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Energy harvesting is a technology for enabling green, sustainable, andautonomous wireless networks. In this paper, a large-scale wireless networkwith energy harvesting transmitters is considered, where a group oftransmitters forms a cluster to cooperatively serve a desired receiver amidinterference and noise. To characterize the link-level performance, closed-formexpressions are derived for the transmission success probability at a receiverin terms of key parameters such as node densities, energy harvestingparameters, channel parameters, and cluster size, for a given cluster geometry.The analysis is further extended to characterize a network-level performancemetric, capturing the tradeoff between link quality and the fraction ofreceivers served. Numerical simulations validate the accuracy of the analyticalmodel. Several useful insights are provided. For example, while morecooperation helps improve the link-level performance, the network-levelperformance might degrade with the cluster size. Numerical results show that asmall cluster size (typically 3 or smaller) optimizes the network-levelperformance. Furthermore, substantial performance can be extracted with arelatively small energy buffer. Moreover, the utility of having a large energybuffer increases with the energy harvesting rate as well as with the clustersize in sufficiently dense networks.

A Stochastic Geometry Analysis of Large-scale Cooperative Wireless Networks Powered by Energy Harvesting