Online Policies for Throughput Maximization of Energy-Constrained Wireless-Powered Communication Systems

In this paper, we consider the design of online transmission policies in a single-user wireless-powered communication system over an infinite horizon, aiming at maximizing the long-term system throughput for the user equipment (UE) subject to a given energy budget. The problem is formulated as a constrained Markov decision process problem, which is subsequently converted into an equivalent Markov decision process (MDP) problem via the Lagrangian approach. The corresponding optimal resource allocation policy is obtained through jointly solving the corresponding MDP problem and updating the Lagrangian multiplier. To reduce the complexity, a sub-optimal policy named "quasi-best-effort" is proposed, where the transmit power of the UE is structurally designed so that in each block the UE either exhausts its entire battery energy for transmission or suspends its transmission. To validate the effectiveness of our proposed policy, extensive numerical simulations are conducted with various system parameters. The results show that the proposed quasi-best-effort policy requires far less computation time but achieves a similar long-term throughput performance as the optimal policy.