Detection of Short-Term Radio Signal Disturbances in Industrial Wireless Sensor Networks

Abstract

The performance of wireless sensor networks (WSNs) in industrial environments may be degraded due to harsh radio signal propagation conditions. Short-term signal disturbances are of major concern due to incoming and outgoing trucks, moving around forklifts and workers, as well as large concrete and metal surfaces. We studied the effects of some environmental disturbances on the quality of the transmitted signals. We consider directly measurable transmission quality parameters Received Signal Strength Indicator (RSSI) and Bit-Error-Rate (BER) as well as statistical characteristics of the received signal magnitude. We used software defined radio (SDR) as the receiver to capture the transmitted signals and analyzed the statistical properties of the captured signals with Matlab/Simulink tools. Our studies led us to a method which aims to identify the short-term radio disturbances by calculating the probability density function (PDF) of the received signal magnitude and analyzing the parameters of the PDFs. The results show that tracking the changes of the PDF of the received signal magnitudes contributes to recognize and characterize the temporal changes in the radio link environment and in that way to choose the right actions in order to overcome the communication problems.