Two-Timescale Resource Allocation for Wireless Powered D2D Communications With Self-Interested Nodes

Wireless powered device-to-device (D2D) communications can empower D2D communications via a power station (PS) in a self-sustainable manner. In this paper, aided by an incentive mechanism, we investigate the dynamic resource allocation for content transmission in wireless powered D2D communications with self-interested nodes including D2D transmitters (D2D-Txs) and PS. Stochastic optimization is developed to maximize the average network utility under the constraints of the limited data buffer, energy capacity, and incentives. Then, to coordinate the different timescales for the network state variation, the problem of stochastic optimization is converted into two subproblems via two-timescale Lyapunov optimization technique. Specifically, at the large timescale where the D2D-Tx's resource states (data queue, energy resource, and incentive) change slowly, we obtain the solution of a joint rate adaption and energy trading problem. While, at the small timescale where the channel state experiences rapid variation, we develop a closed-form expression of power factor by solving a transmit power control problem, which is non-convex owing to the interference among D2D-Txs. Additionally, an online two-timescale resource allocation (OTTRA) algorithm is proposed, and the performance bounds of the algorithm are characterized theoretically in terms of the utility-delay tradeoff. The numerical results exhibit that the OTTRA algorithm not only encourages the cooperative content transmission and ET among self-interested nodes, but also ensures a satisfied network performance in the long term.