Prediction of QoS Outage Probability for Wireless Communication in Factory Environments

In manufacturing and logistics, various applications exploiting IoT devices are started to be used. Although there is a demand for wireless connection between the IoT devices to networks, obstacles such as radio frequency interference, multipath-rich propagation, and movement of objects make communication unstable. The instability can cause a system failure of IoT applications. Since the QoS outage does not occur frequently in actual systems, the training of QoS outage events may be insufficient to accurately predict future QoS values. Therefore, we propose a method to estimate QoS outage probability from the predicted future QoS, distribution of prediction error, and required QoS. The proposed method can achieve high estimation accuracy by obtaining and using different error distributions according to the rarity of the observed sequence. Simulation results based on a theoretical throughput analysis of wireless LAN show that the proposed method can appropriately predict the QoS outage probability.