Transposition Errors in Diffusion-Based Mobile Molecular Communication

Haselmayr, Werner; Aejaz, Syed Muhammad Haider; Asyhari, A. Taufiq; Springer, Andreas; Guo, Weisi

doi:10.1109/lcomm.2017.2712605

Cited by 58 publications

(35 citation statements)

References 16 publications

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“…However, a passive receiver model was used in [14], which may not be suitable for modeling drug delivery systems since the effect of drug absorption cannot be captured. A diffusive absorbing receiver and the average distribution of the first hitting time, i.e., the mean of the channel impulse response (CIR), were derived for a one-dimensional environment without drift in [15] and with drift in [16]. Clearly, none of these works provides a complete statistical analysis of the three-dimensional (3D) time-variant channel with an absorbing receiver nor do they consider drug delivery systems.…”

Section: Introductionmentioning

confidence: 99%

Diffusive Mobile MC for Controlled-Release Drug Delivery with Absorbing Receiver

Cao

Ahmadzadeh

Jamali

et al. 2019

ICC 2019 - 2019 IEEE International Conference on Communications (ICC)

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Nanoparticle drug carriers play an important role in facilitating efficient targeted drug delivery, i.e., improving treatment success and reducing drug costs and side effects. However, the mobility of nanoparticle drug carriers poses a challenge in designing drug delivery systems. Moreover, healing results critically depend on the rate and time duration of drug absorption. Therefore, in this paper, we aim to design a controlledrelease drug delivery system with a mobile drug carrier that minimizes the total amount of released drugs while ensuring a desired rate of drug absorption during a prescribed time period. We model the mobile drug carrier as a mobile transmitter, the targeted diseased cells as an absorbing receiver, and the channel between the transceivers as a time-variant channel since the carrier mobility results in a time-variant absorption rate of the drug molecules. Based on this, we develop a molecular communication (MC) framework to design the controlled-release drug delivery system. In particular, we develop new analytical expressions for the mean, variance, probability density function, and cumulative distribution function of the channel impulse response (CIR). Equipped with the statistical analysis of the CIR, we design and evaluate the performance of the controlled-release drug delivery system. Numerical results show significant savings in the amount of released drugs compared to a constant-release rate design and reveal the necessity of accounting for drug carrier mobility for reliable drug delivery.

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Section: Introductionmentioning

confidence: 99%

Diffusive Mobile MC for Controlled-Release Drug Delivery with Absorbing Receiver

Cao

Ahmadzadeh

Jamali

et al. 2019

ICC 2019 - 2019 IEEE International Conference on Communications (ICC)

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“…The derived PDF is also verified through particle-based simulations in[16]. It is worth noting that the PDF in (4) is equivalent to the first hitting time PDF[14, Eq. (6)] for diffusion channels without flow and mobile CN and FC.…”

mentioning

confidence: 60%

“…The quantity N k [j + 1] denotes MSI, i.e., background noise arising due to molecules received from other sources, which can be modeled as a Gaussian distributed random variable with mean µ o and variance σ 2 o under the assumption that the number of interfering sources is sufficiently large [17]. Also, 1 Similar to [14]- [16], the movement of each CN and the FC is modeled as a one dimensional Gaussian random walk. It is assumed that the movement of each CN and the FC does not disrupt the propagation of the information molecules.…”

Section: System Modelmentioning

confidence: 99%

Abnormality Detection Inside Blood Vessels With Mobile Nanomachines

Varshney

Patel

Deng

et al. 2018

IEEE Trans. Mol. Biol. Multi-Scale Commun.

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Motivated by the numerous healthcare applications of molecular communication within Internet of Bio-Nano Things (IoBNT), this work addresses the problem of abnormality detection in a blood vessel using multiple biological embedded computing devices called cooperative biological nanomachines (CNs), and a common receiver called the fusion center (FC). Due to blood flow inside a vessel, each CN and the FC are assumed to be mobile. In this work, each of the CNs perform abnormality detection with certain probabilities of detection and false alarm by counting the number of molecules received from a source, e.g., infected tissue. These CNs subsequently report their local decisions to a FC over a diffusion-advection blood flow channel using different types of molecules in the presence of inter-symbol interference, multi-source interference, and counting errors. Due to limited computational capability at the FC, OR and AND logic based fusion rules are employed to make the final decision after obtaining each local decision based on the optimal likelihood ratio test. For the aforementioned system, probabilities of detection and false alarm at the FC are derived for OR and AND fusion rules. Finally, simulation results are presented to validate the derived analytical results, which provide important insights.

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“…Since mpt, τ q and σpt, τ q do not oscillate but are well-behaved and smooth functions of t as shown in Section VI, a small value of N (e.g., N " 5) is usually enough to meet the continuous constraint (24) for all t. Having m pt, τ q in (11) and σ pt, τ q in (13) and treating the α i as real numbers, (26) can be readily solved numerically as a linear program. We note that although the numbers of drug molecules α i are integers, for tractability, we solve (26) for real α i and quantize the results to the nearest integer values.…”

Section: A Controlled-release Designmentioning

confidence: 99%

Diffusive Mobile MC With Absorbing Receivers: Stochastic Analysis and Applications

Cao

Ahmadzadeh

Jamali

et al. 2019

IEEE Trans. Mol. Biol. Multi-Scale Commun.

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This paper presents a stochastic analysis of the time-variant channel impulse response (CIR) of a three dimensional diffusive mobile molecular communication (MC) system where the transmitter, the absorbing receiver, and the molecules can freely diffuse. In our analysis, we derive the mean, variance, probability density function (PDF), and cumulative distribution function (CDF) of the CIR. We also derive the PDF and CDF of the probability p that a released molecule is absorbed at the receiver during a given time period.The obtained analytical results are employed for the design of drug delivery and MC systems with imperfect channel state information. For the first application, we exploit the mean and variance of the CIR to optimize a controlled-release drug delivery system employing a mobile drug carrier. We evaluate the performance of the proposed release design based on the PDF and CDF of the CIR. We demonstrate significant savings in the amount of released drugs compared to a constant-release scheme and reveal the necessity of accounting for the drug-carrier's mobility to ensure reliable drug delivery. For the second application, we exploit the PDF of the distance between the mobile transceivers and the CDF of p to optimize three design parameters of an MC system employing on-off keying modulation and threshold detection. Specifically, we optimize the detection threshold at the receiver, the release profile at the transmitter, and the time duration of a bit frame. We show that the proposed optimal designs can significantly improve the system performance in terms of the bit error rate and the efficiency of molecule usage.

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Transposition Errors in Diffusion-Based Mobile Molecular Communication

Cited by 58 publications

References 16 publications

Diffusive Mobile MC for Controlled-Release Drug Delivery with Absorbing Receiver

Diffusive Mobile MC for Controlled-Release Drug Delivery with Absorbing Receiver

Abnormality Detection Inside Blood Vessels With Mobile Nanomachines

Diffusive Mobile MC With Absorbing Receivers: Stochastic Analysis and Applications

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