Conference proceeding
Learning algorithm for reconfigurable antenna state selection
2012 IEEE Radio and Wireless Symposium
Jan 2012
Abstract
In this paper, we propose an online learning algorithm for selecting the state of a reconfigurable antenna. We formulate the antenna state selection as a multiarmed bandit problem and present a selection technique, implemented for a 2 × 2 MIMO OFDM system employing highly directional metamaterial Reconfigurable Leaky Wave Antennas. We quantify the performance of our selection technique using a software defined radio testbed and present results for a wireless network in a typical indoor environment.
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3 Record Views
6 citations in Scopus
Details
- Title
- Learning algorithm for reconfigurable antenna state selection
- Creators
- N Gulati - Dept. of Electr. & Comput. Eng., Drexel Univ., Philadelphia, PA, USAD Gonzalez - Dept. of Electr. & Comput. Eng., Drexel Univ., Philadelphia, PA, USAK. R Dandekar - Dept. of Electr. & Comput. Eng., Drexel Univ., Philadelphia, PA, USA
- Publication Details
- 2012 IEEE Radio and Wireless Symposium
- Publisher
- IEEE
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Scopus ID
- 2-s2.0-84860685267
- Other Identifier
- 991014877798904721