Multicommodity Network Flow for Indoor Progation Loss Prediction

Channel models are an essential tool for some communication systems. Simultaneous Wireless Information and Power Transfer, SWIPT is a widely studied topic in areas like wireless sensor networks and internet of things applications, the utilization of a prediction model in this situation can bring many benefits. Therefore, this paper proposes a propagation loss model based on Multicommodity Network Flow (MCNF) for industrial indoor environments, focused on Simultaneous Wireless Information and Power Transfer Applications. We analyze the frequencies of 2.4GHz. The proposed model showed higher adherence to the measured values than the other indoor propagation models, mainly for short and higher transmission powers.