Energy consumption optimization for green Device-to-Device multimedia communications

Abstract

Recently, Device-to-Device (D2D) multimedia communications have been envisioned as emerging technology for improving capacity and reducing power consumption in wireless networks. In D2D multimedia communications, multimedia applications consume considerable amount of energy and bandwidth resources to satisfy increasing mobile user demands. To overcome this problem, we have proposed a novel energy consumption optimization method (ECO) for green D2D multimedia communications by using Adaptive Genetic Algorithm. In particular, we first encode the videos by using layered multiple description coding with forward error correction (LMDC-FEC) to protect against error and delays as well as more adaptive to unstable bandwidth in wireless channels. To minimize the average energy consumption by packetizing and transmitting, we then formulate the energy consumption optimization problem and solve it to find out the optimal encoding rate matrix allocated to each video under limited bandwidth resource and high quality constraints. The experimental results demonstrated that our proposed ECO method can achieve remarkable improvements in terms of energy saving, i.e., save up to 64% average energy consumption compared to the other methods, while ensuring high received video quality and satisfying given limited bandwidth.