Modelo de perdas de propagação para aplicações de internet das coisas e transmissão simultânea de informação e energia para ambientes internos.

Abstract

Since the advent of the Internet of Things in the 1990s, there has been a growing interest in creating industrial applications for things like equipment integration, inventory tracking, and system interoperability. The demand for energy-efficient systems that can harness the power already existing in their surroundings is growing across a wide variety of industries. Transmission of both data and power at the same time, or Simultaneous Wireless Information and Power Transfer (SWIPT), has gained prominence in the field of energy collection, particularly in industrial applications geared toward data collection in an industrial setting. Since radiofrequency (RF) signal energy must be harvested by SWIPT systems for both power regeneration and energy collection and data demodulation and decoding, signal-level prediction models are essential for SWIPT analysis and reliability guarantees in challenging RF environments. Communication systems may be harmed in such an environment due to the presence of obstacles like equipment, raw materials, and finished goods; the movement and transport of these items; and the occurrence of propagation phenomena like reflections, diffractions, and refractions. In this setting, we developed a propagation loss model based on commodity network flow modeling; we call it Multicommodity Network Flow (MCNF) or Multicommodity Flow (MCF). MCF is an optimization tool that can provide a good response to optimization problems and satisfactory computational performance by breaking down complex systems into their component parts. for compared to other models typically used in such situations, the proposed MCF model showed satisfactory performance for predicting propagation losses in internal environments. We analyzed 915 MHz, 2.4 GHz, 3 GHz, and 3.5 GHz signals at transmission powers of 0, 1, 10, 20, and 30 dBm and measured the received signal strength indicator (RSSI) at distances ranging from 1 to 5 meters at powers of -30, -20, -10, -1, 0 to 1, 10, 20, and 30 dBm. Measures were taken to simulate various situations that may arise in internal industrial environments, such as relative movement between the transmitter and receiver and interruption of the direct line of sight. Models used in internal environments, such as COST 231 Motley-Keenan and the ITU-R P.1238-1, were compared with the proposed MCF model using various methods of error analysis.