Compound Poisson Noise Sources in Diffusion-based Molecular Communication
share
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 organs that release molecules identical to the molecules used for signaling as part of their functionality. Such organs in the environment act as external noise source from the DMC system's perspective. Conventional simple receiver noise models are not able to characterize such external noise sources. In this paper, the release of molecules by biological noise sources is 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 by exploiting the rare-event property of Poisson processes. Considering a simple on-off keying modulation and formulating 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 normal distributed. It is proved that the distribution of noise from the CPNS in high-rate regime is log-concave and a simple single-threshold detector (STD) is optimal ML detector. indicate that the simple STD may not optimal ML detector, in general case of CPNS. Moreover, 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.
READ FULL TEXT