Recursive Access Class Barring for Machine Type Communications with PUSCH Resource Constraints

In massive cellular internet-of-things (IoT) networks, periodic and sporadic traffic may be well processed, while bursty traffic may cause an unexpected network congestion or overload problem. Thus, in this paper, we propose a generalized random access (RA) control mechanism considering whole steps of RA procedure and available resources at each step for handling bursty traffic in cellular IoT networks. The proposed RA control mechanism mainly consists of the estimation method for the number of backlogged nodes and the computation method for access class barring (ACB) factors. Through extensive computer simulations, the proposed RA control mechanism shows the enhanced performance in terms of the total service time, the average access delay, and the energy efficiency, compared to the conventional RA control mechanism, which only focuses on controlling preamble transmissions at the first step of the RA procedure.