Title :
Reinforcement learning for power management in wireless multimedia communications
Author :
Mastronarde, Nicholas ; Van der Schaar, Mihaela
Author_Institution :
University of California, Los Angeles, Department of Electrical Engineering, USA
Abstract :
We consider the problem of energy-efficient point-to-point transmission of delay-sensitive data (e.g. multimedia data) over a fading channel. We propose a rigorous and unified framework for simultaneously utilizing both physical-layer and system-level techniques to minimize energy consumption, under delay constraints, in the presence of stochastic and unknown traffic and channel conditions. We formulate the problem as a Markov decision process and solve it online using reinforcement learning. The advantages of the proposed online method are that (i) it does not require a priori knowledge of the traffic arrival and channel statistics to determine the jointly optimal physical-layer and system-level power management strategies; (ii) it exploits partial information about the system so that less information needs to be learned than when using conventional reinforcement learning algorithms; and (iii) it obviates the need for action exploration, which severely limits the adaptation speed and run-time performance of conventional reinforcement learning algorithms.
Keywords :
Energy-efficient wireless multimedia communication; Markov decision process; adaptive modulation and coding; dynamic power management; power-control; reinforcement learning;
Conference_Titel :
Multimedia and Expo (ICME), 2011 IEEE International Conference on
Conference_Location :
Barcelona, Spain
Print_ISBN :
978-1-61284-348-3
Electronic_ISBN :
1945-7871
DOI :
10.1109/ICME.2011.6012018