Multi-Site Energy Harvesting for Battery-Less Internet-of-Things Devices: Prospects and Limits.

Conventional Internet of things (IoT) devices are powered by batteries. However, batteries pose a risk of e-waste and chemical leakage to the environment. An alternative way to power remote IoT devices is to harvest ambient RF energy. It is especially beneficial when battery replacement is costly and could enable large-scale IoT deployments at net-zero energy cost. In this paper, we assume that the IoT devices periodically harvest energy from multiple surrounding base stations (BSs) and use the harvested energy to take sensor measurements and transmit related data packets. We propose an approximate method to analyze the feasibility of this approach in terms of which measurement rates can be supported. To this end, we assume a Poisson point process for the locations of the BSs. We derive mathematical expressions for the coverage probability (i.e., the probability that an IoT device harvests enough energy to operate at a given measurement rate) and the required BS site density in the presence of channel uncertainties, blockage, and harvesting nonlinearities. We derive the parameters of a Gamma distribution to approximate the distribution of the harvested power. For a coverage probability of 0.5, we derive a simplified approximate expression for the required site density that closely describes the one obtained empirically.