecular communication system using a network of cytoskeletal filaments,” in Nanotechnology Conference and Trade Show, (NANOTECH ’06), 9th, vol. 1, May 2006, pp. 725–728. [5] L. P. Gin´e and I. F. Akyildiz, “Molecular communication options for long range nanonetworks,” Computer Networks, vol. 53, no. 16, pp. 2753–2766, August 2009. [6] L. Cobo and I. Akyildiz, “Bacteria-based communication in nanonetworks,” Nano Communication Networks, vol. 1, no. 4, pp. 244–256, 2010. ¨ [7] M. S. Kuran, H. B. Yilmaz, T. Tugcu, and B. Ozerman, “Energy model for communication via diffusion in nanonetworks,” Nano Communication Networks, vol. 1, no. 2, pp. 86–95, 2010.

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