Traffic load access barring scheme for random-access channel in massive machine-to-machine and human-to-human devices coexistence in LTE-A

A major challenge for the development of the upcoming generations of wireless systems is to match the massive expansion of the Internet of things (IoT) applications along with the traditional human communication. Recently, 3rd Generation Partnership Project (3GPP) has suggested the use of LTE-A to support machine-to-machine (M2M) communications to realize the IoT applications. One of the key concerns is the random-access procedure in LTE-A, the existence of a massive number of M2M devices results in system overload and congestion in the random-access channel (RACH). In this paper, we present a new extension to the active barring-based random-access scheme. The proposed traffic load access barring (TLAB) RACH access scheme considers the dynamic changes in system traffic when setting the barring information. At the same time, the proposed scheme avoids unnecessary barring of some M2M devices. Our scheme improves the access delay that results from the barring of M2M devices by applying a new rule in the selection of classes to bar and classes to unbar. The simulation results show the superiority of our scheme in terms of success probability, average access delay, and average power consumption.