Performance analysis of access class barring for next generation IoT devices

• Main Authors: Maira Alvi, Khamael M. Abualnaja, Waqas Tariq Toor, Muhammad Saadi
• Format: Article
• Language: English
• Published: Elsevier 2021-02-01
• Series: Alexandria Engineering Journal
• Subjects: IoT; Random access channel; Machine type communication; Next generation networks; Network protocols; Contention resolution
• Online Access: http://www.sciencedirect.com/science/article/pii/S1110016820305123

Massively dense deployment of Internet of Things (IoT) devices has put a stringent requirement on cellular networks to provide convenient service for not only human type traffic (HTC) but also for bursty traffic for IoT devices. Any bottleneck in the random access process means the bottleneck of the entire system because it is the first step before scheduled access. Access class barring (ACB) scheme is one of the key schemes in long term evolution advanced (LTE-A) to control the congestion in a random access process in which the access of some devices is barred based on a parameter, ACB factor, to relieve the congestion. In this paper, we analyze the ACB factor and criteria of its selection as the optimal selection of the ACB factor is essential for the maximum throughput of the system. The metrics used in the analysis of the ACB factor are total service time (TST), access delay and maximum collision, success, and idle probabilities with fixed and optimal ACB factor. Simulation results in MATLAB provide the complete picture of the behavior of the ACB factor and its control, used in the random access process.