Analysis of $K$-Tier Uplink Cellular Networks With Ambient RF Energy Harvesting

We use stochastic geometry to develop a comprehensive modeling framework for K-tier uplink cellular networks with RF energy harvesting from the concurrent cellular transmissions. In the considered system model, channel inversion power control is used and cellular users are equipped with energy storage units. We also use tools from queueing theory, namely, Markov chain analysis, to model the level of stored energy in each user's battery. A successful transmission is assumed only when the amount of energy stored in a user's battery is sufficient to perform channel inversion with a received signal-to-interference ratio (SIR) above a predefined threshold. The performance of the proposed system model is evaluated in terms of the transmission probability, the (SIR) coverage probability, and the overall success probability. Using Poisson point processes (PPPs) enables us to derive simple expressions for these performance metrics in order to obtain insights for network design and optimization. We show the effect of varying the different network parameters such as the spatial density of BSs and the receiver sensitivity. In addition, we discuss several special cases and provide guidelines on the extensions of the proposed framework. We show that the gain of using RF energy harvesting can be highly improved by a proper choice of the network design parameters.