Abstract
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.
Highlights
IntroductionWith the wide use of smartphones, tablets, and machine-to-machine (M2M) devices for various applications and services, the amount of mobile data traffic has grown dramatically in recent years [1]
With the wide use of smartphones, tablets, and machine-to-machine (M2M) devices for various applications and services, the amount of mobile data traffic has grown dramatically in recent years [1].The deployment of low-power small base stations (BSs) in hotspot areas is a potential solution to cope with the increase in traffic and devices [2]
Energy Efficiency Proportional Fairness Utility Function. Considering that both information transmission and wireless power transfer contribute to the energy efficiency of networks, we are interested in the typical node since its average performance represents the average system performance
Summary
With the wide use of smartphones, tablets, and machine-to-machine (M2M) devices for various applications and services, the amount of mobile data traffic has grown dramatically in recent years [1]. By maximizing the relaxed utility function, we can obtain the optimal receive threshold and user association bias for the tradeoff between information transmission and power transfer. This allows us to derive an efficient iterative algorithm for obtaining the optimal solution. The average transmission rate and harvesting energy of nodes in WPCNs are analyzed and the impact of user association bias and receive threshold on EE of networks is revealed.
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