Wide-band spectrum sensing is an approach for finding spectrum holes within a wideband
signal with less complexity/delay than the conventional approaches. In this thesis,
we propose four different algorithms for detecting the holes in a wide-band spectrum
and finding the sparsity level of compressive signals. The first algorithm estimates the
spectrum in an efficient manner and uses this estimation to find the holes. The second
algorithm detects the spectrum holes by reconstructing channel energies instead of reconstructing
the spectrum itself. In this method, the signal is fed into a number of filters.
The energies of the filter outputs are used as the compressed measurement to reconstruct
the signal energy. The third algorithm employs two information theoretic algorithms
to find the sparsity level of a compressive signal and the last algorithm employs belief
propagation for detecting the sparsity level.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:OTU.1807/29609 |
| Date | 25 August 2011 |
| Creators | Sadiq, Sadiq Jafar |
| Contributors | Valaee, Shahrokh |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
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