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1.
IEEE Trans Nanobioscience ; 22(2): 259-267, 2023 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-35727781

RESUMO

Co-channel interference (CCI) is a performance limiting factor in molecular communication (MC) systems with shared medium. Interference alignment (IA) is a promising scheme to mitigate CCI in traditional communication systems. Due to the signal-dependent noise in MC systems, the traditional IA schemes are less useful in MC systems. In this paper, we propose a novel IA scheme in molecular interference channels (IFCs), based on the choice of releasing/sampling times. To cancel the aligned interference signals and reduce the signal dependent noise, we use molecular reaction in the proposed IA scheme. We obtain the feasible region for the releasing/sampling times in the proposed scheme. Further, we investigate the error performance of the proposed scheme. Our results show that the proposed IA scheme using reaction improves the performance significantly.

2.
Entropy (Basel) ; 24(8)2022 Aug 04.
Artigo em Inglês | MEDLINE | ID: mdl-36010743

RESUMO

In this paper, we study the degrees of freedom (DoF) of a frequency-selective K-user interference channel in the presence of an instantaneous relay (IR) with multiple receiving and transmitting antennas. We investigate two scenarios based on the IR antennas' cooperation ability. First, we assume that the IR receiving and transmitting antennas can coordinate with each other and that the transmitted signal of each transmitting antenna can depend on the received signals of all receiving antennas, and we derive lower and upper bounds for the sum DoF of this model. In an interference alignment scheme, we divide receivers into two groups called clean and dirty receivers. We design our scheme such that a part of the messages of clean receivers can be de-multiplexed at the IR. Thus, the IR can use these message streams for an interference cancellation at the clean receivers. Next, we consider an IR, the antennas of which do not have coordination with each other and where the transmitted signal of each transmitting antenna depends only on the received signal of its corresponding receiving antenna. We also derive lower and upper bounds for the sum DoF for this model of IR. We show that the achievable sum DoF decreases considerably compared with the coordinated case. In both of these models, our schemes achieve the maximum K sum DoF if the number of transmitting and receiving antennas is more than a finite threshold.

3.
IEEE Trans Nanobioscience ; 20(4): 426-435, 2021 10.
Artigo em Inglês | MEDLINE | ID: mdl-34152989

RESUMO

Bacterial populations are promising candidates for the development of the receiver and transmitter nanomachines for molecular communication (MC). A bacterial receiver is required to uptake the information molecules and produce the detectable molecules following a regulation mechanism. We have constructed a novel bacterial MC receiver using an inducible bacterial L-rhamnose-regulating operon. The proposed bacterial receiver produces green fluorescent protein (GFP) in response to the L-rhamnose information molecules following a quite fast regulation mechanism. To fabricate the receiver, the bacterial population has been transformed using a plasmid harboring L-rhamnose operon genes and gene expressing GFP in a microfluidic environment. We mathematically model the reception process of information molecules and characterize the model parameters by comparing the simulation results of the model in the employed microfluidic environment and the data obtained from the experimental setup. Based on the experimental results, the receiver is able to switch between different low and high concentrations. This work paves the way for the fabrication and modeling of any bacterial operon-based receiver with any proteins rather than GFP. Further, our experimental results indicate that the proposed bacterial receiver has a faster response to information molecules compared to the previous bacterial receiver based on the quorum sensing (QS) process.


Assuntos
Microfluídica , Ramnose , Proteínas de Bactérias/genética , Óperon/genética , Percepção de Quorum/genética
4.
IEEE Trans Nanobioscience ; 18(2): 103-116, 2019 04.
Artigo em Inglês | MEDLINE | ID: mdl-30530333

RESUMO

In this paper, we propose using mobile nanosensors (MNSs) for early stage anomaly detection. For concreteness, we focus on the detection of cancer cells located in a particular region of a blood vessel. These cancer cells produce and emit special molecules, so-called biomarkers, which are symptomatic for the presence of anomaly, into the cardiovascular system. Detection of cancer biomarkers with conventional blood tests is difficult in the early stages of a cancer due to the very low concentration of the biomarkers in the samples taken. However, close to the cancer cells, the concentration of the cancer biomarkers is high. Hence, detection is possible if a sensor with the ability to detect these biomarkers is placed in the vicinity of the cancer cells. Therefore, in this paper, we study the use of MNSs that are injected at a suitable injection site and can move through the blood vessels of the cardiovascular system, which potentially contain cancer cells. These MNSs can be activated by the biomarkers close to the cancer cells, where the biomarker concentration is sufficiently high. Eventually, the MNSs are collected by a fusion center (FC), where their activation levels are read and exploited to declare the presence of anomaly. We analytically derive the biomarker concentration in a network of interconnected blood vessels as well as the probability mass function of the MNSs' activation levels and validate the obtained results via particle-based simulations. Then, we derive the optimal decision rule for the FC regarding the presence of anomaly assuming that the entire network is known at the FC. Finally, for the FC, we propose a simple sum detector that does not require knowledge of the network topology. Our simulations reveal that while the optimal detector achieves a higher performance than the sum detector, both proposed detectors significantly outperform a benchmark scheme that uses fixed nanosensors at the FC.


Assuntos
Biomarcadores Tumorais/sangue , Técnicas Biossensoriais , Neoplasias/diagnóstico , Vasos Sanguíneos , Humanos , Injeções , Modelos Biológicos , Neoplasias/sangue
5.
IEEE Trans Nanobioscience ; 16(8): 828-842, 2017 12.
Artigo em Inglês | MEDLINE | ID: mdl-29364127

RESUMO

In this paper, we consider abnormality detection via diffusive molecular communications (MCs) for a network consisting of several sensors and a fusion center (FC). If a sensor detects an abnormality, it injects a number of molecules into the medium which is proportional to its sensing output. Two transmission schemes for releasing molecules into the medium are considered. In the first scheme, each sensor releases a different type of molecule (DTM), whereas in the second scheme, all sensors release the same type of molecule (STM). The molecules released by the sensors propagate through the MC channel and some may reach the FC where the final decision regarding whether or not an abnormality has occurred is made. We derive the optimal decision rules for both DTM and STM. However, the optimal detectors entail high computational complexity as log-likelihood ratios (LLRs) have to be computed. To overcome this issue, we show that the optimal decision rule for STM can be transformed into an equivalent low-complexity decision rule. Since a similar transformation is not possible for DTM, we propose simple low-complexity sub-optimal detectors based on different approximations of the LLR. The proposed low-complexity detectors are more suitable for practical MC systems than the original complex optimal decision rule, particularly when the FC is a nano-machine with limited computational capabilities. Furthermore, we analyze the performance of the proposed detectors in terms of their false alarm and missed detection probabilities. Simulation results verify our analytical derivations and reveal interesting insights regarding the tradeoff between complexity and performance of the proposed detectors and the considered DTM and STM schemes.


Assuntos
Computadores Moleculares , Processamento de Sinais Assistido por Computador , Simulação por Computador , Difusão , Nanotecnologia , Razão Sinal-Ruído
6.
IEEE Trans Nanobioscience ; 15(5): 418-432, 2016 07.
Artigo em Inglês | MEDLINE | ID: mdl-27116747

RESUMO

In diffusion-based molecular communication (DMC), a transmitter nanomachine is responsible for signal modulation. Thereby, the transmitter has to be able to control the release of the signaling molecules employed for representing the transmitted information. In nature, an important class of control mechanisms for releasing molecules from cells utilizes ion channels which are pore-forming proteins across the cell membrane. The opening and closing of the ion channels is controlled by a gating parameter. In this paper, an ion channel based modulator for DMC is proposed which controls the rate of molecule release from the transmitter by modulating a gating parameter signal. Exploiting the capabilities of the proposed modulator, an on-off keying modulation technique is introduced and the corresponding average modulated signal, i.e., the average release rate of the molecules from the transmitter, is analyzed. However, since the modulated signal is random in nature, it may deviate from its average. Therefore, the concept of modulator noise is introduced and the statistics of the modulated signal are investigated. Finally, by assuming a simple transparent receiver, the performance of the proposed on-off keying modulation format is studied. The derived analytical expressions for the average modulated signal are confirmed with particle based simulations. Our numerical results reveal that performance estimates of DMC systems obtained based on the assumption of instantaneous molecule release at the transmitter may substantially deviate from the performance achieved with practical modulators.


Assuntos
Computadores Moleculares , Canais Iônicos/química , Canais Iônicos/metabolismo , Modelos Biológicos , Difusão , Processamento de Sinais Assistido por Computador
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