Wideband and Multiband Temporal Sensing for Opportunistic Spectrum Access
| dc.contributor.advisor | Mark, Brian L | |
| dc.contributor.author | Bruno, Joseph M | |
| dc.creator | Bruno, Joseph M | |
| dc.date | 2017-04-28 | |
| dc.date.accessioned | 2018-05-25T15:27:56Z | |
| dc.date.available | 2018-05-25T15:27:56Z | |
| dc.description.abstract | Opportunistic spectrum access is a proposed solution to the problem of increasing scarcity of radio resources. In certain bands, spectrum is utilized extremely inefficiently by the licensed, or primary, users. Opportunistic spectrum access would allow a secondary user to utilize spectrum when the primary user is idle while not causing harmful interference when the primary user is active. Spectrum sensing techniques determine portions of the spectrum that are occupied by primary user signals at a given time and location. Temporal sensing of a known narrowband channel involves modeling the temporal dynamics of the primary user signal and performing estimation and prediction of the primary user state. Wideband sensing involves determining which parts of a given wide spectrum are occupied or unoccupied at a given point in time. Both temporal and wideband sensing have been studied extensively in the literature. There has been relatively little work on temporal sensing over a wide spectrum band with either well-defined or unknown channels. In this dissertation, novel approaches to wideband and multiband temporal sensing are developed. A class of hidden Markov models is proposed to jointly model time dynamics of the primary system and channel impairments between the primary user and the secondary user over a wide spectrum band. Methods to segment a wide spectrum band into individual channels and to optimize parameter estimation over the channels are proposed. Simulation results are presented to evaluate the effectiveness of the proposed wideband and multiband temporal sensing schemes. Some comparisons to performance bounds are provided. | |
| dc.identifier | doi:10.13021/G89Q45 | |
| dc.identifier.uri | https://hdl.handle.net/1920/10970 | |
| dc.language.iso | en | |
| dc.subject | Spectrum sensing | |
| dc.subject | Hidden Markov Model | |
| dc.subject | Cognitive radio | |
| dc.subject | Dynamic spectrum access | |
| dc.title | Wideband and Multiband Temporal Sensing for Opportunistic Spectrum Access | |
| dc.type | Dissertation | |
| thesis.degree.discipline | Electrical Engineering | |
| thesis.degree.grantor | George Mason University | |
| thesis.degree.level | Doctoral | |
| thesis.degree.name | Doctor of Philosophy in Electrical Engineering |