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Statistical analysis and predictive modeling of industrial wireless coexisting environments

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3 Author(s)
Ganesh Man Shrestha ; Institute Industrial IT OWL University of Applied Sciences, 32657 Lemgo, Germany ; Kaleem Ahmad ; Uwe Meier

Typically, cognitive radio systems either sense the channel just before transmission or perform this task periodically in order to remain aware about the operational environment. However, a channel sensed as `free' can become busy during the transmission of the cognitive system resulting in harmful collisions and unnecessary interruptions in the secondary user data transmission. As a solution, predictive based approaches has been proposed and has shown promising results in simulated environments. However, modeling real-time, dynamic, coexisting environments demand investigation with real-time demonstrators. This paper investigates industrial coexisting environments and illustrates the prediction model selection and its parameter estimation criteria. Based on the investigation a real-time testbed is implemented using a CC2500 TRX and MSP430 μC based platform.

Published in:

Factory Communication Systems (WFCS), 2012 9th IEEE International Workshop on

Date of Conference:

21-24 May 2012