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An Efficient Spectrum Utilization Scheme for Energy-Constrained IoT Devices in Cellular Networks

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The cellular Internet of Things envisions the connection of billions of devices with the Internet through cellular networks. These Internet-of-Things Devices (IoDs) are normally energy constrained. In order to provide… Click to show full abstract

The cellular Internet of Things envisions the connection of billions of devices with the Internet through cellular networks. These Internet-of-Things Devices (IoDs) are normally energy constrained. In order to provide network services to these energy-constrained IoDs, this article proposes a cellular architecture, whereby IoDs utilize resources of the cellular network for energy harvesting and information transmission. The radio resources of the cellular network are divided by time and frequency, and each time-frequency block is called a cellular resource block (CRB). At the beginning of each time slot, IoDs select CRBs randomly. IoDs receive the control information from the base station (BS) and extract the resource allocation information about the selected CRB. When selected CRBs are busy, IoDs harvest energy from the radio-frequency signals of the BS, and then they use that stored energy to transmit their information to the cluster head (CH) when selected CRBs are idle. In order to obtain the average harvested energy, the random distance between cellular BS and randomly deployed IoD has been statistically calculated. Using the finite-state Markov chain model, the transmission probability of each IoD is calculated. Analytical expressions for the collision probability and average throughput of IoDs are also derived. To verify the derived analytical expressions, system-level simulations are carried out, and it is shown that the analytical results match the simulation results. Moreover, the overall performance of the considered architecture is studied for different system parameters.

Keywords: internet things; efficient spectrum; cellular networks; energy constrained; energy; information

Journal Title: IEEE Internet of Things Journal
Year Published: 2021

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