We consider a multicell network where an amplify-and-forward relay is deployed in each cell to help the base station (BS) serve its cell-edge user. We assume that each relay scavenges energy from all received radio signals to process and forward the information data from the BS to the corresponding user. For this, a power splitter and a wireless energy harvester are implemented in the relay. Our aim is to minimize the total power consumption in the network while guaranteeing minimum data throughput for each user. To this end, we develop a resource management scheme that jointly optimizes three parameters, namely, BS transmit powers, power splitting factors for energy harvesting and information processing at the relays, and relay transmit powers. As the formulated problem is highly nonconvex, we devise a successive convex approximation algorithm based on difference-of-convex-functions (DC) programming. The proposed iterative algorithm transforms the nonconvex problem into a sequence of convex problems, each of which is solved efficiently in each iteration. We prove that this path-following algorithm converges to an optimal solution that satisfies the Karush-Kuhn-Tucker (KKT) conditions of the original nonconvex problem. Simulation results demonstrate that the proposed joint optimization solution substantially improves the network performance.
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