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

Peng Yang, Xing Xi, Tony Q.S. Quek, Jingxuan Chen, Xianbin Cao, Dapeng Wu

研究成果: Article同行評審


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, the theoretical analysis of the RACH procedure for massive IoT devices is challenging. To address this challenge, we first correlate the RACH request of an IoT device with the status of its maintained queue and analyze the evolution of the queue status by the probability theory. Based on the analysis result, we then derive the closed-form expression of the random access (RA) success probability, which is a significant indicator characterizing the RACH procedure of the device by the stochastic geometry theory. Besides, considering the agreement on converging different services onto a shared infrastructure, we investigate the radio access network (RAN) slicing for mIoT and bursty ultrareliable and low-latency communication (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. Simulation results demonstrate that the proposed SRO algorithm can effectively implement the service multiplexing of mIoT and bursty URLLC traffic.

頁(從 - 到)14258-14275
期刊IEEE Internet of Things Journal
出版狀態Published - 2021 九月 15

All Science Journal Classification (ASJC) codes

  • 訊號處理
  • 資訊系統
  • 硬體和架構
  • 電腦科學應用
  • 電腦網路與通信


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