Energy-Efficient Traffic Splitting for Time-Varying Multi-RAT Wireless Networks

This paper investigates the energy-efficient traffic splitting for time-varying wireless networks, which have been configured with multiple radio access technologies (multi-RATs). A single stream of the media content is split into multiple segments, which could be transmitted over multiple RATs simultaneously so that the complementary advantages of different RATs can be exploited. To address this problem, we formulate the traffic splitting as a long-term energy efficiency (EE) maximization problem with respect to the time-varying channel state information (CSI). An equivalent transformation method is proposed to convert the long-term nonconvex EE maximization problem into a concave optimization. To reduce the computational complexity, we develop a dynamic traffic splitting (DTS) algorithm, which iterates only one time when the network state changes. Then, we use the definition of tracking error to describe the difference between the DTS and the target optimal traffic splitting solution. After that, an adaptive-compensation traffic splitting (ACTS) algorithm is proposed to offset the tracking error so as to enhance the EE performance. More specifically, we give a sufficient condition for significantly eliminating the tracking errors of the ACTS algorithm. Simulation results show that the proposed ACTS algorithm obtains the EE performance comparable with the optimal solution at the overhead of only a single iteration at each timeslot of the network state acquisition.