Abstract
This paper investigates the self-sustainability of an overlay Internet of Things (IoT) network that relies on harvesting energy from a downlink cellular network. Using stochastic geometry and queueing theory, we develop a spatiotemporal model to derive the steady state distribution of the number of packets in the buffers and energy levels in the batteries of IoT devices given that the IoT and cellular communications are allocated disjoint spectrum. Particularly, each IoT device is modelled via a two-dimensional discrete-time Markov Chain (DTMC) that jointly tracks the evolution of the data buffer and energy battery. In this context, stochastic geometry is used to derive the energy generation at the batteries and the packet transmission success probability from buffers taking into account the mutual interference from other active IoT devices. To this end, we show the Pareto-Frontiers of the sustainability region, which define the network parameters that ensure stable network operation and finite packet delay. Furthermore, the spatially averaged network performance, in terms of transmission success probability, average queueing delay, and average queue size are investigated. For self-sustainable networks, the results quantify the required buffer size and packet delay, which are crucial for the design of IoT devices and time critical IoT applications.
Highlights
The Internet of Things (IoT) is the paradigm that bridges the physical and cyber worlds such that everything and anything will be connected to the Internet
To the best of our knowledge, this paper presents the first mathematical model that jointly accounts for spatiotemporal traffic generation, energy harvesting problem, and mutual interference between devices in a large scale IoT network
Using stochastic geometry and queueing theory, this paper develops a spatiotemporal mathematical model for selfsustainable IoT networks that recycles the radio frequency (RF)-energy of downlink cellular network
Summary
The Internet of Things (IoT) is the paradigm that bridges the physical and cyber worlds such that everything and anything will be connected to the Internet. None of the aforementioned works consider unsaturated data buffers and unsaturated energy queues to study the self-sustainability of large scale IoT networks. This paper proposes a novel spatiotemporal mathematical model, based on stochastic geometry and queueing theory, to characterize and design self-sustainable IoT networks. To the best of our knowledge, this paper presents the first mathematical model that jointly accounts for spatiotemporal traffic generation, energy harvesting problem, and mutual interference between devices in a large scale IoT network. A novel spatiotemporal model is developed to account for the unsaturated batteries and data buffers for IoT networks powered by cellular downlink energy. While the packet generation is assumed to be geometric, energy generation and successful packet transmissions are model via a phase type (PH) distribution that accounts for, respectively, energy harvesting from the downlink cellular network and mutual interference among the IoT devices. We illustrate the spectrum scarcity and energy scarcity tradeoff within self-sustainable IoT networks
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