Cluster-based Random access with Data aggregation for Massive Machine Type Communications

Machine-type communication requires the infrastructure of the cellular network to adequately function. Therefore the need to share the same random access channel (RACH) with other communication devices poses a serious challenge considering the massive nature of machine-type communication devices (MTCDs). The current setup of access requests through the random access (RA) process is known to suffer congestion and network overload due to the variability of MTCDs. Data aggregation could be used to resolve the high collision rate by reducing the access request to the base station. However, this may introduce an excessive delay for the MTCDs. To solve this problems, we propose a clustered-based data aggregation access scheme (CDAAS) which reduces the access request to the base station while increasing the access success proportion of MTCDs. The proposed scheme utilizes MTCD clustering as well as effective data aggregation to increase access success proportion while meeting the delay requirement of the various MTCDs. Based on simulation results, our proposed scheme significantly outperforms the typical access schemes such as access class barring (ACB) in terms of access delay and access success proportion.