by N. Gulati and K. R. Dandekar
Reference:
N. Gulati, K. R. Dandekar, “Learning State Selection for Reconfigurable Antennas: A Multi-Armed Bandit Approach”, IEEE Transactions on Antennas and Propagation, vol. 62, no. 3, pp. 1027-1038, 2014.
Bibtex Entry:
@ARTICLE{6574205,
author={N. Gulati and K. R. Dandekar},
journal={IEEE Transactions on Antennas and Propagation},
title={Learning State Selection for Reconfigurable Antennas: A Multi-Armed Bandit Approach},
year={2014},
volume={62},
number={3},
pages={1027-1038},
keywords={antenna radiation patterns;MIMO communication;OFDM modulation;radio links;wireless channels;learning state selection;reconfigurable antennas;multiarmed bandit approach;radiation patterns;wireless link;optimal antenna state;channel state information;reconfigurable antenna state selection;multiarmed bandit problem;arbitrary link quality metrics;online learning;multiarmed bandit framework;sequential decision policy;wireless channel statistics;adaptive state selection;MIMO OFDM system;long term link performance;channel training frequency;Receiving antennas;Training;Transmitting antennas;MIMO;OFDM;Beamsteering;cognitive radio;MIMO;multi-armed bandit;OFDM;online learning;reconfigurable antennas},
doi={10.1109/TAP.2013.2276414},
ISSN={0018-926X},
month={March},}