Abstract
In this paper, we investigate the power–delay tradeoff for the newly emerging wireless powered communication networks, in which wireless powered devices (WPDs) harvest energy from a power station via wireless energy transfer in the downlink and then communicate with an information receiving station in the uplink. Each WPD is equipped with an energy buffer and a data buffer to store the random harvested energy and the bursty data arrivals, respectively. To minimize the time-averaged power consumption, a stochastic optimization problem is formulated subject to both constraints of data queue stability and harvested energy availability. By employing Lyapunov optimization theory, we transform the stochastic optimization problem into a series of deterministic problems, where each is further proved to become the standard convex optimization problem and, hence, can be effectively and optimally solved by standard convex optimization techniques. Correspondingly, we propose an Online Power and TIMe Allocation (Optima) algorithm, which requires no a priori distribution knowledge of channel states and data arrivals. Most importantly, the proposed algorithm achieves the power–delay tradeoff as $[\mathcal{O}(\text{1}/V),\mathcal{O}(V)]$ , with $V$ being a system control parameter, and provides a significant method to control the power–delay performance on demand in system design. Simulation results verify the theoretical analysis and validate the effectiveness of the proposed algorithm.
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