This work develops a learning-based framework for energy-efficient power control in multi-carrier wireless networks. The problem is formulated as the maximization of the network global energy efficiency, defined as the ratio between the network sum-rate and the total consumed power, and is tackled by a novel approach which merges tools from learning, non-cooperative game theory, and fractional programming theory. The proposed algorithm is provably convergent, enjoys near-optimal performance, while requiring a much lower complexity than previous alternatives.
Titolo: | A learning-based approach to energy efficiency maximization in wireless networks |
Autori interni: | |
Data di pubblicazione: | 2018 |
Handle: | http://hdl.handle.net/20.500.11769/358420 |
ISBN: | 978-1-5386-1734-2 |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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