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Article

Beamforming and Power Control in Sensor Arrays Using Reinforcement Learning

1
UFERSA—Federal Rural University of the Semi-Árido, Pau dos Ferros 59900-000, Brazil
2
DCA-CT-UFRN, Federal University of Rio Grande do Norte, Natal 59072-970, Brazil
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editor: Vittorio M.N. Passaro
Sensors 2015, 15(3), 6668-6687; https://doi.org/10.3390/s150306668
Received: 31 October 2014 / Revised: 14 February 2015 / Accepted: 4 March 2015 / Published: 19 March 2015
(This article belongs to the Section Physical Sensors)
The use of beamforming and power control, combined or separately, has advantages and disadvantages, depending on the application. The combined use of beamforming and power control has been shown to be highly effective in applications involving the suppression of interference signals from different sources. However, it is necessary to identify efficient methodologies for the combined operation of these two techniques. The most appropriate technique may be obtained by means of the implementation of an intelligent agent capable of making the best selection between beamforming and power control. The present paper proposes an algorithm using reinforcement learning (RL) to determine the optimal combination of beamforming and power control in sensor arrays. The RL algorithm used was Q-learning, employing an ε-greedy policy, and training was performed using the offline method. The simulations showed that RL was effective for implementation of a switching policy involving the different techniques, taking advantage of the positive characteristics of each technique in terms of signal reception. View Full-Text
Keywords: beamforming; power control; sensor arrays; Q-learning beamforming; power control; sensor arrays; Q-learning
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MDPI and ACS Style

Almeida, N.C.; Fernandes, M.A.C.; Neto, A.D.D. Beamforming and Power Control in Sensor Arrays Using Reinforcement Learning. Sensors 2015, 15, 6668-6687. https://doi.org/10.3390/s150306668

AMA Style

Almeida NC, Fernandes MAC, Neto ADD. Beamforming and Power Control in Sensor Arrays Using Reinforcement Learning. Sensors. 2015; 15(3):6668-6687. https://doi.org/10.3390/s150306668

Chicago/Turabian Style

Almeida, Náthalee C., Marcelo A.C. Fernandes, and Adrião D.D. Neto. 2015. "Beamforming and Power Control in Sensor Arrays Using Reinforcement Learning" Sensors 15, no. 3: 6668-6687. https://doi.org/10.3390/s150306668

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