Class based priority scheduling to support Machine to Machine communications in LTE systems

Due to the ubiquitous coverage and seamless connectivity, cellular systems are very promising to support Machine-to-Machine (M2M) communications. But, all of the cellular networks are designed and optimized for Human-to-Human (H2H) or Human-to-Machine (H2M) communications and therefore facing several challenges due to incorporation of M2M communications. One of such challenges is efficient resource allocation to M2M applications without affecting or least affecting H2H applications. In order to address this challenge, we need application specific priority based scheduling algorithms in which based on the QoS of the application, radio resources are allocated. In this paper, we have classified and prioritized all H2H and M2M flows based on their QoS requirements. Resources are allocated first to higher priority classes and in a given class, they are allocated to H2H flows first. In order to ensure the QoS of H2H flows, a threshold is kept on the maximum number of radio resource blocks to be assigned to M2M flows in a scheduling interval. Performance of the proposed scheduling algorithm is evaluated using various metrics such as system throughput and average utility per class and compared against existing scheduling schemes.