SNR Threshold Scheduling for IoT Uplink Network

This paper investigates the impact of SNR (Signal-to-Noise Ratio)-based threshold scheduling on IoT (Internet of Things) uplink network performance. Threshold scheduling is a low-complexity technique utilizing channel state information (CSI) to boost network performance by only allowing transmission when the received SNR at the receiver is greater than a certain threshold. We use stochastic geometry to derive analytical and asymptotic expressions of the transmission success probability, active probability, and spatial capacity and characterize the network performance. We obtain a novel asymptotic bound for the signal-to-interference-plus-noise ratio (SINR) distribution of threshold scheduling. Furthermore, we adopt physical layer security to enhance the network security of threshold scheduling utilizing artificial noise. Based on these results, we optimize the spatial capacity of threshold scheduling under the constraints of reliability, security, and latency, then introduce a computationally efficient algorithm that finds the optimal SNR threshold maximizing the spatial capacity for a resource-limited IoT network. Various numerical results are provided to furnish the findings and gain insights to optimize the design of threshold scheduling.