RACH performance in massive machine-type communications access scenario

A Successive Interference Cancellation Based Random Access Channel Mechanism for Machine-to-Machine Communications in Cellular Internet-of-Things

“…Each M2M device in a cluster communicates with the cluster head using IEEE 802.11ah during the data collection phase and then forwards to the BS in data transmission phase which reduces the access delay and increases the successful access probability of M2M devices [15]. In [16], a simulation study has been carried out to study the impact of increasing number of devices on RACH success rate in the presence of only M2M traffic as well as mixed traffic. It has been concluded that the RACH performance is not affected by the available preambles and is limited by PDCCH resources [16].…”

“…In [16], a simulation study has been carried out to study the impact of increasing number of devices on RACH success rate in the presence of only M2M traffic as well as mixed traffic. It has been concluded that the RACH performance is not affected by the available preambles and is limited by PDCCH resources [16]. In [17], the authors have shown the effectiveness of the machine learning techniques in detecting the number of users that have transmitted a given preamble so as to control the network traffic in order to improve the success rate.…”

“…Whenever an M2M device gets ready to transmit data, it wakes up and attempts to connect to the BS. This connection mechanism from RRC-idle to RRCconnect state is termed as random access channel (RACH) mechanism [1].…”

“…A typical RACH mechanism involves exchange of four unique messages between each M2M device and the BS VOLUME 4, 2016 FIGURE 1: The random access mechanism [1].…”