Effect of Receptor Density and Size on Signal Reception in Molecular Communication via Diffusion With an Absorbing Receiver

Akkaya, Ali; Yilmaz, H. Birkan; Chae, Chan-Byoung; Tuǧcu, Tuna

doi:10.1109/lcomm.2014.2375214

Cited by 93 publications

(90 citation statements)

References 12 publications

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“…In general, P x (t), x ∈ {A, B}, depends on the release mechanism at the transmitter, the MC environment, and the properties of the receiver such as its size, the number of receptors, etc. For instance, assuming instantaneous molecule release and a point source transmitter, expressions for P x (t) can be found in [19] for a general reactive receiver and in [5] for an absorbing receiver. On the other hand, the external noise molecules originate from other MC links or natural sources which also employ type-A or type-B molecules.…”

Section: A System Modelmentioning

confidence: 99%

Symbol Synchronization for Diffusion-Based Molecular Communications

Jamali

Ahmadzadeh

Schober

2017

IEEE Trans.on Nanobioscience

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Symbol synchronization refers to the estimation of the start of a symbol interval and is needed for reliable detection. In this paper, we develop several symbol synchronization schemes for molecular communication (MC) systems where we consider some practical challenges, which have not been addressed in the literature yet. In particular, we take into account that in MC systems, the transmitter may not be equipped with an internal clock and may not be able to emit molecules with a fixed release frequency. Such restrictions hold for practical nanotransmitters, e.g., modified cells, where the lengths of the symbol intervals may vary due to the inherent randomness in the availability of food and energy for molecule generation, the process for molecule production, and the release process. To address this issue, we develop two synchronization-detection frameworks which both employ two types of molecule. In the first framework, one type of molecule is used for symbol synchronization and the other one is used for data detection, whereas in the second framework, both types of molecule are used for joint symbol synchronization and data detection. For both frameworks, we first derive the optimal maximum likelihood (ML) symbol synchronization schemes as performance upper bounds. Since ML synchronization entails high complexity, for each framework, we also propose three low-complexity suboptimal schemes, namely a linear filter-based scheme, a peak observation-based scheme, and a threshold-trigger scheme, which are suitable for MC systems with limited computational capabilities. Furthermore, we study the relative complexity and the constraints associated with the proposed schemes and the impact of the insertion and deletion errors that arise due to imperfect synchronization. Our simulation results reveal the effectiveness of the proposed synchronization schemes and suggest that the end-to-end performance of MC systems significantly depends on the accuracy of the symbol synchronization.

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Section: A System Modelmentioning

confidence: 99%

Symbol Synchronization for Diffusion-Based Molecular Communications

Jamali

Ahmadzadeh

Schober

2017

IEEE Trans.on Nanobioscience

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“…Fully-absorbing Receiver: For fully-absorbing receivers [73], [74], [64], [75], [22], [76], [77] (also referred to as perfect sinks), unlike the passive receiver model, the physical and chemical properties of the receiver geometry are taken into account. In particular, the signaling A molecules that reach the receiver via diffusion are absorbed as soon as they hit the receiver surface, see Fig.…”

Section: B Receiver Modelsmentioning

confidence: 99%

“…Remark 5: For a fully-absorbing receiver, it is implicitly assumed that the whole surface of the receiver is fullyabsorbing. The extension of this model to the case where the receiver surface is partially covered by fully absorbing receptor patches is considered in [74]. Moreover, the extension of the fully-absorbing receiver to take the impact of degradation and production noise into account, is considered in [64].…”

Section: B Receiver Modelsmentioning

confidence: 99%

Channel Modeling for Diffusive Molecular Communication—A Tutorial Review

et al. 2019

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Molecular communication (MC) is a new communication engineering paradigm where molecules are employed as information carriers. MC systems are expected to enable new revolutionary applications such as sensing of target substances in biotechnology, smart drug delivery in medicine, and monitoring of oil pipelines or chemical reactors in industrial settings. As for any other kind of communication, simple yet sufficiently accurate channel models are needed for the design, analysis, and efficient operation of MC systems. In this paper, we provide a tutorial review on mathematical channel modeling for diffusive MC systems. The considered end-to-end MC channel models incorporate the effects of the release mechanism, the MC environment, and the reception mechanism on the observed information molecules. Thereby, the various existing models for the different components of an MC system are presented under a common framework and the underlying biological, chemical, and physical phenomena are discussed. Deterministic models characterizing the expected number of molecules observed at the receiver and statistical models characterizing the actual number of observed molecules are developed. In addition, we provide channel models for timevarying MC systems with moving transmitters and receivers, which are relevant for advanced applications such as smart drug delivery with mobile nanomachines. For complex scenarios, where simple MC channel models cannot be obtained from first principles, we investigate simulation-driven and experimentallydriven channel models. Finally, we provide a detailed discussion of potential challenges, open research problems, and future directions in channel modeling for diffusive MC systems.

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“…Thus, by applying (14) and (15) in (16), it is easy to find a relationship between the release rate and λ * a . In addition, by using the Little's law [64], it is immediate to find that the mean number of busy receptors (servers) in the system is given by λ * a T tra f f , and the desired fraction f results equal to the overall utilization coefficient ρ, which is equal to…”

Section: Application To Drug Deliverymentioning

confidence: 99%

“…In addition, receptors saturation affects drug delivery and disease modeling [13]. However, most of research in the molecular communications either neglect the presence of individual receptors (absorbing receiver [14]), or neglect the absorption time of molecules (absorbing receptors [15]). A more accurate model, which partially addresses these shortcomings by modeling molecules absorption via receptors with a birth-death Markov process, is presented in [16].…”

Section: Introductionmentioning

confidence: 99%

A Molecular Communications Model for Drug Delivery

Femminella

Reali

Vasilakos

2015

IEEE Trans.on Nanobioscience

107

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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.

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Effect of Receptor Density and Size on Signal Reception in Molecular Communication via Diffusion With an Absorbing Receiver

Cited by 93 publications

References 12 publications

Symbol Synchronization for Diffusion-Based Molecular Communications

Symbol Synchronization for Diffusion-Based Molecular Communications

Channel Modeling for Diffusive Molecular Communication—A Tutorial Review

A Molecular Communications Model for Drug Delivery

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