Abstract

In this paper, we consider a fully sustainable cooperative communication system which consists of multiple source nodes with radio-frequency (RF) energy harvesting capabilities, a half-duplex relay node with renewable energy supplies, and a destination node. Specifically, the relay node is powered by the green energy harvested from renewable sources such as solar or wind, while the source nodes are wirelessly charged by the RF energy from the relay node’s forwarding signals to the destination node. An optimal joint time scheduling and power allocation problem is formulated to achieve the maximum system sum-throughput of the users over a finite time horizon. To tackle the formulated NP-hard non-convex mixed integer nonlinear programming problem, we first analyze its upper bound by problem reformulation and relaxation, which can be simplified by the directional water filling algorithm and iteratively solved by sequential parametric convex approximation. We then propose an optimal branch-and-bound framework to solve the formulated problem, and develop an efficient sub-optimal offline algorithm and a heuristic online algorithm to reduce the computational complexity. Finally, extensive simulations are conducted to verify the superiority of the proposed solution and demonstrate that the sub-optimal algorithm approaches the performance upper bound with polynomial time complexity.

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