A Semi-Analytical Method for Channel Modeling in Diffusion-Based Molecular Communication Networks

Zoofaghari, Mohammad; Arjmandi, Hamidreza; Etemadi, Ali; Balasingham, Ilangko

doi:10.1109/tcomm.2021.3065372

Cited by 5 publications

(8 citation statements)

References 42 publications

(66 reference statements)

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“…The paper provides simple and exact closed-form inversion formulas based on the dispersal model for both cases of concentration profiles. Using Green's second theorem [159], a sequence based on Prony's method was developed to estimate the intended source parameter. The use of Green's second theorem links the boundary and obstacle surface concentration measurements to the abnormality sources.…”

Section: ) Classification and Discrete Modelsmentioning

confidence: 99%

“…The standard localization problem, formulated in (22), solves inverse problem to find Q Ab and r Ab . However, finding closed-form analytical solution to ( 6) is cumbersome and only semianalytical or numerical solutions [159] are attainable in case of realistic scenarios. Assuming the analytical dispersion model in (22) and given the location of the sensors in a ddimensional space, at least d + 1 sensors are theoretically needed to localize the transmitter [12].…”

Section: ) Continuous Modelsmentioning

confidence: 99%

“…However, collecting and processing a huge amount of spatiotemporal data which is inevitable for training the MC systems makes it more challenging. Also, numerical methods for complex environments [159] may need prior information about the environment which cannot be obtained solely by the MC systems and may need external interventions.…”

Section: Modelingmentioning

confidence: 99%

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Abnormality Detection and Localization Schemes Using Molecular Communication Systems: A Survey

et al. 2023

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Abnormality detection and localization (ADL) have been studied widely in wireless sensor networks (WSNs) literature, where the sensors use electromagnetic waves for communication. Molecular communication (MC) has been introduced as an alternative approach for ADL in particular areas such as healthcare, being able to tackle the shortcomings of conventional WSNs, such as invasiveness, bioincompatibility, and high energy consumption. In this paper, we introduce a general framework for MCbased ADL, which consists of multiple tiers for sensing the abnormality and communication between different agents, including the sensors, the fusion center (FC), the gateway (GW), and the external node (e.g., a local cloud), and describe each tier and the agents in this framework. We classify and explain different abnormality recognition methods, the functional units of the sensors, and different sensor features. Further, we describe different types of interfaces required for converting the internal and external signals at the FC and GW. Moreover, we present a unified channel model for the sensing and communication links. We categorize the MC-based abnormality detection schemes based on the sensor mobility, cooperative detection, and cooperative sensing/activation. We also classify the localization approaches based on the sensor mobility and propulsion mechanisms and present a general framework for the externally-controllable localization systems. Finally, we present some challenges and future research directions to realize and develop MC-based systems for ADL. The important challenges in the MC-based systems lie in four main directions as implementation, system design, modeling, and methods, which need considerable attention from multidisciplinary perspectives.

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Section: ) Classification and Discrete Modelsmentioning

confidence: 99%

Section: ) Continuous Modelsmentioning

confidence: 99%

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Abnormality Detection and Localization Schemes Using Molecular Communication Systems: A Survey

et al. 2023

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“…In the transmission process of optical fiber communication network, interface modelling is a key step to optimize the communication network [11]. The forward and backward conversion of interface variables can be expressed as follows:…”

Section: Optical Fiber Communication Network Interface Modelingmentioning

confidence: 99%

Digital interference signal filtering on laser interface for optical fiber communication

Zhang¹,

Gadekallu

2022

EAI Endorsed Scal Inf Syst

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INTRODUCTION: Fiber laser communication is a communication method that uses laser and fiber medium to realize data transmission and information output OBJECTIVES: In order to reduce the signal interference of optical fiber communication laser interface and ensure the communication quality of optical fiber network. A filtering method of optical fiber communication laser interface interference signal based on digital filtering technology is designed. METHODS: In this paper, the interface model of optical fiber communication network is firstly constructed, and the interface noise signal is input into the digital filter bank. The digital quadrature filtering method and the least square algorithm are used to separate the denoised signals to reduce the crosstalk between the signals in the channel. In this way, the crosstalk component in the signal can be filtered out, and a better filtering processing effect of the laser interface interference signal can be achieved. RESULTS: The results of peak signal-to-noise ratio are above 25, which effectively filters the interference signal in the signal, and retains the effective signal completely. The intelligibility of optical fiber communication network in signal communication is above 0.94, and the highest value is 0.986. The distortion degree are all below 0.025, and the minimum value is 0.004. The communication bit error rate are all below 0.001, which ensures the communication quality of the network. CONCLUSION: The experimental results show that the signal noise reduction effect of the proposed method is good, which provides a reliable basis for filtering and separating interference signals of optical fiber communication laser interface.

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“…The general HBC framework is able to model the interaction of different active transport mechanisms across the biological barriers. Considering the general HBCs for objects, transceivers, and borders in an environment with arbitrary geometries, a semianalytical approach has been recently proposed to model the pure diffusion channel [12].…”

Section: Introductionmentioning

confidence: 99%

Modeling Molecular Communication Channel in the Biological Sphere With Arbitrary Homogeneous Boundary Conditions

Zoofaghari

Etemadi

Arjmandi

et al. 2021

IEEE Wireless Commun. Lett.

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Diffusion-based molecular communication (DMC) is envisioned to realize nanonetworks for health applications. Inspired by sphere-like entities in the body, modeling diffusion channel in the biological sphere is motivated. The boundary condition in such biological environments is considered as homogeneous boundary conditions (HBC) that can simply model the molecular processes over biological barriers, e.g., carriermediated transport and transcytosis over the blood vessel walls. In this paper, we model the diffusive communication channel between a point source transmitter and a transparent receiver arbitrarily located inside a spherical environment with HBC. To this end, the concentration Green's function (CGF) is analytically derived in the Fourier domain. Statistics of the signal received at the receiver is computed based on the derived CGF to obtain the analytical results. The analytical results are accurately confirmed with particle-based simulation (PBS). The performance of a simple on-off keying modulation scheme is also examined in terms of error probability.

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A Semi-Analytical Method for Channel Modeling in Diffusion-Based Molecular Communication Networks

Cited by 5 publications

References 42 publications

Abnormality Detection and Localization Schemes Using Molecular Communication Systems: A Survey

Abnormality Detection and Localization Schemes Using Molecular Communication Systems: A Survey

Digital interference signal filtering on laser interface for optical fiber communication

Modeling Molecular Communication Channel in the Biological Sphere With Arbitrary Homogeneous Boundary Conditions

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