1 research outputs found
Compound Poisson Noise Sources in Diffusion-based Molecular Communication
Diffusion-based molecular communication (DMC) is one of the most promising
approaches for realizing nano-scale communications for healthcare applications.
The DMC systems in in-vivo environments may encounter biological entities that
release molecules identical to the molecules used for signaling as part of
their functionality. Such entities in the environment act as external noise
sources from the DMC system's perspective. In this paper, the release of
molecules by biological external noise sources is particularly modeled as a
compound Poisson process. The impact of compound Poisson noise sources (CPNSs)
on the performance of a point-to-point DMC system is investigated. To this end,
the noise from the CPNS observed at the receiver is characterized. Considering
a simple on-off keying (OOK) modulation and formulating symbol-by-symbol
maximum likelihood (ML) detector, the performance of DMC system in the presence
of the CPNS is analyzed. For special case of CPNS in high-rate regime, the
noise received from the CPNS is approximated as a Poisson process whose rate is
normally distributed. In this case, it is proved that a simple single-threshold
detector (STD) is an optimal ML detector. Our results reveal that in general,
adopting the conventional simple homogeneous Poisson noise model may lead to
overly optimistic performance predictions, if a CPNS is present