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Joint Optimization of Time and Power in Energy-Constrained Wireless Powered Communication Network

In this paper, we study the common throughput optimization problem with finite energy capacity in a wireless powered communication network (WPCN). In WPCNs, a hybrid energy and information access point broadcast an energy signal to wireless nodes on the downlink. Wireless nodes which are near to the energy provider harvests more energy in comparison to far users and send information signals in the uplink allocated time slots by utilizing the energy harvested in the downlink phase. In this paper, we jointly optimize the time and power allocation to maximize the minimum throughput of a wireless node. For this, we propose a sequential parametric convex approximation (SPCA) based iterative algorithm to find the feasible solution for near-optimal time and power allocation in the non-convex optimization problem. The proposed solution maximizes the minimum throughput by allocating more time and power to far wireless nodes and thus, increase the average throughput of the network. Through simulations and results, it is verified that the proposed solution performs better in comparison to other solutions.