Asilomar Conference on Signals, Systems and Computers,
Pacific Grove, California USA, Oct. 28-31, 2018
Q-Learning Algorithm for VoLTE Closed Loop Power Control in Indoor Small Cells
Faris B. Mismar and
Brian L. Evans
Department of Electrical and Computer Engineering,
Wireless Networking and Communications Group,
The University of Texas at Austin,
Austin, TX 78712 USA
Final Paper (Archive) -
Final Paper (Local) -
Poster (PowerPoint) -
Poster (PDF) -
We propose a reinforcement learning (RL) based closed loop power control
algorithm for the downlink of the voice over LTE (VoLTE) radio bearer
for an indoor environment served by small cells.
The main contributions of our paper are to
In simulation, the proposed RL-based power control algorithm significantly
improves both voice retainability and mean opinion score compared to current
The improvement is due to maintaining an effective downlink signal to
interference plus noise ratio against adverse network operational issues
- use RL to solve performance tuning problems in an indoor cellular
network for voice bearers and
- show that our derived lower bound loss in effective SINR is sufficient
for VoLTE power control purposes in practical cellular networks.
COPYRIGHT NOTICE: All the documents on this server
have been submitted by their authors to scholarly journals or conferences
as indicated, for the purpose of non-commercial dissemination of
The manuscripts are put on-line to facilitate this purpose.
These manuscripts are copyrighted by the authors or the journals in which
they were published.
You may copy a manuscript for scholarly, non-commercial purposes, such
as research or instruction, provided that you agree to respect these
Last Updated 11/07/18.