On Stochastic Geometry Analysis and Optimization of Wireless-Powered Cellular Networks

In this paper, a new mathematical framework to the analysis and optimization of wireless-powered cellular networks is introduced. The proposed approach leverages stochastic geometry for system-level analysis of cellular networks, by modeling base station locations as points of a Poisson point process. The trade-offs emerging from simultaneous wireless information and power transfer are characterized through the joint cumulative distribution function of average harvested energy and average rate, which is conveniently formulated in terms of an easy-to-compute two-fold integral. The analysis shows that an optimal operating point for system-level optimization exists, as well as that network densification and directional beamforming constitute essential enablers for enhancing the performance. Finally, the fundamental trade-offs emerging in wireless-powered cellular networks are quantified through the concept of feasibility regions.