Channel Capacity Analysis of a Comprehensive Absorbing Receiver for Molecular Communication via Diffusion

Liu, Shenghan; Wei, Zhuangkun; Wang, Xiang; Zhao, Chenglin

doi:10.1109/access.2020.3045439

Cited by 8 publications

(7 citation statements)

References 32 publications

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“…The state-space representation will subsequently allow us in Section III-C to incorporate the nonlinear effects due to receptor saturation that we have avoided in this section by setting κ a = 0. To derive the SSD, the expansion coefficients ȳµ in (27) and the synthesis equation (21) for y are transformed into discrete time using an impulse invariant transform [30]. This yields the following discrete-time SSD [29] ȳ i.e., the smaller D, κ a 0 , κ d , and κ e C E are, the smoother signal y(x, t) is and the larger may T be chosen.…”

Section: ) Functional Transformationsmentioning

confidence: 99%

“…For a numerical example, please see Table I. In the discrete-time SSD in ( 29) and (30), state equation (29) is the vector-valued discrete-time equivalent of (27), where vector ȳ ∈ R Q×1 contains Q coefficients ȳµ and diagonal matrix A ∈ R Q×Q contains Q eigenvalues s µ on its main diagonal, i.e.,…”

Section: ) Functional Transformationsmentioning

confidence: 99%

“…However, the model presented in [26] is limited to bandlimited input signals which are independent of the molecular binding events at the receiver. A statistical signal model for the reactive receiver without receptor saturation was presented in [27]. In [27], however, the saturation of the molecular receiver is neglected, i.e., molecules are assumed to bind statistically independently to receptors.…”

Section: Introductionmentioning

confidence: 99%

“…A statistical signal model for the reactive receiver without receptor saturation was presented in [27]. In [27], however, the saturation of the molecular receiver is neglected, i.e., molecules are assumed to bind statistically independently to receptors. As the probability for a molecule to find a free receptor decreases when more receptors are occupied, this assumption is in general not satisfied.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Saturating Receiver and Receptor Competition in Synaptic DMC: Deterministic and Statistical Signal Models

Lotter

Schäfer

Zeitler

et al. 2021

IEEE Trans.on Nanobioscience

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Synaptic communication is based on a biological Molecular Communication (MC) system which may serve as a blueprint for the design of synthetic MC systems. However, the physical modeling of synaptic MC is complicated by the possible saturation of the molecular receiver caused by the competition of neurotransmitters (NTs) for postsynaptic receptors. Receiver saturation renders the system behavior nonlinear in the number of released NTs and is commonly neglected in existing analytical models. Furthermore, due to the ligands' competition for receptors (and vice versa), the individual binding events at the molecular receiver are in general not statistically independent and the commonly used binomial model for the statistics of the received signal does not apply. Hence, in this work, we propose a novel deterministic model for receptor saturation in terms of a state-space description based on an eigenfunction expansion of Fick's diffusion equation. The presented solution is numerically stable and computationally efficient. Employing the proposed deterministic model, weshow that saturation at the molecular receiver effectively reduces the peak-value of the expected received signal and accelerates the clearance of NTs as compared to the case when receptor occupancy is neglected.We further derive a statistical model for the received signal in terms of the hypergeometric distribution which accounts for the competition of NTs for receptors and the competition of receptors for NTs. The proposed statistical model reveals how the signal statistics are shaped by the number of released NTs, the number of receptors, and the binding kinetics of the receptors, respectively, in the presence of competition. In particular, we show that the impact of these parameters on the signal variance is qualitatively different depending on the relative numbers of NTs and receptors. Finally, the accuracy of the proposed deterministic and statistical models is verified by particle-based computer simulations.

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Section: ) Functional Transformationsmentioning

confidence: 99%

Section: ) Functional Transformationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Saturating Receiver and Receptor Competition in Synaptic DMC: Deterministic and Statistical Signal Models

Lotter

Schäfer

Zeitler

et al. 2021

IEEE Trans.on Nanobioscience

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show abstract

“…In molecular communication theory, the channel impulse response reflects the expected number of molecules at the receiver, given that a certain number of messenger molecules has been released by the transmitter [13,14]. The channel impulse response for the MC system corresponding to the digestive system is derived by solving (2)-( 4) analytically.…”

Section: Channel Impulse Responsementioning

confidence: 99%

Channel Capacity of Starch and Glucose Molecular Communications in the Small Intestine Digestive Tract

Vimalajeewa¹,

Balasubramaniam²

2021

Preprint

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The emerging field of Molecular Communication (MC) aims to characterize biological-based signaling environments through information that are encoded into molecules. Since the birth of this field, a number of different applications and biological systems have been characterized using MC theory. This study proposes a new application and direction for MC, focusing on the digestive system, where we characterize and model the starch and glucose propagation along the small intestine (SI). Based on the advection-diffusion and reaction mechanisms, we define a channel capacity for the small intestine digestive tract that is dependent on the starch to glucose conversion, velocity flow within the tract, viscosity of the digest product, and length of the tract and position of the receivers for glucose absorption. The numerical results from the derived channel capacity model shows that the SI digestive capacity depends both on physiological factors of the digestive system and type of consumed food, where the digestive capacity is greater for shorter gastric emptying time, low viscosity of the digest product and efficient enzyme activity. We believe that our digital MC model of the digestive tract and lead to personalized diet for each individual, which can potentially avoid a number of different diseases (e.g., celiac disease).

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Coding in Diffusion-Based Molecular Nanonetworks: A Comprehensive Survey

et al. 2023

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Diffusion-based molecular nanonetworks exploit the diffusion of molecules, e.g., in free space or in blood vessels, for the purpose of communication. This article comprehensively surveys coding approaches for communication in diffusion-based molecular nanonetworks. In particular, all three main purposes of coding for communication, namely source coding, channel coding, and network coding, are covered. We organize the survey of the channel coding approaches according to the different channel codes, including linear block codes, convolutional codes, and inter-symbol interference (ISI) mitigation codes. The network coding studies are categorized into duplex network coding, physical-layer network coding, multi-hop nanonetwork coding, performance improvements of network-coded nanosystems, and network coding in mobile nanonetworks. We also present a comprehensive set of future research directions for the still nascent area of coding for diffusion-based molecular nanonetworks; specifically, we outline research imperatives for each of the three main coding purposes, i.e., for source, channel, and network coding, as well as for overarching research goals.

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Channel Capacity Analysis of a Comprehensive Absorbing Receiver for Molecular Communication via Diffusion

Cited by 8 publications

References 32 publications

Saturating Receiver and Receptor Competition in Synaptic DMC: Deterministic and Statistical Signal Models

Saturating Receiver and Receptor Competition in Synaptic DMC: Deterministic and Statistical Signal Models

Channel Capacity of Starch and Glucose Molecular Communications in the Small Intestine Digestive Tract

Coding in Diffusion-Based Molecular Nanonetworks: A Comprehensive Survey

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