RAN Slicing for Massive IoT and Bursty URLLC Service Multiplexing: Analysis and Optimization

Future wireless networks are envisioned to serve massive Internet of things (mIoT) via some radio access technologies, where the random access channel (RACH) procedure should be exploited for IoT devices to access the networks. However, modelling of the dynamic process of RACH of massive IoT devices is challenging. To address this challenge, we first revisit the frame and minislot structure of the radio access network (RAN). Then, we correlate the RACH request of an IoT device with its queue status and analyze the evolution of the queue status. Based on the analysis result, we derive the closed-form expression of the random access (RA) success probability of the device. Besides, considering the agreement on converging different services onto a shared infrastructure, we investigate the RAN slicing for mIoT and bursty ultra-reliable and low latency communications (URLLC) service multiplexing. Specifically, we formulate the RAN slicing problem as an optimization one to maximize the total RA success probabilities of all IoT devices and provide URLLC services for URLLC devices in an energy-efficient way. A slice resource optimization (SRO) algorithm exploiting relaxation and approximation with provable tightness and error bound is then proposed to mitigate the optimization problem.