Throughput Maximization of Wireless-Powered Communication Networks: An Energy Threshold Approach

In this paper, we consider a wireless-powered communication network (WPCN) where one mobile hybrid access point (HAP) coordinates the wireless energy transfer to sensor nodes and receives data from sensor nodes, which are powered exclusively by the harvested wireless energy. As the harvest-then-transmit protocol is employed by sensor nodes, a major challenge lies on the tradeoff between achievable throughput and energy harvesting opportunity of sensor nodes. Confronting this challenge, we develop an energy threshold approach by jointly considering geographic locations and energy states of sensor nodes, where wireless energy transfer occurs when none of the sensor nodes in the range of data transmission has more energy than the threshold, otherwise data transmission from one randomly chosen qualified sensor node to the HAP occurs. By comparing the range of energy harvesting and that of data transmission, we divide the network topology into two cases for throughput analysis, and formulate the energy states of sensor nodes as Markov chain processes with different energy state spaces in the two cases. Through monotonicity analysis of achievable throughput and probability distribution of energy states, we prove the existence of the optimal energy threshold that maximizes the achievable throughput, and find that the achievable throughput under infinite battery size could be viewed as the upper bound of that under the limited battery size. Finally, simulation results validate theoretical results of the optimal energy threshold, and show the impacts of system parameters on the achievable throughput.

Automated summary

This paper investigates energy management in a wireless-powered communication network and proposes a method to dynamically adjust energy transfer mechanism based on the energy states and geographic locations of sensor nodes. By comparing the energy harvesting and data transmission ranges, the network topology is divided into two cases for throughput analysis, which ultimately proves the existence of an optimal energy threshold, enhancing the achievable throughput.