dissertation · Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft) · 2011
Frequency occupancy prediction and its application in a novel channel access method
Keyvan, A.
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Abstract
This thesis was written with the motivation of further maintaining the rapid growth in wireless technologies by reducing the burden from the spectrum specifically in the industrial environments. Wireless sensor networks are used extensively in industrial environments which they commonly transmit packets periodically. Using the cognitive radio paradigm, spectrum can be sensed and later the periodic pattern in a specific channel can be determined. The periodic pattern is used in order to predict the future status of the channel. As part of this task, two frequency occupancy predictors have been implemented and evaluated. Moreover, using the channel occupancy prediction, a novel channel access method has been developed and was named CSMA/PCA. Compared to the conventional CSMA/CA, packet error rate has been found to be significantly lower and throughput has found to be much higher using CSMA/PCA.
Cite this paper
Keyvan, A. (2011). Frequency occupancy prediction and its application in a novel channel access method. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft).
Keyvan, A. “Frequency occupancy prediction and its application in a novel channel access method.” Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft), 2011.
Keyvan, A. 2011. “Frequency occupancy prediction and its application in a novel channel access method.” Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft).
Keyvan, A. (2011) ‘Frequency occupancy prediction and its application in a novel channel access method’, Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft).
@phdthesis{keyvan2011frequency,
title = {{Frequency occupancy prediction and its application in a novel channel access method}},
author = {Keyvan, A.},
school = {Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft)},
year = {2011}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.