In recent years there has been a rapid increase in the number of wireless devices for both commercial and defense applications. Such unprecedented demand has increased device cost and complexity and also added a strain on the spectrum utilization of wireless communication systems. This thesis addresses these issues, from an antenna system perspective, by developing new techniques to dynamically optimize adaptive beamforming arrays for improved anti-jamming and reliability. Available frequency spectrum is a scarce resource, and therefor e increased interference will occur as the wireless spectrum saturates. To mitig ate unintentional interference, or intentional interference from a jamming source, antenna arrays are used to focus electromagnetic energy on a signal of interest while simultaneously minimizing radio frequency energy in directions of interfering signals. The reliability of such arrays, especially in commercial satellite and defense applications, can be addressed by hardware redundancy, but at the expense of increased volume, mass as well as component and design cost. This thesis proposes the development of new models and optimization algorithms to dynamically adapt beamforming arrays to mitigate interference and increase hardware reliability. The contributions of this research are as follows. First, analytical models are developed and experimental results show that small antenna arrays can thwart interference using dynamically applied stochastic algorithms. This type of insitu optimization, with an algorithm dynamically optimizing a beamformer to thwart interference sources with unknown positions, inside of an anechoic chamber has not been done before to our knowledge. Second, it is shown that these algorithms can recover from hardware failures and localized faults in the array. Experiments were performed with a proof-of-concept four-antenna array. This is the first hardware demonstration showing an antenna array with live hardware fault recovery that is adapted by stochastic algorithms in an anechoic chamber. We also compare multiple stochastic algorithms in performing both anti-jamming and hardware fault recovery. Third, we show that stochastic algorithms can be used to continuously track and mitigate interfering signals that continuously move in an additive white Gaussian noise wireless channel.
| Identifer | oai:union.ndltd.org:cmu.edu/oai:repository.cmu.edu:dissertations-1331 |
| Date | 16 May 2014 |
| Creators | Becker, Jonathan |
| Publisher | Research Showcase @ CMU |
| Source Sets | Carnegie Mellon University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Dissertations |
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