A Scheduling Algorithm Based Self-Learning Technique for Smart Grid Communications over 4G Networks

Abstract—The latest 4G wireless technology, Long Term Evolution (LTE), is expected to be a promising wireless network for smart grid communications due to its high data rate and low latency. However, Scheduling mechanism has a crucial role on the smart grid performance since it is responsible for resources allocation process among users taking into account delay, fairness, throughput and channel status. LTE has not been intended for smart grid communications which results in unfair resource allocation between LTE users and smart grid applications. Moreover, the smart grid utilizes real time communications which have to be prioritized and allocated more resources in some cases. Following the requirements for a scheduling algorithm that takes into account smart grid communications and offers a compromise among different classes, this paper proposes a two level scheduling algorithm for smart grid communications in order to meet the requirements of these classes. In first level, the smart grid applications are classified into three classes where the resources are distributed based on the Packet Drop Rate (PDR). In second level, a novel queuing algorithm is proposed to prioritize the RT users with shortest delay. Furthermore, the proposed algorithm’s performance is evaluated in term of throughput, delay and fairness index and compared with Frame Level Scheduler (FLS) and Proportional Fairness (PF) algorithms where the proposed approach illustrates higher overall system performance in terms of throughput, delay and fairness.