Improving UAV base station energy efficiency for industrial IoT URLLC services by irregular repetition slotted-ALOHA

Abstract

In the past few years, the continual improvement of 5G technology has supported powerful IoT (Internet of Things) and IIoT (Industrial IoT) devices which have been used to provide a wide range of services. One of the service types that has been noticed recently is URLLC (Ultra-Reliable Low-Latency Communication) service that requires highly reliable communication and low latency bounds. In this paper, intending to meet the latency and reliability requirements of IIoT users located outdoor in a hard-to-reach area, we propose to use a UAV-BS (Unmanned Aerial Vehicle Base Station) for air-to-ground (A2G) communications. Despite the very fact that UAV-BSs have been used widely, yet they have some shortcomings in flight time. So we proposed an energy-efficient trajectory design method to reduce the UAV-BS’s energy consumption for both the communication and mobility functions while fulfilling the application’s reliability and latency requirements. We proposed a UMC-IRSA (UAV-BS Multi-Channel Irregular Repetition Slotted-ALOHA) method to adapt the New Radio (NR) distinct frame structure for IIoT users. The IIoT nodes are clustered by the UMC-IRSA method (based on Mahalanobis distance) to decrease the UAV-BS energy consumption. The simulation results show that the UMC-IRSA clustering method combined with the Q-Learning algorithm for clusters serving decreases the UAV-BS energy consumption for flying in fixed altitude. The reduction in energy consumption provided by using the combination of UMC-IRSA and Q-Learning, in comparison to the combination of UMC-IRSA and Random Serving, combination of CRP (Chinese Restaurant Process) and Q-Learning, and CRP and Random Serving is 19%, 24%, and 31% respectively.