Owing to the ubiquitous availability of radio-frequency (RF) signals, RF energy harvesting is emerging as an appealing solution for powering Internet-of-Things (IoT) devices. In this paper, we model and analyze an IoT network which harvests RF energy and receives information from the same wireless network. In order to enable this operation, each time slot is partitioned into charging and information reception phases. For this setup, we characterize two performance metrics: 1) energy coverage and 2) joint signal-to-interference-plus-noise and energy coverage. The analysis is performed using a realistic spatial model that captures the spatial coupling between the locations of the IoT devices and the nodes of the wireless network (referred, henceforth, as the IoT gateways), which is often ignored in the literature. In particular, we model the locations of the IoT devices using a Poisson cluster process and assume that some of the clusters have IoT gateways (GWs) deployed at their centers while the other GWs are deployed independently of the IoT devices. The level of coupling can be controlled by tuning the fraction of total GWs that are deployed at the cluster centers. Due to the inherent intractability of computing the distribution of shot noise process for this setup, we propose two accurate approximations, using which the aforementioned metrics are characterized. Multiple system design insights are drawn from our results. For instance, we demonstrate the existence of optimal slot partitioning that maximizes the system throughput. In addition, we explore the effect of the level of coupling between the locations of the IoT devices and the GWs on this optimal slot partitioning. Particularly, our results reveal that the optimal value of time duration for the charging phase increases as the level of coupling decreases.