Communication over Diffusion-Based Molecular Timing Channels

Murin, Yonathan; Farsad, Nariman; Chowdhury, Mainak; Goldsmith, Andrea

doi:10.1109/glocom.2016.7841672

Cited by 30 publications

(26 citation statements)

References 10 publications

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“…2) Timing-based Receivers: In the MC literature, timing channels have been used as a model for non-recurrent receivers [95], [98], [99], [96], [97]. Let T rls denote the vector containing the release times of the molecules by the transmitter and let T arv be the vector containing the respective arrival times of the molecules at the receiver.…”

Section: A Unified Signal Definitionmentioning

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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Section: A Unified Signal Definitionmentioning

confidence: 99%

Channel Modeling for Diffusive Molecular Communication—A Tutorial Review

et al. 2019

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“…One of the main results presented in [14] is that in the case of a Lévy-distributed additive noise, linear detection under multiple particle release has worse performance than linear detection based on a single particle release. This degradation is due to the fact that the Lévy distribution has heavy tails that render linear processing highly suboptimal.…”

Section: Introductionmentioning

confidence: 99%

“…This degradation is due to the fact that the Lévy distribution has heavy tails that render linear processing highly suboptimal. It was further shown in [14] that for a small number of released particles, the probability of error achieved by the FA detector is indistinguishable from that achieved by the ML detector; thus, this detector provides a simple and attractive alternative to ML detection for a small number of released particles.…”

Section: Introductionmentioning

confidence: 99%

Exploiting Diversity in One-Shot Molecular Timing Channels via Order Statistics

Murin

Farsad

Chowdhury

et al. 2018

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

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We study diversity in one-shot communication over molecular timing channels. We consider a channel model where the transmitter simultaneously releases a large number of information particles, while the information is encoded in the time of release. The receiver decodes the information based on the random time of arrival of the information particles. The random propagation is characterized by the general class of right-sided unimodal densities. We characterize the asymptotic exponential decrease rate of the probability of error as a function of the number of released particles, and denote this quantity as the system diversity gain. Four types of detectors are considered: the maximum-likelihood (ML) detector, a linear detector, a detector that is based on the first arrival (FA) among all the transmitted particles, and a detector based on the last arrival (LA). When the density characterizing the random propagation is supported over a large interval, we show that the simple FA detector achieves a diversity gain very close to that of the ML detector. On the other hand, when the density characterizing the random propagation is supported over a small interval, we show that the simple LA detector achieves a diversity gain very close to that of the ML detector.The authors are with the

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“…The resulting channels are commonly referred to as timing channels. Communication over timing channels was studied in three main contexts: communication via queues, i.e., queuing timing channels [1]- [5], molecular communications, i.e., molecular timing channels, [6]- [11], and covert (secure) timing channels [12], [13].…”

Section: Introductionmentioning

confidence: 99%

“…In particular, in molecular communications, the particles propagate to the receiver following a random Brownian path. When the propagation is based solely on diffusion, the additive noise associated with random delay follows the Lévy distribution [11]. When the diffusion is accompanied by a drift, this additive noise follows the inverse Gaussian (IG) distribution [7], [8].…”

Section: Introductionmentioning

confidence: 99%

Diversity Gain of One-Shot Communication over Molecular Timing Channels

Murin

Chowdhury

Farsad

et al. 2017

GLOBECOM 2017 - 2017 IEEE Global Communications Conference

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We study diversity in one-shot communication over molecular timing channels. In the considered channel model the transmitter simultaneously releases a large number of information particles, where the information is encoded in the time of release. The receiver decodes the information based on the random time of arrival of the information particles. We characterize the asymptotic exponential decrease rate of the probability of error as a function of the number of released particles. We denote this quantity as the system diversity gain, as it depends both on the number of particles transmitted as well as the receiver detection method. Three types of detectors are considered: the maximumlikelihood (ML) detector, a linear detector, and a detector that is based on the first arrival (FA) among all the transmitted particles. We show that for random propagation characterized by right-sided unimodal densities with zero mode, the FA detector is equivalent to the ML detector, and significantly outperforms the linear detector. Moreover, even for densities with positive mode, the diversity gain achieved by the FA detector is very close to that achieved by the ML detector and much higher than the gain achieved by the linear detector.

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Communication over Diffusion-Based Molecular Timing Channels

Cited by 30 publications

References 10 publications

Channel Modeling for Diffusive Molecular Communication—A Tutorial Review

Channel Modeling for Diffusive Molecular Communication—A Tutorial Review

Exploiting Diversity in One-Shot Molecular Timing Channels via Order Statistics

Diversity Gain of One-Shot Communication over Molecular Timing Channels

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