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. © 2012 IEEE.
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CITATION STYLE
Gulati, N., Gonzalez, D., & Dandekar, K. R. (2012). Learning algorithm for reconfigurable antenna state selection. In RWW 2012 - Proceedings: IEEE Radio and Wireless Symposium, RWS 2012 (pp. 31–34). https://doi.org/10.1109/RWS.2012.6175375
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