Zhang Jing, Zhou Qingjie, Ng Derrick Wing Kwan, Jo Minho
School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, China.
School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney 2052, Australia.
Sensors (Basel). 2017 Sep 15;17(9):2125. doi: 10.3390/s17092125.
In wireless powered communication networks (WPCNs), it is essential to research energy efficiency fairness in order to evaluate the balance of nodes for receiving information and harvesting energy. In this paper, we propose an efficient iterative algorithm for optimal energy efficiency proportional fairness in WPCN. The main idea is to use stochastic geometry to derive the mean proportionally fairness utility function with respect to user association probability and receive threshold. Subsequently, we prove that the relaxed proportionally fairness utility function is a concave function for user association probability and receive threshold, respectively. At the same time, a sub-optimal algorithm by exploiting alternating optimization approach is proposed. Through numerical simulations, we demonstrate that our sub-optimal algorithm can obtain a result close to optimal energy efficiency proportional fairness with significant reduction of computational complexity.
在无线供电通信网络（WPCN）中，研究能量效率公平性对于评估节点接收信息和收集能量的平衡至关重要。在本文中，我们提出了一种用于WPCN中最优能量效率比例公平性的高效迭代算法。主要思想是利用随机几何来推导关于用户关联概率和接收阈值的平均比例公平效用函数。随后，我们证明了松弛的比例公平效用函数分别对于用户关联概率和接收阈值是凹函数。同时，提出了一种利用交替优化方法的次优算法。通过数值模拟，我们表明我们的次优算法能够在显著降低计算复杂度的情况下获得接近最优能量效率比例公平性的结果。
