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Synchronisation and Wavelet Compression for Background Interference Classification in Wireless Environments
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- Author / Creator
- Vlachaki, Aikaterini
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Dense wireless deployment environments are increasingly facing Radio Frequency (RF) spectrum congestion and increased levels of interference. Addressing the interference will require a distributed decision-making application on wireless nodes, that characterize the state of the channel with respect to the presence (or not) of interference, allowing the nodes to adopt mitigation strategies. In this thesis, through a study of empirical data, we examine if each node was to separately characterize the state of the channel and then form consensus with other nodes, whether this consensus correctly reflects the similarity of the per-node sensed background interference. Towards this goal we develop a distributed synchronization scheme that reduces the inaccuracy inherent in distributed data sampling in local node clocks. As an alternative to consensus of per-node characterization we also examine the effectiveness of the Discrete Wavelet Transform (DWT) to communicate to other nodes the state of the channel, as sampled by a node, in a compressed, denoised form. Our early results show that wavelet compression of the sampled time series may produce significant data volume savings, to allow the full time series to be communicated e.g. to a cloud infrastructure where large scale planning of spectrum usage can take place.
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- Subjects / Keywords
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- Graduation date
- Fall 2017
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- Type of Item
- Thesis
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- Degree
- Master of Science
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- License
- This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.