Energy Efficient Power Allocation for Collaborative Mobile Clouds with Information and Power Transfer

Abstract

Prolonging the battery life of mobile terminals (MTs) is critical for mobile users, especially for the smartphone users to enjoy the high data rate services offered by the future wireless networks. A collaborative mobile cloud (CMC), which consists of several MTs offers one potential solution for reducing the energy consumption at the terminal side in the downlink. In addition, as RF signal can carry both information and energy simultaneously, the induced simultaneous wireless information and power transfer (SWIPT) is also capable of prolonging the battery of MTs. In this paper, the power allocation algorithm for CMC with SWIPT is formulated as a non-convex optimization problem which takes into account the baseband circuit power consumption, RF transmit and receiver power, harvested energy and the minimum required data rate. Accordingly, by exploiting the properties of nonlinear fractional programming, the formulated non-convex optimization problem, of which objective function is in fractional form, is transformed into an equivalent optimization problem having an objective function in subtractive form and is able to be solved in dual domain. Simulation results demonstrate that the proposed user scheduling and resource allocation algorithms can achieve significant energy saving performance.