Performance Analysis of Ambient RF Energy Harvesting with Repulsive Point Process Modeling

TL;DR

This paper analyzes the performance of ambient RF energy harvesting for battery-free wireless sensors using stochastic geometry, specifically modeling ambient sources with a repulsive point process to capture realistic spatial distributions.

Contribution

It introduces a novel analysis using Ginibre alpha-DPP to model ambient RF sources, deriving energy harvesting metrics and outage bounds for different receiver architectures.

Findings

Stronger source repulsion improves sensor energy harvesting efficiency.

Derived closed-form expressions for energy harvesting rate and variance.

Provided guidelines for optimal time-switching parameters.

Abstract

Ambient RF (Radio Frequency) energy harvesting technique has recently been proposed as a potential solution to provide proactive energy replenishment for wireless devices. This paper aims to analyze the performance of a battery-free wireless sensor powered by ambient RF energy harvesting using a stochastic geometry approach. Specifically, we consider the point-to-point uplink transmission of a wireless sensor in a stochastic geometry network, where ambient RF sources, such as mobile transmit devices, access points and base stations, are distributed as a Ginibre alpha-determinantal point process (DPP). The DPP is able to capture repulsion among points, and hence, it is more general than the Poisson point process (PPP). We analyze two common receiver architectures: separated receiver and time-switching architectures. For each architecture, we consider the scenarios with and without co-channel interference for information transmission. We derive the expectation of the RF energy harvesting rate in closed form and also compute its variance. Moreover, we perform a worst-case study which derives the upper bound of both power and transmission outage probabilities. Additionally, we provide guidelines on the setting of optimal time-switching coefficient in the case of the time-switching architecture. Numerical results verify the correctness of the analysis and show various tradeoffs between parameter setting. Lastly, we prove that the sensor is more efficient when the distribution of the ambient sources exhibits stronger repulsion.