Joan Meseguer Llopis
ABSTRACT
Reducing power consumption in LTE networks has become an important issue for mobile network operators. The 3GPP organization has included such operation as one of SON (Self-Organizing Networks) functions [1][2]. Using the approach presented in this paper the decision about turning Radio Access Network (RAN) nodes off and on, according to the network load (which is typically low at night), is taken into account. The process is controlled using a combination of Fuzzy Logic and Q-Learning techniques (FQL). The effectiveness of the proposed approach has been evaluated using the LTE-Sim simulator with some extensions. The simulations are very close to real network implementation: we used the RAN node parameters that are defined by 3GPP and simulations take into account the network behaviour in the micro time scale.
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Index Terms
- Reinforcement learning based energy efficient LTE RAN
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