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Conference papers
Online Energy-Efficient Power Control in Wireless Networks by Deep Neural Networks
Abstract : The work describes how deep learning by artificial neural networks (ANNs) enables online power allocation for energy efficiency maximization in wireless interference networks. A deep ANN architecture is proposed and trained to take as input the network communication channels and to output suitable power allocations. It is shown that this approach requires a much lower computational complexity compared to traditional optimization-oriented approaches, dispensing with the need of solving the optimization problem anew in each channel coherence time. Despite the lower complexity, numerical results show that a properly trained ANN achieves similar performance as more traditional optimization-oriented methods.
Cited literature [22 references]
https://hal-centralesupelec.archives-ouvertes.fr/hal-01962086
Contributor : Delphine Le Piolet <>
Submitted on : Thursday, December 20, 2018 - 1:33:18 PM
Last modification on : Thursday, January 7, 2021 - 2:30:03 PM
Long-term archiving on: : Friday, March 22, 2019 - 10:42:34 AM
Contributor : Delphine Le Piolet <>
Submitted on : Thursday, December 20, 2018 - 1:33:18 PM
Last modification on : Thursday, January 7, 2021 - 2:30:03 PM
Long-term archiving on: : Friday, March 22, 2019 - 10:42:34 AM
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PID5385981.pdf
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