Robust Uplink Resource allocation in LTE Networks With M2M Devices as an Infrastructure of Internet of Things

Machine-to-Machine (M2M) communication is an emerging technology for communication between machines without human intervention. The main issue for cellular operators and service providers is to find a way to manage the high volume of these machine type communications and current human type communications for allocating network resources. An overall solution for large access management issues is to use application prioritization and priority class based traffic scheduling. In order to enhance the system efficiency and to reduce waste of resources, this paper investigates a creative type based dynamic priority scheduling mechanism for M2M/H2H coexistence traffics in LTE-A networks. Dynamic resources allocation is a significant challenge due to the uncertainty introduced by the network, QoS and energy efficiency requirements. The proposed solution is based on type-2 fuzzy logic controller expert system to anticipate and manage uncertainties. The performance of the proposed algorithm is evaluated by various metrics such as delay, throughput, and bandwidth utilization.