Conference proceeding
Online learning for spectrum sensing and reconfigurable antenna control
2014 9th International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM), pp 508-513
Jun 2014
Abstract
Efficient dynamic spectrum access (DSA) policies rely on accurate spectrum sensing information to exploit spectrum white space optimally. Obtaining accurate channel state information (CSI) from local spectrum measurements is made difficult by wireless signal fading and the presence of thermal noise which distorts measured signals and leads to uncertainty regarding the occupancy of spectrum resources. Electrically reconfigurable antenna systems (ERAS) offer the system designer an additional degree of freedom to exploit pattern and polarization diversity to improve the accuracy of local spectrum sensing decisions. We propose a learning technique to exploit pattern and polarization diversity offered by ERAS to improve spectrum sensing accuracy. While the proposed approach is designed to work within the unique design constraints of reconfigurable antennas, the approach is not antenna specific and will work with a wide variety of reconfigurable antenna designs. Validation of system performance is provided from measurements taken using the wireless open access research platform (WARP) software defined radio (SDR) platform in an indoor office environment.
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Details
- Title
- Online learning for spectrum sensing and reconfigurable antenna control
- Creators
- Kevin WanugaNikhil GulatiHarri SaarnisaariKapil R Dandekar
- Publication Details
- 2014 9th International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM), pp 508-513
- Publisher
- ICST
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000343594900085
- Scopus ID
- 2-s2.0-84905043755
- Other Identifier
- 991014878648804721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Hardware & Architecture
- Engineering, Electrical & Electronic
- Telecommunications