A Nonlinear Recursive Model Based Optimal Transmission Scheduling in RF Energy Harvesting Wireless Communications
Computing Sciences and Computer Engineering
© 2002-2012 IEEE. The transmission scheduling is a critical problem in radio frequency (RF) energy harvesting communications. Existing transmission strategies are mainly based on a conventional model, in which the amount of harvested energy is modeled as predetermined random variables and the data transmission is arranged in a fixed feasible energy tunnel. In this paper, we show through the theoretical analysis and experimental results that due to the nonlinear battery charging characteristics, the harvested energy will largely depend on the transmission strategy. The bounds of feasible energy tunnel become dynamic. To describe a practical ambient energy harvesting process more accurately, a new nonlinear recursive model is proposed by adding a feedback loop that reflects the real-time influence of the data transmission on the energy harvesting process. In addition, to improve communication performance, we redesign the optimal transmission scheduling strategy based on the new model. In order to cope with the challenge of the endless loop in the new model, a recursive algorithm is developed. The simulation results reveal that the new transmission scheduling strategy can balance the efficiency of energy harvest and energy utilization regardless of the length of energy packets, thus improving the throughput performance of RF energy harvesting wireless communications.
IEEE Transactions on Wireless Communications
(2020). A Nonlinear Recursive Model Based Optimal Transmission Scheduling in RF Energy Harvesting Wireless Communications. IEEE Transactions on Wireless Communications, 19(5), 3449-3462.
Available at: https://aquila.usm.edu/fac_pubs/17865