Energy-efficiency Random Network Coding Scheduling Based on Kalman prediction under Mobile Network

Random network coding (RNC) is an efficient coding scheme to improve the performance of wireless networks. However, when the users move randomly in the network, the transmitting distance between the transceivers changed randomly, causing the time-varying channel conditions. To fit this situation, in this paper, we considered the heterogenous wireless channels of the users caused by user movement and analyzed the energy consumption of overall network. Then, we introduce the Kalman filter to predict the locations of the users and proposed a new power control metric that both considered the energy consumption and the network throughput. Based on the new metric and the Kalman prediction, we optimized the transmitting power of the BS and proposed an energy-efficient ARNC scheduling to improve quality of service. The simulation results also showed the effectiveness of the optimization and proposed methods compared with the traditional methods.

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