Energy-Efficient Traffic Rate Adaptation for Wireless Streaming Media Transmission

Energy-efficient streaming of real-time scalable video over wireless fading channels with imperfect channel state information is considered in this paper. A traffic rate adaptation (TRA) scheme is presented to minimize the transmission energy consumption while satisfying the quality of experience (QoE) requirement by dynamically selecting the delivered encoding layers of streaming media depending on the channel condition. A partially observable Markov decision process model is introduced to formulate the energy-efficient QoE-guaranteed TRA problem. Based on the Lagrange method of multipliers, an online policy iteration algorithm is proposed to solve the constrained optimization problem. This algorithm performs policy evaluation and improvement without intensive computations and prior knowledge of channel statistics. The adaptability to unknown environments and high computation efficiency make the proposed scheme attractive for implementation in real-life mobile systems. Simulation results demonstrate the effectiveness of the proposed method.