On the Optimization of Outage Probability of Access Delay of MTDs in Cellular Networks for URLLC

Abstract

This paper focuses on the outage probability of access delay of Machine-to-Machine (M2M) communications in cellular networks, which is an important performance indicator for Ultra-Reliable and Low-Latency Communication (URLLC). Specifically, by deriving the outage probability for given maximum allowable access delay as a function of system parameters, the outage probability is minimized by optimally tuning the Access Class Barring (ACB) factor. For given outage probability bound, the admission control and resource allocation for the random access channel are further discussed, where the maximum number of Machine-Type Devices (MTDs) that can be admitted with given number of preambles and the minimum number of preambles that should be allocated with given network size are obtained. Compared to the standard setting where the ACB factor is fixed, significant gains in outage probability are demonstrated by optimally tuning the ACB factor according to the number of MTDs and the traffic input rate of each MTD. It is also shown that for given required outage probability bound, the optimal tuning of ACB factor enables much more MTDs to be admitted for given preamble resource, and requires much fewer preambles for given network size.