LAUSR

In vivo wireless nanosensor networks (iWNSNs) are paving the way toward transformative healthcare solutions. These networks are expected to enable a plethora of applications, including drug-delivery, bio-sensing, and health monitoring. With the development of miniature plasmonic signal sources, antennas, and detectors, wireless communications among intrabody nanodevices will expectedly be enabled in the terahertz (THz) frequency band (0.1–10 THz). Several propagation models were recently developed to analyze and assess the feasibility of intra-body electromagnetic (EM) nanoscale communication. The emphasis of these works has mainly been on understanding the propagation of EM signals through biological media, with limited focus on the intra-body noise sources and their impact on the system performance. In this paper, a stochastic noise model for iWNSNs is presented in which the individual noise sources that impact intra-body systems operating in the THz frequency band are analyzed. The overall noise contributions are composed of three distinctive constituents, namely, Johnson–Nyquist noise, black-body noise, and Doppler-shift-induced noise. The probability distribution of each noise component is derived, and a comprehensive analytical approach is developed to obtain the total noise power-spectral density. The model is further validated via 2-D particle simulations as the active transport motion of particles is conveyed in the presented framework. The developed models serve as the starting point for a rigorous end-to-end channel model that enables the proper estimation of data rate, channel capacity, and other key parameters, which are all factors of the noise environment.