Connectivity Model for Molecular Communication-Based Nanomachines Network in Normal and Sub-diffusive Regimes
Nanomachines network is an interconnection of nanomachines (NMs) capable of communicating with each other. NMs networks are expected to provide an intelligent alternative to contemporary wireless sensor networks due to their biocompatibility, pervasiveness, and energy efficiency. However, connectivity issues of NMs networks are yet to be explored fully. This paper presents a probabilistic connectivity model for molecular communication-based NMs network which involves transmission of a message via diffusion of messenger molecules. This model has been developed through signal to interference and noise ratio (SINR) analysis considering effects of co-channel interference (CCI) and intersymbol interference (ISI). It is found that ISI is the dominating factor in degrading the network connectivity than CCI. Also, results have shown that selection of symbol time is crucial and should depend on internode distance (or transmission range), for higher network connectivity. Physical obstructions in transmission media lead to anomalous diffusive behavior. This paper has investigated effects of sub-diffusion on the connectivity of NMs network to reveal that presence of physical obstructions can be a favorable condition in MC-based NMs networks if symbol time is adjusted accordingly.
KeywordsNanomachines network Molecular communication Network connectivity Anomalous diffusion
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