6 research outputs found
Heuristic Barycenter Modeling of Fully Absorbing Receivers in Diffusive Molecular Communication Channels
In a recent paper it has been shown that to model a diffusive molecular
communication (MC) channel with multiple fully absorbing (FA) receivers, these
can be interpreted as sources of negative particles from the other receivers'
perspective. The barycenter point is introduced as the best position where to
place the negative sources. The barycenter is obtained from the spatial mean of
the molecules impinging on the surface of each FA receiver. This paper derives
an expression that captures the position of the barycenter in a diffusive MC
channel with multiple FA receivers. In this work, an analytical model inspired
by Newton's law of gravitation is found to describe the barycenter, and the
result is compared with particle-based simulation (PBS) data. Since the
barycenter depends on the distance between the transmitter and receiver and the
observation time, the condition that the barycenter can be assumed to be at the
center of the receiver is discussed. This assumption simplifies further
modeling of any diffusive MC system containing multiple FA receivers. The
resulting position of the barycenter is used in channel models to calculate the
cumulative number of absorbed molecules and it has been verified with PBS data
in a variety of scenarios.Comment: 30 pages, 10 figure
Channel Modeling for Diffusive Molecular Communication - A Tutorial Review
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
time-varying 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
experimentally-driven channel models. Finally, we provide a detailed discussion
of potential challenges, open research problems, and future directions in
channel modeling for diffusive MC systems.Comment: 40 pages; 23 figures, 2 tables; this paper is submitted to the
Proceedings of IEE
Channel modeling for diffusive molecular communication - a tutorial review
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 experiment-driven channel models. Finally, we provide a detailed discussion of potential challenges, open research problems, and future directions in channel modeling for diffusive MC systems