'It is not a lack of spectrum. It is an issue of efficient use of the available spectrum"--conclusions of the FCC Spectrum Policy Task Force.
There is growing interest towards providing broadband communication with high bit rates and throughput, especially in the ISM band, as it was an ignition of innovation triggered by the FCC to provide, to some extent, a regulation-free band that anyone can use. But with such freedom comes the risk of interference and more responsibility to avoid causing it. Therefore, the need for accurate interference detection and identification, along with good blind detection capabilities are inevitable. Since cognitive radio is being adopted widely as more researchers consider it the ultimate solution for efficient spectrum sharing [1], it is reasonable to study the cognitive radio in the ISM band [2].
Many indications show that the ISM band will have less regulation in the future, and some even predict that the ISM may be completely regulation free [3]. In the dawn of cognitive radio, more knowledge about possible interfering signals should play a major role in determining optimal transmitter configurations. Since signal identification and interference will be the core concerns [4], [5], we will describe a novel approach for a cognitive radio spectrum sensing engine, which will be essential to design more efficient ISM band transceivers.
In this thesis we propose a novel spectrum awareness engine to be integrated in the cognitive radios. Furthermore, the proposed engine is specialized for the ISM band, assuming that it can be one of the most challenging bands due to its free-to-use approach. It is shown that characterization of the interfering signals will help with overcoming their effects. This knowledge is invaluable to help choose the best configuration for the transceivers and will help to support the efforts of the coexistence attempts between wireless devices in such bands.
| Identifer | oai:union.ndltd.org:USF/oai:scholarcommons.usf.edu:etd-1100 |
| Date | 11 May 2009 |
| Creators | Zakaria, Omar |
| Publisher | Scholar Commons |
| Source Sets | University of South Flordia |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate Theses and Dissertations |
| Rights | default |
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